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Table of Contents

1 Annual report 2012 of DISC ..................................................................................................1

1.1 Introduction ........................................................................................................................1

1.2 Organization ......................................................................................................................1

1.3 Research Program DISC 2012 ..........................................................................................6

1.4 Teaching program ..............................................................................................................7

1.5 Summer School ...............................................................................................................34

1.6 Winter Course ..................................................................................................................38

1.7 Benelux Meeting ..............................................................................................................38

1.8 DISC PhD Thesis Award 2011 .........................................................................................41

1.9 PhD Theses 2012 ............................................................................................................42

1.10 Awards ...........................................................................................................................44

1.11 3TU Centre of Excellence Intelligent Mechatronic Systems ..........................................44

1.12 National MSc programmes ............................................................................................45

1.13 Management report 2012 ..............................................................................................46

1.14 Financial report (in Eur) .................................................................................................48

1.15 UNIT DISC .....................................................................................................................49

Delft University of TechnologyFaculty of Mechanical, Maritime and Materials Engineering (3mE)Delft Center for Systems and Control (DCSC) .......................................................................50

Delft University of TechnologyFaculty: Electrical Engineering, Mathematics and Computer ScienceDepartment: Delft Institute of Applied MathematicsChair: Optimization and Systems Theory (OST) ....................................................................99

Delft University of TechnologyFaculty of Aerospace EngineeringControl and Simulation ........................................................................................................102

Eindhoven University of TechnologyDepartment of Mechanical EngineeringDynamics and Control Group, Control Systems Technology Group & Hybrid and NetworkedSystems ...............................................................................................................................110

Eindhoven University of TechnologyDepartment of Electrical Engineering – Control Systems ....................................................132

University of TwenteRobotics and Mechatronics(RaM)(Formerly Control Engineering (CE)) ..............................157

University of Twente – Faculty of Electrical Engineering, Mathematics and ComputerScience

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Department of Applied MathematicsHS Group .............................................................................................................................183

University of GroningenIndustrial Technology and Management (ITM) .....................................................................191

University of GroningenJohann Bernoulli Institute for Mathematics and Computer ScienceResearch Program SystemsControl and Applied Analysis ...............................................................................................205

Tilburg UniversityFaculty of Economics and Business Administration Department of Econometrics andOperations Research ...........................................................................................................213

Wageningen Universiteit.Departement Agrotechnologie en Voedingswetenschappen, leerstoelgroep BiomassRefinery & Process Dynamics .............................................................................................216

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1 Annual report 2012 of DISC

1.1 Introduction

Research school DISC is an interuniversity research institute and graduate schoolthat unites all academic groups in the Netherlands that are active in systems andcontrol theory and engineering. It offers a nationally organized graduate programmefor PhD students in this field.

Being founded by the Delft and Eindhoven Universities of Technology and theUniversity of Twente, a majority of participants in the school are affiliated with thefaculties of electrical engineering, mechanical engineering, and mathematics of thesethree universities. A large number of other departments and institutes participate inDISC under various agreements.

The ambitions of DISC are:• To provide a PhD programme of high quality and internationally recognized level;• To provide PhD students with a national and international network and to support

them in their development towards independent researchers that are part of theinternational community and whose research is recognized according to internationalstandards;

• To develop the field of systems and control through coordinated research in bothfundamental and technology directed programs, and to represent this field of sciencein national and international networks, consortia and boards;

• To use the position of DISC as center of expertise for dissemination of knowledge onsystems and control theory and engineering in the widest sense.

1.2 Organization

DISC is governed by a board consisting of representatives of the 3TU’s, the otheruniversities, and an external member. The daily operation of DISC is directed by thescientific director, who is assisted by the DISC secretariat.

Board membersProf.dr. F. Eising (UT), chairmanProf.dr. S. Weiland (TU/e-EE)Prof.dr. H. Nijmeijer (TU/e-ME)Prof.dr. A.J. van der Schaft (RUG)Prof.dr. R. Babuska (TUD-DCSC)

Prof.dr. H.J. Zwart (UT-AM)

Scientific DirectorProf.dr.ir. P.M.J. Van den Hof (TUD)

SecretaryMrs. Saskia van der Meer (TUD)

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Contact informationdisc = dutch institute of systems and controlDelft University of TechnologyMekelweg 2 = 2628 CD = DelftTel: +31 (0)15 2785572Fax:+31 (0)15 2786679Email:[email protected]://www.disc.tudelft.nl

The DISC advisory board, composed of leading representatives from industrial,university and institutional bodies, meets once a year with the DISC board to discussissues concerning strategy and policy.

Members Advisory boardProf.dr.ir. J. Vandewalle (KU-Leuven) (chairman)Prof.ir. J.C.M. Baeten (TU/e)Dr.ir. H. Borggreve (ASML)Dr.ir. D.A. Schipper (Demcon)Dr.ir. E.J. Sol (TNO-Industrie en Techniek)Dr. W. Schinkel (Shell)

The scientific director is supported by a management team consisting of all headsof DISC departments.

See fig. 1.

Management team

Prof.dr.ir. A.W. Heemink (TUD-DIAM)Prof.dr. A.A. Stoorvogel (UT-AM)Prof.dr.ir. S. Stramigioli (UT-EE)Prof.dr.ir. P.M.J. Van den Hof (TU/e-EE)Prof.dr.ir. W.P.M.H. Heemels (TU/e-ME)Prof.dr. H. Nijmeijer (TU/e-ME)Prof.dr.ir. M. Steinbuch (TU/e-ME)Dr.ir. R.G.K.M. Aarts (UT-AM)(temporary)Prof.dr. A.C.M. Ran (VU)Dr.ir. K.J. Keesman (WU)

Prof.dr. J.M. Schumacher (TU-CentER)Prof.dr.ir. J.H. van Schuppen (CWI)Dr.ir. R.L.M. Peeters (MU)Prof.dr. C. De Persis (RUG-ITM)Prof. J.M.A. Scherpen (RUG-ITM)Prof.dr. H.L. Trentelman (RUG-JBI)Prof.dr.ir. M. Mulder (TUD-AEProf.dr. R. Babuska (TUD-DCSC)Prof.dr.ir. B. De Schutter (TUD-DCSC)Prof.dr.ir. M. Verhaegen (TUD-DCSC)

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Fig. 1. Organizational structure

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Full-time professorsDelft University of Technology

Prof.dr. R. Babuska, MScProf.dr.ir. B. De SchutterProf.dr.ir. M. Verhaegen

Faculty of Mechanical, Maritime andMaterials Engineering;Delft Center for Systems and Control

TUD-DCSC

Prof.dr.ir. A.W. HeeminkFaculty of Electrical Engineering,Mathematics and Computer ScienceDepartment of Applied Mathematics

TUD-DIAM

Prof.dr.ir. M. MulderFaculty of Aerospace EngineeringDepartment of Aerospace Design,Integration & Operations; SectionControl and Simulation

TUD-AE

Eindhoven University of Technology

Prof.dr.ir. M. SteinbuchProf.dr. H. NijmeijerProf.dr.ir. W.P.M.H.Heemels

Department of Mechanical EngineeringSection Dynamics and ControlTechnology,Section Control Systems Technology

TU/e-ME

Prof.dr.ir. P.M.J. Van denHof Prof.dr. S. WeilandProf.dr.ir. P.P.J. van denBosch

Department of Electrical EngineeringSection Control Systems

TU/e-EE

University of Twente

Prof.dr.ir. S. StramigioliFaculty of Electrical Engineering,Mathematics and Computer ScienceDepartment of Electrical EngineeringSection Control Engineering

UT-EE

Prof.dr. A.A. StoorvogelProf.dr. A. Bagchi

Faculty of Electrical Engineering,Mathematics and Computer ScienceDepartment of Applied MathematicsSystems, Signals and Control Group

UT-AM

Dr.ir. R.G.K.M. AartsFaculty of Engineering TechnologyDepartment of Mechanical EngineeringGroup Mechanical Automation andMechatronics

UT-ME

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CWI Amsterdam

Prof.dr.ir. J.H. vanSchuppen

Center for Mathematics and ComputerScienceCluster Modelling, Analysis andSimulationsResearch Group Control and SystemTheory

CWI

VU University Amsterdam - Stieltjes Institute

Prof.dr. A.C.M. RanFaculty of SciencesDepartment of MathematicsSection Mathematical Analysis

VU

University of Groningen

Prof.dr. A.J. van der SchaftProf.dr. H.L. Trentelman

Faculty of Mathematics and NaturalSciencesJohann Bernoulli Institute forMathematics and Computer Science

RUG-JBI

Prof.dr.ir. J.M.A. ScherpenProf.dr. C. De Persis

Faculty of Mathematics and NaturalSciencesIndustrial Engineering and ManagementDepartment of Discrete Technology andDepartment Smart ManufacturingSystems

RUG-ITM

Maastricht University

Prof.dr.ir. R.L.M. PeetersFaculty of Humanities and ScienceDepartment of Knowledge Engineering

MU

Tilburg University

Prof.dr. J.M. SchumacherFaculty of Economics and BusinessAdministration; CentER - Department

TU

of Econometrics and OperationsResearch

Wageningen University

Dr.ir. K.J. KeesmanDepartment of Agrotechnology andFood Sciences; Systems and ControlGroup

WU

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1.3 Research Program DISC 2012

The research program of DISC consists of fundamental and applied scientific researchin the domain of systems and control theory and engineering. By exploiting thefundamental principle of feedback, control systems enable the realization of high-techsystems in all domains of engineering science with fascinating performance in termsof speed, accuracy, autonomy and adaptability to varying circumstances.

The research domain employs modern techniques from information and computertechnology to analyze, control and optimize dynamical processes, machines and(high-tech) systems. Modelling tools are essential in analyzing and designing optimalcontrol strategies, e.g. by exploiting optimization theory. Mathematical System Theoryprovides insight in the formulation of mathematical models, in the derivation ofmathematical models from experimental data, and in the design of control andfeedback signals.

The orientation towards a variety of technological application domains is importantfor the interplay between theoretical possibilities on the one side, and the urge toadvance high-tech applications on the other side, thereby providing a fruitful stimulusfor further evolution and development of the scientific area.

The research program of DISC is divided in three main areas, each of which containsseveral themes.

• System and control theory• Theory and application of system modelling• Applications of control engineering

The three main areas in the research programme of DISC are further divided intoseveral themes. Within each theme research lines and topics are sketched togetherwith the acronyms of the DISC groups that participate.

1. System and control theory• System theory, nonlinear, distributed, hybrid and embedded systems.• Behavioral systems and control theory (RUG-JBI,UT-AM,TU/e-EE)• Infinite-dimensional systems (UT-AM,WU,TU/e-EE,RUG-JBI)• Hybrid systems (RUG-JBI,CWI,TU/e-ME,TUD-DCSC,UT-AM)• Embedded systems (TU/e-ME, RUG-JBI)• Nonlinear systems and control theory (RUG-ITM,TU/e-ME,TUD-DCSC,RUG-JBI)• Model reduction (RUG-JBI,MU,TU/e-EE)• Control theory for nonlinear, robust, adaptive and optimal control.• Optimization-based control and LMI’s (TUD-DCSC,TU/e-EE)• Distributed sensing and control (TUD-DCSC,TU/e-EE, TU/e-ME)• Adaptive control and learning (TUD-DCSC,TU/e-ME,TUD-AE)• Nonlinear control (TU/e-ME,RUG-JBI)

2. Theory and application of system modelling• System identification, estimation and signal processing; detection and diagnosis• System identification (TUD-DCSC,TU/e-EE,WU,CWI,MU)• Fault detection (TUD-DCSC,TUD-AE)• Parameter and state estimation (TUD-DCSC,WU,TUD-DIAM,TUD-AE)

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• Modelling tools: discrete events, hybrid systems, network theory, variational andgeometric methods, fuzzy logic/neural networks;

• Discrete event and hybrid systems (TU/e-ME,TUD-DCSC,TUD-DIAM,MU)• Fuzzy systems and neural networks (TUD-DCSC)• Physical modelling (RUG-JBI,TUD-DIAM,RUG-ITM)• Financial engineering (TU,UT-AM)

3. Applications of control engineering• Mechatronics, robotics, precision technology, motion control systems, biomedical,

aerospace and transportation systems• Mechatronics (TU/e-ME,TU/e-EE,TUD-DCSC,UT-EE,UT-ME,RUG-ITM)• Aerospace systems (TUD-AE, TUD-DCSC)• Transportation systems (TU/e-EE,TUD-DCSC,TU/e-EE)• Smart optics systems (TUD-DCSC,TU/e-ME)• Automotive systems (TU/e-ME,TUD-DCSC,TU/e-EE)• Robotics (UT-EE,TUD-DCSC,TU/e-ME)• Biomedical systems (TU/e-ME)• Precision tecnology (TU/e-ME,TU/e-EE)• Wind energy systems (TUD-DCSC)• Process control and optimization in (petro)-chemical and agricultural systems; analysis

and control of biological systems• Process control and optimization (TU/e-EE,TUD-DCSC,WU)• Experiment design and monitoring (TUD-DCSC,WU)• Biological systems (CWI,WU,TUD-DCSC,MU,RUG-JBI,RUG-ITM)• Agricultural systems (WU,UT-AM)• Nuclear fusion (TU/e-ME)

A detailed report on the progress of the several research projects within DISC canbe found in chapter 2.

1.4 Teaching program

DISC offers a graduate program in systems and control that leads to a doctor'sdegree of one of the participating universities. The requirements are:

• Completion of a course program of 27 EC credits.• Completion of a doctoral dissertation, to be approved by the adviser and awarded by

one of the participating universities in DISC.

During the academic years 2011-2012 and 2012-2013 a program consisting of eightcourses was offered, as listed in Tables 2 and 3. Classes meet every Monday duringfour or eight week terms in a central location in Utrecht. Full participation in an eightweeks course including successful completion of the tests is rewarded with 6 EC.Auditing the eight weeks course provides 1.5 EC.The four weeks specialized coursesare awarded with 3 EC (for only auditing 1 EC).

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Table 2. Courses 2011-2012

Course program 2011-2012

AfternoonMorningDataTerm

Mathematical Models ofSystemsJ.W. PoldermanH.L. Trentelman

Flexible Multibody SystemAnalysis for ControlPurposesJ.B. JonkerR.G.K.M. AartsJ. van Dijk

7/9Fall 2011

14/9

21/9

28/9

5/10

12/10

19/10

26/10

Control and SystemTheory of StochasticSystemsJ.H. van SchuppenR.L.M. Peeters

Nonlinear Control SystemsC. De PersisB. Jawardhana

16/11Winter 2011-2012

23/11

30/11

7/12

Model Predictive ControlA.J.J. van den BoomA.A. Stoorvogel

4/1

11/1

18/1

25/1

Model Reduction forControl Based onBalanced RealizationsJ.M.A. ScherpenK. Fujimoto

Design Methods for ControlSystemsM. SteinbuchS. Weiland

8/3Spring 2012

15/3

22/3

29/3

Distributed Control andOptimization inMulti-Agent SystemsT. KeviczkyM. Cao

12/4

19/4

26/4

3/5

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Table 3. Courses 2012-2013

Course program 2012-2013

AfternoonMorningDataTerm

Networked ControlSystemsW.P.M.H. HeemelsN. van de WouwM. Johansson

Mathematical Models ofSystemsJ.W. PoldermanH.L. Trentelman

3/9Fall 2012

10/9

17/9

24/9

Sensor Fusion forTracking ApplicationsF. GustafssonD. Roetenberg

1/10

8/10

15/10

22/10

Modeling and Control ofHybrid SystemsB. De SchutterW.P.M.H. Heemels

System Identification forControlP.M.J. Van den HofX.J.A. Bombois

12/11Winter 2012-2013

19/11

26/11

3/12

Contol Methods forRoboticsG.A.D. LopesR. Carloni

7/1

14/1

21/1

28/1

Nonlinear ControlSystemsC. De Persis

B. Jawardhana

Design Methods for ControlSystemsM. SteinbuchS. Weiland

4/3Spring 2013

11/3

18/3

25/3

8/4

15/4

22/4

6/5

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1.4.1 flexible multibody system analysis for control purposes (Fall 2011)

lecturersProf. dr. ir. J.B.Jonker, University of TwenteDr. ir. R.G.K.M. Aarts, University of TwenteDr. ir. J. van Dijk, University of Twente

objectiveFor control design of mechatronic systems it is essential to make use of prototypemodels with a few degrees of freedom that capture only the relevant system dynamics.For this purpose, the multibody system approach is a well-suited method to modelthe dynamical behaviour of the mechanical part of such systems. In this approachthe mechanical components are considered as rigid or flexible bodies that interactwith each other through a variety of connections such as hinges and flexible couplingelements like trusses and beams. The method is applicable for flexible multibodysystems as well as for flexible structures in which the system members experienceonly small displacement motions and elastic deformations with respect to anequilibrium position. A mathematical description of these models is represented bythe equations of motion derived from the multibody systems approach.

The exact constraint design of a (compliant) mechanism can be verified from akinematic analysis. Underconstraints and overconstraints are visualized askinematically indeterminate motions and statically indeterminate stress distributions.

For control synthesis a linearized state-space formulation is required in which anarbitrary combination of positions, velocities, accelerations and forces can be takenboth as input variables and as output variables, according to the control problembeing solved.

In this course basic concepts of flexible multibody system dynamics are presentedusing a non-linear finite element method. This formulation accounts for geometricnonlinear effects of flexible elements due to axial and transverse displacements.Theapproach offers many possibilities for analysis, simulation and prototype modelingof mechatronic systems. This will be illustrated through a variety of design cases.

contents• Scope of flexible multibody kinematics and dynamics. Multibody versus finite element

formulations. Description of angular orientation: Euler angles, Euler parameters.• Finite element representation of flexible multibody systems. Kinematical analysis: the

concept of constraints, degrees of freedom and geometric transfer functions, exactconstraint design. Dynamic analysis: lumped mass formulation, consistent massformulation, stiffness matrices, equations of motion, equations of reaction.

• Linearized equations for control system analysis. Stationary and equilibrium solutions.Linearized state-space equations.

• Illustrative design examples e.g. an active encoder head and a tilting mirror mechanism.

lecture notesLecture notes will be distributed during the course.

prerequisitesBasic background in systems modeling and control theory.

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homework assignmentsThree homework assignments will be handed out. The assignments will be gradedand the average grade will be the final grade for this course.

participantsRegistered participants: 7

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1.4.2 mathematical models of systems (Fall 2011 and Fall 2012)

lecturersDr. J.W. Polderman, University of Twente (Fall 2011 and Fall 2012)Prof. dr. H.L. Trentelman, University of Groningen (Fall 2011)Dr. J.W . van der Woude, Delft University of Technology (Fall 2012)

objectiveThe purpose of this course is to discuss the ideas and principles behind modelingusing the behavioral approach, and to apply these ideas to control system design.In the behavioral approach, dynamical models are specified in a different way thanis customary in transfer function or state space models. The main difference is thatit does not start with an input/output representation. Instead, models are simplyviewed as relations among variables. The collection of all time trajectories which thedynamical model allows is called the behavior of the system. Specification of thebehavior is the outcome of a modelling process.

Models obtained from first principles are usually set-up by tearing and zooming.Thusthe model consist of the laws of the subsystems on the one hand, and theinterconnection laws on the other. In such a situation it is natural to distinguishbetween two types of variables: the manifest variables which are the variables whichthe model aims at and the latent variables which are auxiliary variables introducedin the modelling process. Behavioral models easily accommodate static relations inaddition to the dynamic ones. A number of system representation questions occurin this framework, among others:

• the elimination of latent variables• input/output structures• state space representations

We also introduce some important system properties as controllability andobservability in this setting. In the first part of the course, we review the mainrepresentations, their interrelations, and their basic properties.

In the context of control, we view interconnection as the basic principle of design. Inthe to–be–controlled plant there are certain control terminals and the controllerimposes additional laws on these terminal variables.Thus the controlled system hasto obey the laws of both the plant and the controller. Control design procedures thusconsist of algorithms which associate with a specification of the plant (for example,a kernel, an image, or a hybrid representation involving latent variables) a specificationof the controller, thus passing directly from the plant model to the controller. Weextensively discuss the notion of implementability as a concept to characterize thelimits of performance of a plant to be controlled. We discuss how the problems ofpole-placement and stabilization look like in this setting.

contents• General ideas. Mathematical models of systems. Dynamical systems. Examples from

physics and economics. Linear time-invariant systems. Differential equations.Polynomial matrices.

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• Minimal and full row rank representation. Autonomous systems. Inputs and outputs.Equivalence of representations.

• Differential systems with latent variables. State space models. I/S/O models.• Controllability. Controllable part. Observability.• Elimination of latent variables. Elimination of state variables.• From I/O to I/S/O models. Image representations.• Interconnection. Control in a behavioral setting. Implementability.• Stability. Stabilization and pole placement.

prerequisitesThe course is pretty much self-contained. Basic linear algebra and calculus shouldsuffice.

course materialThe main reference is Introduction to Mathematical Systems Theory: A BehavioralApproach by J.W. Polderman and J.C. Willems (Springer 1998). The last lecture isbased on a paper by M.N. Belur and H.L. Trentelman

examinationFour sets of homework exercises will be handed out during the course. The averagegrade of these four assignments determines the final grade. There is no final exam.

participantsRegistered participants 2011-2012: 18Registered participants 2012-2013: 18

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1.4.3 nonlinear control systems (Winter 2011-2012)

lecturersProf.dr. C. De Persis, University of GroningenDr. B. Jayawardhana, University of Groningen

objectivesTo provide a set of self-contained results and proofs on the existence of specialnormal forms of nonlinear systems and their use in the design of state- andoutput-feedback controllers for nonlinear systems. Fundamental notions such asrelative degree, zero dynamics, semi-global stabilizability, observability canonicalform, high-gain observers, nonlinear separation principle will be dealt with in theselectures. The analogue of these notions for linear systems will be emphasized.

contentsLecture 1 (Relative degree and normal forms) Relative degree. Normal forms forsingle-input single-output systems. Zero or inverse dynamics. Global normal forms.Relative degree and zero dynamics for linear systems.

ReferencesA. Isidori. Nonlinear Control Systems. Vol. I, Third Edition, Springer Verlag,

1999. Sections 4.1, 4.3.

H. Nijmeijer, A.J. van der Schaft, Nonlinear Dynamical Control Systems, Springer,New York, 1990, 4th reprint 1998. Sections 8.1, 8.2.

Lecture 2 (Semi-global stabilization) Minimum-phase systems. Semi-globalasymptotic stabilization by full-state feedback. Semi-global practical stabilization bypartial-state feedback.

ReferencesA. Isidori. Nonlinear Control Systems. Vol. I, Third Edition, Springer Verlag,

1999. Section 9.3. A. Isidori. Nonlinear Control Systems. Vol. II, Springer Verlag,1999. Section

11.1.

Lecture 3 (High-gain nonlinear observers) The observability canonical form. High-gainnonlinear observers.

ReferencesJ.P. Gauthier and I. Kupka. Deterministic observation theory. Cambridge UniversityPress, 2004. Selected sections and handouts.

Lecture 4 (Output feedback stabilization) High-gain observer-based nonlinearstabilization. A nonlinear separation principle.

ReferencesJ.P. Gauthier and I. Kupka. Deterministic observation theory. Cambridge UniversityPress, 2004. Selected sections from Chapter 7 and handouts.

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prerequisitesThe students willing to attend the course will be requested to read a few selectedparts from H. Khalil, Nonlinear Systems, 3rd edition, Prentice Hall, 2002. Thisassignment is aimed at emphasizing the peculiarity of some nonlinear phenomenaand making the students more familiar with basic notions such as equilibria, existenceand uniqueness of solutions and

Lyapunov stability theory.

The students are expected to be familiar with ordinary differential equations, linearsystems and control theory and linear algebra.

lecture notesThe lecture notes will be distributed during the course.

homework assignmentsThe students will be given two take-home exams consisting of a number of problems.


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1.4.4 control and system theory of stochastic systems (Winter 2011-2012)

lecturersProf.dr.ir. R.L.M. Peeters, University of MaastrichtProf.dr.ir. J.H. van Schuppen, Delft University of Technology / CWI

objectiveThe purpose of the course is to present the concept of a stochastic system as aprobabilistic model for signals with uncertainty and to present synthesis methods forcontrol

and filtering of stochastic systems.

The course is directed jointly to engineers and to mathematicians. Because of theintended audience, the mathematical content of the course is not that deep (measuretheory is used but lightly). Only discrete-time stochastic systems will be treated.Although several classes of stochastic systems will be discussed most attention willbe given to the class of Gaussian systems.

contents1. Probability and stochastic processes. Introduction to the course. Probabilitydistribution functions, probability densities. Gaussian random variables. Expectation.Inde-

pendence and conditioning. Stochastic processes, Gaussian processes.

2. Stochastic systems. Stochastic system, Gaussian system, finite stochastic system.

Properties of Gaussian systems. Examples from control, communication, mechanicalengineering, and other areas of engineering.

3. Stochastic realization. Stochastic realization of stationary Gaussian processes.Existence and classification of minimal realizations. Special stochastic realizations.Sub-space version of stochastic realization algorithm.

4. Stochastic control problems. Examples. Stochastic control system and stochasticcontrollability. Control objectives. Control synthesis methods and design.

5. Stochastic control with complete observations - Finite horizon. Example. Dynamicprogramming. Gaussian systems and quadratic criteria (LQG and LEQG). Examples.

6. Stochastic control with complete observations – Finite horizon. Discounted costand average cost. Dynamic programming for discounted cost. Examples. Dynamicprogramming for average cost. Examples.

7. Kalman filters. Filtering problem for Gaussian processes. Kalman filter. Examples.Asymptotic Kalman filter. Design of Kalman filters. Prediction and smoothing ofGaussian systems. Filter theory and filter techniques, extended Kalman filter.

8. Stochastic control with partial observations. Example. Filtering in the presence ofan input process. Dynamic programming in case of partial observations. Gaussian

systems with quadratic criteria (LQG and LEQG). Separation property and principle.Asymptotic controller. Perspective on control and system theory of stochastic systems.

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prerequisitesThe participants are assumed to have knowledge as provided by a basic

undergraduate course in control of linear systems; and by an undergraduate coursein probability and elementary stochastic processes. The minimum level is indicatedby the books:

(1) for probability theory the book Sheldon Ross, A first course in probability, (5thEd.),

Prentice-Hall, Upper Saddle River, 1998; and (2) for control and system theory thebook G.J. Olsder, J.W. van der Woude, Mathematical systems theory, Delft UniversityPress, Delft, 2005.

A recommended prerequisite is knowledge of elementary measure theory andmeasure theoretic probability as provided by the book J. Jacod and Ph. Protter,Probability essentials, Springer, Berlin, 1999 of which there exists also a more recentedition. Students will benefit from having studied this book prior to the start of thecourse but this is not a requirement. Measure theory at this level is usually providedby a course of a mathematics department of a university.

lecture notesWill be distributed during the course.

homework assignmentsHomeworksets and a takehome exam.


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1.4.5 model predictive control (Winter 2011-2012)

lecturersDr.ir. A.J.J. van den Boom, Delft University of TechnologyProf.dr. A.A. Stoorvogel, University of Twente

objectiveThe model predictive control (MPC) strategy yields the optimization of a performanceindex with respect to some future control sequence, using predictions of the outputsignal based on a process model, coping with amplitude constraints on inputs, outputsand states.The course presents an overview of the most important predictive controlstrategies, the theoretical aspects as well as the practical implications, which makesmodel predictive control so successful in many areas of industry, such aspetro-chemical industry and chemical process industry. Hands-on experience isobtained by MATLAB exercises.

Aims of the course:• Introduction to the basic concepts of model predictive control.• Theoretical foundation as well as the practical issues in MPC.• Overview of current research and future directions for MPC.

contents• General introduction. Different type of models and model-structures, advantages and

limitations. Signal constraints in control.• Standard predictive control scheme. Relation standard form with GPC, LQPC and

other predictive control schemes. Finite/infinite horizon MPC. Solution of the standardpredictive control problem.

• Stability and the role of endpoint penalties. The effects of model uncertainty androbustness analysis.

• The effects of noise on prediction and constraints.• Limitations in MPC: complexity, feasibility, computational requirements, real-time

implementation.

lecture notesThe lecture notes of the course will be made available electronically.

prerequisitesCalculus and linear algebra. Basics of linear system and control (Sections §1.13,§1.15, §1.16, §3.2.C, §3.3.C, §6.10 and appendix A.3 from the book Linear systemsby P.J. Antsaklis and A.N. Michel, McGraw-Hill 1998).

homework assignmentsTwo homework assignments will be handed out. The assignments will be graded,and the average will be your final grade for this course.


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1.4.6 design methods for control systems (Spring 2012 and Spring 2013)

lecturersProf.dr.ir. M. Steinbuch, Eindhoven University of TechnologyDr. S. Weiland, Eindhoven University of Technology

objectiveThe course presents "classical," "modern" and "post-modern" notions about linearcontrol system design. First the basic principles, potentials, advantages, pitfalls andlimitations of feedback control are presented. An effort is made to explain thefundamental design aspects of stability, performance and robustness.

Next, various well-known classical single-loop control system design methods,including Quantitative Feedback Theory, are reviewed and their strengths andweaknesses are analysed.

The course includes a survey of design aspects that are characteristic for multivariablesystems, such as interaction, decoupling and input-output pairing. Further LQ, LQGand some of their extensions are reviewed. Their potential for single- and multi-loopdesign is examined.

After a thorough presentation of the generalized plant framework and the notions ofstructured and unstructured uncertainties, design methods based onH-infinity-optimization and mu-synthesis are presented.

contents• Introduction to feedback theory. Basic feedback theory, closed-loop stability, stability

robustness, loop shaping, limits of performance.• Classical control system design. Design goals and classical performance criteria,

integral control, frequency response analysis, compensator design, classical methodsfor compensator design. Quantitative Feedback Theory.

• Multivariable Control Multivariable poles and zeros, interaction, interaction measures,decoupling, input-output pairing, servo compensators.

• LQ, LQG and Control System DesignLQ basic theory, some extensions of LQ theory,design by LQ theory, LQG basic theory, asymptotic analysis, design by LQG theory,optimization, examples and applications

• The generalized plant framework, parametric and dynamic uncertainty models, thesmall-gain theorem, stability robustness of feedback systems, structured singularvalue robustness analysis, combined stability and performance robustness.

• H-infinity optimization and mu-synthesis, the mixed sensitivity problem, loop shaping;the standard H-infinity control problem, state space solution, optimal and suboptimalsolutions, integral control and HF roll-off, mu-synthesis, application of mu-synthesis.

• Appendix on Matrices• Appendix on norms of signals and systems


prerequisitesBasic undergraduate courses in systems and control. Some familiarity with MATLABis helpful for doing the homework exercises.

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homework assignmentsFour homework sets will be distributed via the course website.

Homework is graded on a scale from 1 to 10. Missing sets receive grade 0. The finalgrade for the course is the average of the grades for the four homework sets.

participantsRegistered participants 2011-2012: 38Registered participants 2012-2013: 30

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1.4.7 model reduction for control based on balanced realizations (Spring 2012)

lecturersProf.dr. K. Fujimoto, Nagoya University, JapanProf.dr.ir. J.M.A. Scherpen, University of Groningen

objectiveThe purpose of this course is to provide a basis for model order reduction based onbalanced realizations and to give an overview of the state of the art research.

The need for innovation results in a dominating trend towards analyzing and designingsystems of increasing complexity. Such analysis and design cycles rely on themathematical models of the systems.These models are thus increasing in complexityas well, both in nature (from linear to nonlinear, and from lumped- todistributed-parameter), and size. Complex models are more difficult to analyze andsimulate. Due to this it is also difficult to develop and implement control algorithms;moreover high-order controllers are usually not wanted. This course will focus onlinear and nonlinear systems, and will provide a basis for studying and usage ofbalancing based model order reduction methods.

contents1. Brief overview of recent model order reduction techniques, both linear andnonlinear.2. Balancing for linear systems is treated from a state-space point of view, and arelation with minimality and the frequency domain is given. The relation with theHankel operator, and error bounds and their derivation are treated. Other types ofbalancing, closed-loop balancing, and balancing based on dissipativity, and passivitywill be treated in a unified setting, made possible by recent results.3. Frequency weighting, and controller reduction methods, a.o. based on new resultsof Fujimoto, will be treated.4. Extensions to nonlinear systems for balancing and the corresponding Hankeloperator will be treated.5. Along with the couse, applications for linear systems, and motivational examplesfor nonlinear systems will be considered.


prerequisitesBasic background in systems and control theory.

homework assignmentsTwo to four homework sets will be handed out. The average grade will be the finalgrade for this course.


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1.4.8 distributed control and optimization in multi-agent systems (Spring 2012)

lecturersDr.ir. T. Keviczky, Delft University of TechnologyDr. M. Cao, University of Groningen

objectiveThe purpose of this course is to overview distributed consensus and optimizationalgorithms and their applications in multi-vehicle cooperative control. Theoreticalresults on distributed consensus algorithms for multi-agent systems are firstintroduced. This is followed by an overview of distributed optimization techniquesand corresponding decomposition methods along with optimization-based controldesign approaches such as distributed MPC. Application examples are theninvestigated where the distributed algorithms are used for coordinating vehicleformations (composed of wheeled and airborne mobile robots or deep-spacespacecraft), and performing tasks such as rendezvous and formation keeping.

contents1. Overview of recent research on distributed multi-vehicle cooperative control.2. Consensus algorithms for single- and double-integrator dynamics. Specifically,we introduce basic consensus algorithms for single-integrator dynamics, consensustracking of a dynamic leader, consensus algorithms for double-integrator dynamics,consensus under realistic constraints, and swarm tracking algorithms.3. Distributed optimization methods and various decomposition techniques (primal,dual, augmented Lagrangian / proximal point method), links to consensus algorithms,and their application in networked multi-vehicle distributed robotics problems.4. Online optimization-based control approaches such as distributed model predictivecontrol for multi-vehicle cooperation, distributed LQR and decomposition basedmethods that are applicable to collections of identical mobile agents. The presentedtopics are illustrated on cooperative rendezvous, distributed formation control,spacecraft formation flight, and other application examples in robotic networks.


prerequisitesBasic background in systems and control theory.

homework assignmentsFour homework sets will be distributed by the course website. Homework is gradedon a scale from 1 to 10. Missing sets receive the grade 1. The final grade forthe course is the average of the grades for the four homework sets.


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1.4.9 networked control systems (Fall 2012)

lecturersProf.dr.ir. W.P.M.H. Heemels, Eindhoven University of TechnologyDr.ir. N. van de Wouw, Eindhoven University of TechnologyProf.dr. M. Johansson, KTH, Stockholm, Sweden

objectivesThe rapid advances in communication technologies offer unprecedented opportunitiesfor the control of complex high-tech systems and large-scale plants. The usage ofwired and especially wireless communication networks in control systems offer manybenefits such as the ease of maintenance and installation, the large flexibility, theability to distribute the control system and the possibility to measure in possibly harshenvironments. However, still many issues need to be resolved before all theadvantages of these so-called ̀ `networked control systems (NCSs)'' can be harvested.In particular, the control over a network induces various communication imperfections,such as (i) Quantization errors; (ii) Packet dropouts caused by the unreliability of thenetwork; (iii) Variable sampling/transmission intervals; (iv) Variable communicationdelays/latencies; and (v) Communication constraints caused by the sharing of thenetwork by multiple nodes and the fact that only one node is allowed to transmit itspacket per transmission. Next to improvements in the communication infrastructureitself, there is a need for control algorithms that can deal with these network-inducedimperfections and constraints. This course will offer a brief overview of the field ofNCSs and a particular focus will be on various modeling, analysis, and designmethods for NCSs.

contents1. General introduction to NCSs. Motivating applications are provided that lead tothe identification of the fundamental problems that will be tackled in the course.Models of communication channels and networks are provided that can be integratedin the models of the control loop.

2. Simplest communication models based on hard bounds on delays, samplingintervals and maximum number of subsequent dropouts are exploited leading to amodel structure in terms of discrete-time parameter-dependent systems Methodsfor stability analysis and (robust) controller design methods will be discussed in detail.

3. NCS with communication constraints are analyzed. Communication constraintsrestrict the information that is being sent at each transmission time and requires thescheduling of which information is sent when. Two distinct modelling approaches(based on discrete-time parameter-dependent systems and continuous-time hybridsystems) will be treated for these NCSs. Moreover, analysis tools are provided forsuch NCS models.

4. Analysis and design techniques are discussed for NCS models based onprobabilistic information of the communication channel. Advanced controller designand corresponding numerical tools are presented.

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prerequisitesBasic undergraduate courses in systems and control. Basic programming skills(Matlab). Basic knowledge about stability of switched and hybrid system isadvantageous.

lecture notesW.P.M.H. Heemels, N. van de Wouw and M. Johansson, "Modeling, Analysis andDesign of Networked Control Systems", Handouts for the DISC Course. Thesehandouts will be made available electronically together with all the slides.

homework assignmentsHomework assignments will be handed out.The assignments will be graded and theaverage grade will be the final grade for this course.


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1.4.10 sensor fusion for tracking applications (Fall 2012)

lecturersProf.dr. F. Gustafsson, Linköping University Sweden, University of TwenteDr.ir. D. Roetenberg, Xsens Technologies, University of Twente

objectiveSensor fusion deals with merging information from two or more sensors, where thearea of statistical signal processing provides a powerful toolbox to attack boththeoretical and practical problems.

The objective of this course is to explain and get hands-on experience with state ofthe art theory and algorithms in statistical sensor fusion, covering estimation, detectionand nonlinear filtering theory with applications to localization, navigation and trackingproblems.

The course covers the theory on linear and nonlinear estimation, with a focus onsensor network applications. The book spans the whole range from mathematicalfoundations provided in extensive appendices, to real-world problems covered in apart surveying standard sensors, motion models and applications in this field. Allmodels and algorithms are available as object-oriented Matlab code with an extensivedata file library, and the examples, which are richly used to illustrate the theory, aresupplemented by fully reproducible Matlab code.

The lectures focus on the part of the book describing nonlinear filter theory, with aparticular attention to different variants of the Kalman filter (extended, unscented,sigma point) and the particle filter. Complexity and implementation issues arediscussed in detail. Simultaneous localization and mapping (SLAM) is used as achallenging application area of high-dimensional nonlinear filtering problems.

contentsThe general problem is to estimate a state or parameter from a multitude of sensorobservations distributed over time, space and modality (=type of sensor).The courseis structured as follows.

The static case:General fusion theory.

• Estimation theory in the linear case. Extensions to the non-linear case.• Bayesian fusion perspective, the sensor fusion formula.• Computational estimation issues: Centralized versus decentralized fusion (information

propagation and double-counting, covariance intersection techniques). Batchcomputations versus sensor iterations.

• Diagnosis: The vector model. Error approximations.

The dynamic case:Filter theory.

• General non-linear filter theory.• Kalman filtering: Basic theory, implementation aspects, practical issues, information

filter, smoothing). Approximative algorithms for non-linear models (Extended KF andHMM, UKF and sigma-point filters, KF banks).

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• The particle filter: theory, implementation, proposal methods, sampling principles,smoothing, practical aspects.

Dynamic state dimension problems.• Simultaneous localization and tracking (SLAM).

Practice:Sensors, sensor models and sensor-near signal processing.

• IMU and dead-reckoning.• GPS.• Magnetic field sensors.

Motion models• Multi-purpose motion models.

Human motion capture• Single to multi body segment tracking.

course materialThe main reference is 'Statistical Sensor Fusion' by F. Gustafsson,ISBN978-91-44-05489-6

Other lecture notes will be distributed during the course.

required backgroundPrerequisites:

• Signal and systems, in particular state space models.• Linear algebra including least squares theory.• Probability theory and statistics.• Matlab programming.

Useful background knowledge:• Parameter estimation/system identification• Kalman filtering• Mechanical models

homework assignmentsThe projects are individual and involve navigation and tracking based on inertialsensors. The experiments will be performed on site at Xsens where ground truthreference systems are available. The participants are also encouraged to do theirown experiments with smartphones, where accelerometers, gyroscopes,magnetometer and GPS data are logged and processed off-line in the Matlab toolbox.The Matlab toolbox contains tailored tools for processing these data. Applicationsinclude tracking the roll angle when you bike, the angular rates of your foot whenyou run, or the velocity and angles of your golf club when you swing.The participantsare encouraged to use their imagination to come up with new applications in trackingand perhaps new business opportunities!


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1.4.11 system identification for control (Winter 2012-2013)

lecturersDr.ir. X.J.A. Bombois, Delft University of TechnologyProf.dr.ir. P.M.J. Van den Hof, Eindhoven University of Technology

objectivesSystem Identification concerns the modeling of dynamical systems on the basis ofobserved data. The objective of this course is to present the important systemidentification techniques with a special attention to prediction error methods. Subspaceand frequency-domain methods will be covered as well. We will consider both thecases of data collected in open loop and data collected in closed loop. Finally, theproblem of the optimal design of the identification experiment will be addressed.

contents1. Introduction; concepts; discrete- time signal and system analysis

2. Parametric (prediction error) identification methods – model sets, identificationcriterion, statistical properties

3. Parametric (prediction error) identification methods – model validation, experimentdesign and approximate modelling

4. ETFE and frequency-domain identification

5. Extension on model structures and identification methods

6. Closed-loop identification

7. Subspace identification

8. Optimal identification experiment design

prerequisitesCalculus and linear algebra. Some knowledge of statistics and linear systems theoryand/or time series analysis is helpful, but not required. The lecture notes containuseful summaries of the important notions used during the course.

lecture notesLecture notes will be distributed during the course.

course assessmentThe assessment of this course will be in the form of three homework assignments.


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1.4.12 modeling and control of hybrid systems (Winter 2012-2013)

lecturersProf.dr.ir. B. De Schutter, Delft University of TechnologyProf.dr.ir. W.P.M.H. Heemels, Eindhoven University of Technology

objectiveRecent technological innovations have caused a considerable interest in the studyof dynamical processes of a mixed continuous and discrete nature. Such processesare called hybrid systems and are characterized by the interaction of time-continuousmodels (governed by differential or difference equations) on the one hand, and logicrules and discrete-event systems (described by, e.g., automata, finite state machines,etc.) on the other. A hybrid system also arises in practice when continuous physicalprocesses are controlled via embedded software that intrinsically has a finite numberof states only (e.g., on/off control).

This course will offer a brief overview of the field of hybrid systems ranging frommodeling, over analysis and simulation, to verification and control.We will particularlyfocus on modeling, analysis, and control of tractable classes of hybrid systems.

contents1. General introduction. Examples of hybrid systems & motivation.Modeling frameworks (automata, hybrid automata, piecewise-affine systems,complementarity systems, mixed logic dynamical systems, ...)

2. Properties and analysis of hybrid systems (well-posedness, Zeno behavior, stability,liveness, safety, ....).

3. Control of hybrid systems (switching controllers, model predictive control, ...)

4. Control of hybrid systems (continued). Verification. Tools.

lecture notesB. De Schutter and W.P.M.H. Heemels, "Modeling and Control of Hybrid Systems",Lecture Notes for the DISC Course. Revised edition. Sept. 2012.These lecture noteswill be made available electronically.

prerequisitesBasic undergraduate courses in systems and control.

Basic programming skills (Matlab).

homework assignmentsFour homework assignments will be handed out. The assignments will be gradedand the average grade will be the final grade for this course.

course websitehttp://www.dcsc.tudelft.nl/~disc_hs/course/


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1.4.13 control methods for robotics (Winter 2012-2013)

lecturersDr. G.A.D. Lopes, Delft University of TechnologyDr.ir. R.Carloni, University of Twente

objectiveThis course presents a number of motion control methodologies applied to roboticmanipulators, legged and wheeled robots.

After successfully completing this course the student should be able to:• Define notions of configuration and work spaces of a robot• Identify different classes of robotic systems and associated mathematical models• Implement motion controllers• Compare/differentiate control methodologies• Discuss simulation results

contentsLecture 1 Mathematical preliminaries

• Group theory• Lagrangian mechanics• Hamiltonian mechanics• Port Hamilton systems and Mechanical equations

Lecture 2 Fully actuated systems• Computed torque control and Workspace control• Gradient dynamics and tracking reference dynamics• Impedance/admittance control

Lecture 3 Hybrid controllers• ZMP walking via operational space control• SLIP walking

Lecture 4 Nonholonomic control• Introduction to nonholonomic systems• Transverse function approach

lecture notesThe lecture notes of the course will be made available electronically.

prerequisitesThis course is self-contained. Students should be comfortable with linear algebra

and differential equations.

course material1. Spong, Hutchinson, Vidyasagar, Robot Modeling and Control;

2. Murray, Lee, Sastry, A Mathematical Introduction to Robotic Manipulation;

3. Khalil, Nonlinear Systems

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homework assignmentsThe assessment for this course consists of 4 homework problems to be implementedin the software Mathematica. The models of the robotic platforms and visualizationenvironments are provided.The task of the student is to apply the knowledge gainedin class to synthesize controllers and analyze their performance in simulation.


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1.4.14 nonlinear control systems (Spring 2013)

lecturersProf.dr. C. De Persis, University of GroningenDr. B. Jayawardhana, University of Groningen

objectivesTo provide a set of self-contained results and proofs on the analysis and controldesign of nonlinear systems. Fundamental notions such as relative degree, zerodynamics, semi-global stabilizability, L2 stability, (integral)-input-to-state stability andsmall-gain principle will be dealt with in these lectures. Relevant applications of theseconcepts to the passivity-based control, event-based control and networked controlsystems will be discussed in detail.

contentsLecture 1 (Relative degree and normal forms) Relative degree. Normal forms forsingle-input single-output systems. Zero or inverse dynamics. Global normal forms.

ReferencesA. Isidori. Nonlinear Control Systems. Vol. I, Third Edition, Springer Verlag, 1999.Sections 4.1, 4.3.

H. Nijmeijer, A.J. van der Schaft, Nonlinear Dynamical Control Systems, Springer,New York, 1990, 4th reprint 1998. Sections 8.1, 8.2.

Lecture 2 (Semi-global stabilization) Minimum-phase systems. Semi-globalasymptotic stabilization by full-state feedback. Semi-global practical stabilization bypartial-state feedback.

ReferencesA. Isidori. Nonlinear Control Systems. Vol. I, Third Edition, Springer Verlag, 1999.Section 9.3.

A. Isidori. Nonlinear Control Systems. Vol. II, Springer Verlag, 1999. Section 11.1.

Lecture 3 (L2 stability) Dissipative systems, L2-stable systems, La-Salle invarianceprinciple

ReferencesA.J. van der Schaft, L2-gain and Passivity Techniques in Nonlinear Control, Springer,Berlin, 2000.

R. Ortega, A. Loria, P.J. Nicklasson, H. Sira-Ramirez, Passivity-Based Control ofEuler-Lagrange Systems, Springer-Verlag, London, 1998.

Lecture 4 (Passivity-based control) Interconnection and Damping AssignmentPassivity-based Control, Energy-Balance Passivity-based Control, PI stabilization

ReferencesR. Ortega, A. Loria, P.J. Nicklasson, H. Sira-Ramirez, Passivity-Based Control ofEuler-Lagrange Systems, Springer-Verlag, London, 1998.

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Lecture 5 (ISS & iISS) Characterization of Input-to-State Stability (ISS) and integralInput-to-State Stability (iISS), Input-Output-to-State Stability (IOSS). The relation tothe L2-stable systems is also given.

ReferencesE.D. Sontag, “Input to state stability: basic concepts and results,” P. Nistri & G. Stefani(eds.), Nonlinear and Optimal Control Theory, pp. 163-220, Springer-Verlag, Berlin,2006.

D. Angeli, E.D. Sontag, Y.Wang, “A characterization of integral input to state stability,”IEEE Trans. Automatic Control, vol. 45, pp. 1082-1097, 2000.

Lecture 6 (Event-based control systems) Application of the ISS concept to the varioustopics on event-based control designs, including event-triggered control systemsand self-triggered control systems.

ReferencesP. Tabuada, “Event-triggered real-time scheduling of stabilizing control tasks,” IEEETrans. Automatic Control, vol. 52, no. 9, pp. 1680-1685, 2007.

Lecture 7 (Small-gain principle) Small-gain principle and its application to the analysisof large-scale or distributed systems.

ReferencesZ.-P. Jiang, A.R. Teel, L. Praly, “Small-gain theorem for ISS systems andapplications,” Mathematics of Control, Signals, and Systems, vol. 7, pp. 95-120,1994.

Z. –P. Jiang, I. M.Y. Mareels, and Y. Wang. 1996. "A Lyapunov Formulation of theNonlinear Small-Gain Theorem for Interconnected ISS Systems." Automatica 32 (8):1211-1215.

S. N. Dashkovskiy, B. S. Rüffer, and F. R. Wirth. 2009. "Small Gain Theorems forLarge Scale Systems and Construction of ISS Lyapunov Functions." SIAM Journalon Control and Optimization 48 (6): 4089-4118.

Lecture 8 (Networked Control Systems) Application of the passivity-based controlto the various topics on networked control systems, including synchronization.

ReferencesG-B Stan, R. Sepulchre, “Analysis of Interconnected Oscillators by DissipativityTheory,” IEEE Trans. Automatic Control, vol. 52, no. 2, pp. 256-272, 2007.

L. Scardovi, M. Arcak, and E. D. Sontag. 2010. "Synchronization of InterconnectedSystems with Applications to Biochemical Networks: An Input-Output Approach."IEEE Transactions on Automatic Control 55 (6): 1367-1379.

A. Hamadeh, G.-B. Stan, R. Sepulchre, and J. Gonçalves. 2012. "Global StateSynchronization in Networks of Cyclic Feedback Systems." IEEE Transactions onAutomatic Control 57 (2): 478-483.

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prerequisitesThe students willing to attend the course will be requested to read a few selectedparts from H. Khalil, Nonlinear Systems, 3rd edition, Prentice Hall, 2002. Thisassignment is aimed at emphasizing the peculiarity of some nonlinear phenomenaand making the students more familiar with basic notions such as equilibria, existenceand uniqueness of solutions and Lyapunov stability theory.The students are expectedto be familiar with ordinary differential equations, linear systems and control theoryand linear algebra.


homework assignmentsThe students will be given two take-home exams consisting of a number of problems.


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1.5 Summer School

From June 11-14, 2012 DISC organized an International Summer School onOptimization in Control Theory in Noordwijk, The Netherlands.

About 38 participants attended, mostly PhD students.

The invitation for attending the school was addressed to research students and staffmembers of the Dutch Institute of Systems and Control (DISC) and to otherresearchers and engineers engaged in the systems and control and adjacent fields.

The main goal of the DISC summer schools is to familiarize young researchers withrecent developments in systems and control as well as in neighboring disciplines,and to provide them with the opportunity to enjoy, in an informal atmosphere,discussions with top researchers in systems and control. The summer schools alsoprovide an opportunity for DISC staff members and others to upgrade their knowledgein specific areas of interest.

Optimization has always been a core ingredient in the synthesis of control systemsand in solving design questions related to applications in various engineeringdisciplines. Many challenges in control and engineering translate to fundamentalquestions in optimization and their solutions depend on the availability of reliabletechniques in optimization. This summer school focuses on topics that are relevantto optimization in control theory:

• Convex optimization• Dynamic programming• Optimization for infinite and high dimensional systems• Non-convex and non-smooth optimization

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Participants and lecturers of the DISC Summer School on Optimization in ControlTheory, Noordwijk, June 2012

The abstracts of the lectures:

Anders Helmersson, Linkoping University, SwedenLecture 1 - Tools for LMI-Based Synthesis and AnalysisLecture 2 - Solvers for LMI-Based Synthesis and AnalysisLecture 3 - LMI-Based Synthesis and Analysis ILecture 4 - LMI-Based Synthesis and Analysis II

Orest Iftime, University of Groningen, The NetherlandsLecture 1 - Approximation of Infinite-Dimensional Systems and Optimal Control

Abstract: In this lecture, a theory for robust finite-dimensional controllers for a classof infinite-dimensional systems is presented. First we define the appropriate stabilityconcept for transfer matrices. Then we consider the robust stabilization problemunder additive perturbation. Examples of infinite-dimensional robust control designare also presented. We conclude with a short exposition on approximation ofinfinite-dimensional systems using moment matching techniques and its possibleadvantages.

• block circulant and block toeplitz approximants• moment matching with preservation of properties

Finite-Dimensional Controller Synthesis for Infinite-Dimensional Systems. As contentI propose: -an overview of the "standard" Chapter 9 from Curtain and Zwart book(with examples and a short exposition on Hankel norm approximation) -the last 10-12minutes a short view of moment matching with preservation of properties and as anextension on current research.

Anders Rantzer, Lund University, SwedenLecture 1 - Optimal Control and Dynamic ProgrammingAbstract: General problem formulations of optimal control. Dynamic Programming.Value iteration. Policy iteration. Bellman's equation. Approximate dynamicprogramming. Examples.

Lecture 2 - Model Predictive Control (MPC)Abstract: The main idea of receding horizon control. Brief literature review. Issuesof feasibility, stability, performance. Guarantees from terminal constraints. Introductionto exercise session.

Lecture 3 - Performance of MPC ControllersAbstract: More on terminal constraints. Terminal penalty. Performance analysiswithout terminal constraints/penalty. Intro to receding horizon estimation (timepermitting).

Lecture 4 - Distributed Model Predictive ControlAbstract: Intro to distributed optimization. Dual decomposition in convex optimization.Dual decomposition in MPC. Gradient updates of prices. Examples.

Miroslav Krstic, University of California, USALecture 1&2 - Extremum Seeking I

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Lecture 3&4 - Extremum Seeking II

Abstract: Extremum seeking (ES) is an approach for model-free real-time optimizationfor plants with dynamics and where the plant model and the analytical form of theperformance index are unknown. ES does not attempt to fully learn the analyticalform of the performance index but instead simply tunes the input to the system toforce the gradient of the performance index with respect to the input to go to zero.ES performs the tuning with the help of perturbation signals, which can be eitherdeterministic (sinusoids) or stochastic (white noise). I will review the history of ESand the basic deterministic algorithms and then dedicate the rest of the time to themore recent stochastic algorithms. Convergence of the algorithms is studied withthe help of averaging theorems for deterministic and stochastic ODEs. Topics to becovered include single-input and multivariable optimization using ES, applicationsto nonholonomic vehicle guidance source seeking without position measurement,extension from gradient to Newton methods for ES, and applications tonon-cooperative games.

Wil Schilders, Eindhoven University of Technology, The NetherlandsLecture 1 – Optimization via Model-Approximation

Tamas Keviczky, Delft University of Technology, The NetherlandsLecture 1 - Distributed Optimization-Based Control and Estimation

Abstract: Optimization techniques have played a fundamental role in designingcontrol systems for the most part of the past half century. This dependence is evermore obvious in today's wide-spread use of online optimization-based control methods(e.g., receding horizon control, moving horizon estimation). These methods arebecoming increasingly applicable to processes with fast dynamics as well. In thispresentation, some fundamental methods and aspects of optimization decompositionwill be reviewed. In addition, various recent approaches and examples of usingdistributed optimization techniques for the coordination of multi-agent systems willbe discussed along with open issues for future research.

Thijs van Keulen, DAF Trucks N.V., The NetherlandsLecture 1 - Numerical Solution for State Constrained Optimal Control Problems

Abstract: In this presentation we present a numerical solution for scalar stateconstrained optimal control problems for which we can formulate the Hamiltonianwhich is assumed to be convex in the control variable.

Gunn Larsen, University of Groingen, The NetherlandsLecture 1 - Distributed Model Predictive Control for an Electrical Power Network

Abstract: This work aims to achieve balance of power in a group of prosumers,based on a price mechanism, i.e. to steer the di_erence between the total productionand consumption of power to zero. We first decide the information network topologysuch that the prosumers exchange price (power) information with their neighborsaccording to this topology. Based on the exchanged information and its own measuredpower demand, each prosumer uses a local control strategy to turn on and o_ itspower generator to cooperatively achieve the global balance. More speci_cally, thelocal control strategy results from distributed model predictive control based on dual

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decomposition and sub-gradient iterations. The method achieves a unique dynamicprice signal for each prosumer. Simulation results with realistic data validate themethod.

Siep Weiland, Eindhoven University of Technology, The NetherlandsLecture 1 – Introduction to Optimization

Anton Stoorvogel, University of Twente, The NetherlandsLecture 1 – On Stochastic Optimization and Monte-Carlo Expriments

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1.6 Winter Course

The 4th Winter Course was held at the University of Groningen from February 13until February 15, 2012. Dr. Vincent Andrieu, Lyon University, France taught on“Observer for Nonlinear Systems”. There were 14 participants.

1.7 Benelux Meeting

Benelux Meeting 2012

The 31th Benelux Meeting on Systems and Control was organized under the auspicesof DISC and held from March 27-29, 2012 in Heijen, The Netherlands.

The aim of this meeting is to promote research activities and cooperation betweenresearchers in Systems and Control. It is the twenty-ninth in a series of annualconferences that are held alternately in Belgium and The Netherlands. The meetingtakes place under the auspices of the Dutch Institute of Systems and Control (DISC)and the Belgian Federation of Automatic Control (IBRA).

Scientific programThe Scientific Program included three keynote speakers, namely

• Allesandro Astolfi, Imperial College London, UK• Jan Lunze, Ruhr-University, Germany• Stefano Stramigioli, Twente University, The Netherlands

Additionally, there were numerous (parallel) sessions with contributed lecturescovering a wide range of topics in Systems and Control.

An overview of the program follows. A total of 220 staff, researchers and PhD studentsattended the meeting.

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Best junior presentation award – DISC trophyAt the end of the 31th Benelux Meeting on Systems and Control, the Best JuniorPresentation award was awarded to Ewoud Vos (University of Groningen, Facultyof Mathematics and Natural Sciences) for his presentation "Port-Hamiltonian approachto deployment on a line".

The prize honors the best presentation at the Benelux Meeting by a junior presenter,i.e., a researcher working towards the PhD degree.The award consists of a certificateand the DISC Challenge Trophy.The jury for this year’s award consisted of Prof. Johan Schoukens (Vrije UniversiteitBrussel), and Dr Simon van Mourik (Wageningen University).

1.8 DISC PhD Thesis Award 2011

During the 2012 Benelux Meeting the DISC PhD Thesis Award was awarded to theDISC PhD student that defended his PhD thesis during 2011 and was selected asthe author of the best PhD Thesis. Eligible candidates are required to have completeda DISC course programme, to have defended their thesis within 54 months after thestart of their project, and to be nominated by their promotor. Each full professor canonly nominate one candidate.

Finalists for the 2011 Award were:• Daniel Dirkz (RUG-ITM)• Tijs Donkers (TU/e-ME)• Michel Franken (UT-EE)• Florian Kerber (RUG-IWI)• Erik Steur (TU/e-ME)• Solomon Zegeye (TUD-DCSC)

The DISC PhD Thesis Award 2011 was awarded to Dr.ir. Erik Steur (TU/e-ME) forhis thesis entitled “Synchronous behavior in networks of coupled systems”.

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1.9 PhD Theses 2012

MUHeijman, J. (2012, April 27) Computational Modeling of Beat-To-Beat Variability ofCardiac. Maastricht University. Prom./coprom.: Prof.dr. H.J.G.M. Crijns / Prof.dr.ir.R.L.M. Peeters / Dr. P.G.A. Volders; dr. R.L. Westra.

TUD-DCSCDoan, MD (2012, november 21). Distributed model predictive controller design asedon distributedoptimization.TUD Technische Universiteit Delft (118 pag.). Prom./coprom.: Prof.dr.ir.B De Schutter & TKeviczky.

Kuiper, S (2012, mei 08). Mechatronics and Control Solutions for Increasing theImaging Speed in AtomicForce Microscopy. TUD Technische Universiteit Delft (133 pag.). Prom./coprom.:Prof.dr.ir. PMJ Vanden Hof & Dr.ir. G Schitter.

Simonetto, A (2012, november 02). Distributed Estimation and Control for RoboticNetworks. TUDTechnische Universiteit Delft (175 pag.). Prom./coprom.: Prof.dr. R Babuska & TKeviczky.

Safaei Farahani, S (2012, november 28). Approximation Methods in StochasticMax-Plus Systems. TUD Technische Universiteit Delft (149 pag.). Prom./coprom:Prof.dr.ir. B. De Schutter & Dr.ir. T. van den Boom.

TUD-DIAMLawniczak, W (2012, december 10). Feature-based estimation for applications ingeosciences. Delft University of Technology (125 pag.). Prom./coprom.: Prof.dr.ir.AW Heemink & Prof.dr.ir. JD Jansen.

TUD-AEFalkena, W . Investigation of Practical Flight Control Systems for Small Aircraft.TUDTechnische Universiteit Delft (306 pag.) (Zutphen: Wohrmann Print Service).Prom./coprom.: Prof.dr.ir. JA Mulder & Dr. QP Chu.

Nieuwenhuizen, FM (2012, juli 04). Changes in Pilot Control Behaviour across StewartPlatform Motion Systems. TUD Technische Universiteit Delft (200 pag.) (Zutphen:Wohrmann Print Service). Prom./coprom.: Prof.dr.ir. M Mulder, HH Bulthoff & Dr.ir.MM van Paassen.

Pool, DM (2012, september 24). Objective Evaluation of Flight Simulator MotionCueing Fidelity Through a Cybernetic Approach. TUD Technische Universiteit Delft(430 pag.) (Zutphen: Wöhrmann Print Service). Prom./coprom.: Prof.dr.ir. M Mulder& Dr.ir. MM van Paassen.

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TU/e-MEB. Besselink (4 juni 2012). PhD.Thesis, Model reduction for nonlinear control systems2012, TU/e, Advisors: H. Nijmeijer, Co-advisor: I.J.M. Besselink

D. Rijlaarsdam (21 juni 2012), PhD. Thesis, Frequency domain based performanceoptimization of systems with static nonlinearities, 2012, TU/e, Advisors: M. Steinbuch,Co-advisor: P.W.J.M. Nuij

S. Adinandra (6 september 2012), PhD. Thesis, Hierarchical Coordination Controlof Mobile Robots 2012, TU/e, Advisors: H. Nijmeijer

V.D. Ngo (26 september 2012), PhD. Thesis, Gear shift Strategies for AutomotiveTransmissions 2012, TU/e, Advisors: M. Steinbuch, Co-advisor: T. Hofman

R.W. van Gils (14 november 2012), PhD. Thesis, Feedback stabilization ofPool-Boiling systems, 2012, TU/e, Advisors: H. Nijmeijer, Co-advisor: M.F.M.Speetjens

TU/e-EEEzzeldin Mahdy Abdelmonem, M. (2012, april 25). Performance improvement ofprofessional printing systems : from theory to practice. TUE :Technische UniversiteitEindhoven (161 pag.) (Eindhoven: Technische Universiteit Eindhoven).Prom./coprom.: prof.dr.ir. P.P.J. van den Bosch & prof.dr. S. Weiland.

Mutsaers, M.E.C. (2012, september 06). Control relevant model reduction andcontroller synthesis for complex dynamical systems. TUE : Technische UniversiteitEindhoven (195 pag.) (Eindhoven: Technische Universiteit Eindhoven).Prom./coprom.: prof.dr. S. Weiland & prof.dr.ir. A.C.P.M. Backx.

Sijs, J. (2012, april 26). State estimation in networked systems. TUE : TechnischeUniversiteit Eindhoven (173 pag.) (Eindhoven: Technische Universiteit Eindhoven).Prom./coprom.: prof.dr.ir. P.P.J. van den Bosch & dr. M. Lazar.

UT-AMBesseling, N.C. (2012) Strability analysis in continuous and discrete time. (2012,January 20) 107 pp. Univ. of Twente. Thesis advisor(s): prof. dr. H.J. Zwart & prof.dr. A.A. Stoorvogel. ISBN 978-90-365-3307-2

Shekhawat, H.S. (2012) Optimal Sampling and Interpolation (2012, November 29)217 pp. Univ. of Twente.Thesis advisor(s): prof. dr. A.A. Stoorvogel & dr. G. Meinsma,Ass. promotor. ISBN 978-90-365-3473-4

UT-EEBabakhani, B. (2012) Active Damping of Vibrations in High-Precision Motion Systems.PhD thesis, Univ. of Twente. Prom./coprom.:Prof.dr.ir. J. van Amerongen / Dr.ir.T.J.A. de Vries. ISBN 978-90-365-3464-2

UT-METjepkema D. (2012, November 2) Identification of stiffness and inertia parametersof an industrial welding robot using acceleration sensors. PhD thsis, Univ. of Twente.Prom./coprom.: Prof.ir. H.M.J.R. Soemers / Dr.ir. J. van Dijk

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VUKempker, P. (2012, November 23), Control for coordination of several classes ofdistributed systems. Prom./coprom.: Prof.dr. A.C.M. Ran / Prof.dr.ir. J.H. vanSchuppen.

WUAgudelo Vera, C.M. (2012, June 20). Dynamic water resource management forachieving self-sufficiency of cities of tomorrow. WUR Wageningen UR (208 pag.)([S.l.]: [s.n.]). Prom./coprom.: Prof dr ir H.H.M. Rijnaarts, Dr ir K.J. Keesman & Dr irA.R. Mels.

Omony, J. (2012, December 19). The Dynamics of the XInR Regulon of Aspergillusniger: a systems biology approach. WUR Wageningen UR (158 pag.) ([S.l.]: [s.n.]).Prom./coprom.: Prof Emeritus dr ir G. van Straten, ,Dr ir A.J.B. van Boxtel & Dr irL.H. de Graaff.

1.10 Awards

In 2012 the following awards were granted to DISC members:

DISC NWO Research Grants in the scope of the NWO Graduate Programme• Alina Doban (TU/e), "Stabilization of set-dynamics" (Lazar, van Schuppen)• Geert Folkertsma (UT), "Fast-running energy-efficient quadruped" (Stramigioli, van

der Schaft)• Sofie Haeasaert (TUD), "Identification for control of dynamic networks in biology" (Van

den Hof, Abate)• Hidde-Jan Jongsma (RUG), “Robust Synchronizatiion of Networked Multi-Agent

Systems” (Trentelman, Heemink)

ERC Starting Grant• Ming Cao (RUG), “Control of spatially distributed complex multi-agent networks”.

IEEE Transactions on Control Systems Technology Best Paper Award• Jan-Willem van Wingerden, Anton Hulskamp, Thanasis Barlas, Ivo Houtzager, Harald

Bersee, Gijs van Kuik and Michel Verhaegen, “Two-degree-of-freedom active vibrationcontrol of a prototyped ‘smart’ rotor”.

1.11 3TU Centre of Excellence Intelligent Mechatronic Systems

The three leading universities of technology in the Netherlands - Delft University ofTechnology, Eindhoven University of Technology and the University of Twente -have joined forces in the 3TU.Federation. This federation maximizes innovation bycombining and concentrating the strengths of all three universities in research,education and knowledge transfer.

By clustering research activities into Centres of Competence, the 3TU.Federationaims to strengthen the competitive position of the Dutch knowledge economy. Theresulting ‘critical mass’ is essential to create a strong knowledge base. We believethis is inseparable from the drive to achieve and maintain scientific excellence. Forthis reason, Centres of Excellence have been established within the Centres ofCompetence. These are partnerships aiming at the creation of synergy and critical

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mass in specific research topics. In these Centres our best research workers, togetherwith newly recruited top professors, will work together on a number of socially relevantthemes in coordinated, focused programmes. The five Centres of Competence /Centres of Excellence are:

• CoCHigh Tech Systems / CoE 3TU.Centre for Intelligent Mechatronic Systems• CoC Netherlands Institute of Research on ICT / CoE 3TU.Centre for Dependable ICT

Systems• CoC University Research Group on Sustainable Energy Technologies / CoE

3TU.Centre for Sustainable Energy Technologies• CoC Applications of Nano Technology / CoE 3TU.Centre for Bio-Nano Applications• CoC Fluid and Solid Mechanics / CoE 3TU.Centre for Multiscale phenomena

On top of these five research domains the three Dutch Technical Universities createda sixth CoE, the 3TU Centre for Ethics and Technology.

Each Centre of Competence has a board formed by the dean of each of the threeUniversities of Technology who is the most involved in the subject area concerned.Furthermore, each Centre of Competence has a Scientific Director who coordinatesthe work within the Centre of Competence, including the Centres of Excellence withinit, and advises the board accordingly. Within the domain of “High-Tech Systems” a3TU Centre of Excellence in Intelligent Mechatronic Systems was created,incorporating around 10M€ of investments in tenured university positions within thethree TU’s, in particular in systems and control, mechatronics and robotics. ScientificDirector of the 3TU CoE IMS is Prof. Maarten Steinbuch (TU/e).

In the scope of this 3TU CoE the following members of DISC have been appointed:• Prof. Bart De Schutter (TUD-DCSC) Hybrid Control and Intelligent

Transportation Systems• Dr. Tamas Keviczky (TUD-DCSC) Distributed Tensing and Control• Dr. Rafaella Carloni (UT-EE) Humanoid Robotics• Prof.dr. Anton Stoorvogel (UT-AM) Mathematical Systems Theory• Dr. Mircea Lazar (TU/e-EE) Hybrid systems• Dr. Dragan Kostic (TU/e-ME) Robotics• Prof.dr.ir. Maurice Heemels (TU/e-ME) Hybrid and Networked Systems• Prof.dr. Siep Weiland (TU/e-EE) Spatial-Temporal Systems for Control

1.12 National MSc programmes

In the scope of the 3TU Federation and in particular the 3TU Graduate School, DISCis involved in the 3TU MSc Program in Systems and Control (two-year program).DISC is involved in this initiative in a coordinating and facilitating role. The scientificdirector of DISC is member of the Team of Education Directors of this programme.The 3 TU program started on 1 September 2007 (http://www.3tu.nl/sc/en/).

Furthermore DISC is involved in Mastermath, the Dutch Master Program inMathematics. (www.mastermath.nl/). Dr.ir. J.W. Polderman represents DISC in theprogram council.

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1.13 Management report 2012

1.13.1 Course certificatesDuring 2012, 14 certificates for completing a course program of 27 EC were awardedto the following DISC students:

• Koos van Berkel (TU/e-ME)• Jos Elfring (TU/e-ME)• Mohamed Ezzeldin Mahdy Abdelmonem (TU/e-EE)• Sasanka Gottimukkala (RUG-JBI)• Rob Janssen (TU/e-ME)• Cesar Lopez Martinez (TU/e-ME)• Carlos Murguia (TU/e-ME)• Le Quang Thuan (RUG-JBI)• Patricio Torres (TUD-DCSC)• Marko Seslija (RUG-JBI)• Hanumant Shekhawat (UT-AM)• Ewoud Vos (RUG-ITM)• Pieter van Zutven (TU/e-ME)• Ana Virag (TU/e-EE)

1.13.2 DISC Board Meetings in 2012The DISC Board met on January 17, April 10, June 26, September 4 and November28, 2012. The meetings took place in Utrecht or by video conference. Importantagenda items were: selection and evaluation of DISC courses and schools;Membership fee for DISC groups; DISC book/25 year DISC education, DISC NextGeneration, Benelux Meeting, Summer School, Winter Course and NWO GraduateProgramme.

1.13.3 Management team meeting 2012The DISC management team met on March 28 in Heijen, The Netherlands, duringthe 31th Benelux Meeting on Systems and Control. Agenda items were reportingactivities of DISC in the preceding year, the DISC teaching and course program,NWO Graduate Programme, local Graduate Schools, Membership fee for DISCgroups and upcoming activities.

1.13.4 NWO Graduate Programme Application 2010In August 2010 DISC’s application for the NWO Graduate Programme was granted.This programme involves the organization of a Pre PhD-Track for a selected groupof high-potential MSc students in the regular MSc programs of DISC groups, includingthe 3TU MSc Systems and Control.

The intention of this special track, is that MSc students who are well qualified perpursuing a PhD, get additional research training, spend research visits to differentDISC groups, and prepare their own PhD research project proposal.The NWO grantprovides funding for 4 PhD positions (800 K€) to be awarded to the best students,who then can perform a PhD research with a supervisor and in a university of theirchoice.

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The Pre PhD-track, embedded in the 3TU MSc Systems and Control, is composedas follows:

Structure of the DISC Pre-PhD Track in the 3TU MSc Systems and Control.

In 2011 a DISC work group was installed to guide this programme. It was composedof Prof. Henk Nijmeijer (TU/e-chair), Dr. Peter Heuberger (TUD), Dr. Jan WillemPolderman (UT) and Prof. Jacquelien Scherpen (RUG).

A group of 10 high-potential MSc students was selected to enroll in this program onthe basis of an application.Out of this group 7 participants completed the full programme and defended theirfinal PhD research proposal in front of an international jury. On the basis of the juryreport four PhD Research grants – meant for funding a four year PhD researchproject – were awarded to

• Alina Doban (TU/e), Stabilization of set-dynamics, under supervision of Mircea Lazarand Jan van Schuppen

• Geert Folkertsma, (UT), Fast-Running Energy-Efficient Quadruped (Freeq), undersupervision of Stefano Stramigioli and Arjan van der Schaft.

• Sofie Haesert (TUD), Identification for Control of Dynamic Networks in Biology, undersupervision of Paul Van den Hof and Alessandro Abate.

• Hidde-Jan Jongsma (RUG), Robust Synchronization of Networked Multi-AgentSystems, under supervision of Harry Trentelman and Maurice Heemels.

1.13.5 Membership feeSince many years DISC’s operational costs have been covered by a contribution ofTUD (Department of 3mE) to the amount of 75 K€ per year.The current commitmentof TUD runs until the end of 2014. In order to cover the –increasing- costs of DISC,the Board of DISC, after consultation of all groups and the Management Team, hasdecided in 2012 to introduce membership fees for groups that participate in DISC. Iwas decided to have DISC groups pay yearly membership fee that is determined onthe basis of the number of PhD students that take DISC courses. An additional yearlybudget of around 40K€ is obtained as a result of this.

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1.14 Financial report (in Eur)

DISC budget 2012

Realized 2012budget 2012

Income

€ 75.000,00€ 75.000,00Contribution TUD

€ 3.825,00€ 0,00Course registration fees

€ 2.250,00€ 0,00NWO subsidy BeneluxMeeting

€ 2.250,00€ 0,00NWO subsidy SummerSchool

€ 44.625,00€ 42.000,00Membership fee

€ 127.950,00€ 117.000,00TOTAL

Expenditure

€ 55.105,00€ 58.000,00Salaries WD andsecretariat

€ 0,00€ 10.000,00Secretaris

€ 18.526,00€ 20.000,00Course program

€ 15.000,00€ 5.000,0025 years PhD education

€ 6.000,00€ 2.000,00DISC Summer School 2012

+€ 5.158,00€ 0,00Benelux Meeting 2012

€ 1.048,00€ 1.000,00Best Thesis Award

€ 2.515,00€ 3.000,00Winter Course 2012

€ 1.698,00€ 2.000,00NWO GraduateProgramme

€ 2.070,00€ 1.500,00IFAC Membership Fee

€ 1.677,00€ 3.000,00DISC Secretariat/Boardmeetings

€ 2.623,00€ 3.750,00DISC Website/Offset/Other

+€ 26.846,00€ 7.750,00Balance

€ 127.950,00€ 117.000,00TOTALOn 1 September 2012, it was 25 years ago that the DISC community stated itsnational PhD courses Utrecht.To commemorate this event, it was decided to publisha history-book about 25 year national cooperation in systems and control and DISC

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in the Netherlands. The DISC Board decided to spend € 15000 out of the reservesof DISC to publish and distribute this booklet, which is officially presented in 2013.

1.15 UNIT DISC

UNIT DISC is the council of research students of DISC.

They have regular contacts with the Scientific Director and also are responsible forthe course evaluations.

In 2012 UNIT DISC was coordinated by the following persons:• Douwe Dresscher (UT-EE), [email protected], 053-4892814• Yashar Zeinaly (TUD-DCSC), [email protected], 015-2782087• Mark Mutsaers (Tue-EE), [email protected], 040-2473579• Ruiyue Ouyang (RUG-ITM) [email protected], 050-3633436

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Delft University of TechnologyFaculty of Mechanical, Maritime and Materials Engineering(3mE)Delft Center for Systems and Control (DCSC)

General Information

AddressDelft University of Technology, Mekelweg 2, 2628 CD Delft, The Netherlands. Secretariat:phone: +31–15–2782473. Fax: +31–15–2786679. E-mail: [email protected]

Scientific staffdr.ir. A. Abate, prof.dr.ir. R. Babuška, dr.ir. X.J.A. Bombois, dr.ir. A.J.J. van den Boom, dr.ir.A.J. den Dekker, prof.dr.ir. B. De Schutter, dr. G.A.D. Lopes, prof.dr.ir. J. Hellendoorn, dr.P.S.C. Heuberger, dr.ir. T. Kevicky, dr.ir. J.H.A. Ludlage, dr.ir. M. Mazo Jr, dr.ir. R. Toth,prof.dr.ir. P.M.J. Van den Hof, prof.dr.ir. M. Verhaegen, dr.ir. J.W. van Wingerden

Technical and administrative staffE.G.P. de Booij, C.J.M. Dukker, ing. W.J.M. van Geest, S.M. van der Meer, ing. R.M.A. vanPuffelen, ing. J.E. Seiffers, C.J. Slinkman, M. Versloot, ir. O.K. Voorwinde, ing. F.K. Zhang

PhD studentsD. Adzkiya MSc, J. Antonello MSc, H.J. Bijl MSc, Z. Cong MSc, A.G. Dankers MSc, M.D.Doan MSc, ir. J.M. Engel, S. Esmaeil Zadeh MSc, S. Farahani MSc, M. Forgione MSc, ir.P.M.O. Gebraad, ir. I. Grondman, N.B. Groot MSc, J. Guo, A. Haber MSc, M. HajiahmadiMSc, Z. Hidayat MSc, Y. Hu MSc, ir. B. Kersbergen, A.A. Khalate MSc, L. Li MSc, S. LiuMSc, R. Luo MSc, R. Mustata MSc, S.P. Nageshrao, E. Najafi MSc, S.T. Navalkar MSc,M.G Potters MSc, Y. Qiu MSc, M. Shahbazi Aghbelagh MSc, A. Simonetto MSc, ir. E. vanSolingen, H. Song MSc, ir. P.M. Stano, S.K. Taamallah MSc, I. Tkachev MSc, P.I. TorresMSc, ir. G.J. van der Veen, ir. K.A.J. Verbert, H.R.G.W. Verstraete, Y. Wang BSc, J. XuBSc, H.W.Yoo MSc, Y. Zeinaly MSc

Temporary staff and postdocsdr.ir. M. Burger, dr.ir. P.R. Fraanje, dr. J. Kalkman, dr.ir. R.T. van Katwijk, dr.ir. R.M. Marinica,dr.ir. A. Mesbah, dr.ir. D-P. Molenaar, dr. A. Nuñez, dr. dr. A.D. Sadowska, K. Stankova, dr.A. Tejada Ruiz, dr. M. Zamani

Cooperation withEnclosed is a list of long-term collaborative partners that are involved in joint researchprojects

FundamentalsUniversity collaboration: KTH Stockholm (S), University of Aveiro (P), Hungarian Academyof Sciences (H), University of New South Wales (AU), University of Caen (F), UniversitéCatholique de Louvain-la-Neuve (B), University of Antwerp (B), Free University of Brussels(B), University of California at San Diego (USA), University of Nancy (F), Australian NationalUniversity (AU), University of Linköping (S), Aalborg University (DK), Bogazici UniversityIstanbul (T), Jilin University (PRC), University of California at Los Angelos (USA), Universityof Stuttgart (GE), Eindhoven University of Technology (NL), ETH Zurich (CH), Supelec

Delft University of TechnologyFaculty of Mechanical, Maritime and Materials Engineering (3mE)Delft Center for Systems and Control (DCSC)

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France (F), University of Siena (I), University of Ghent (B), University of Karlsruhe (GE),University of Cambridge (UK), University of Twente (NL). Industrial/Institutional collaboration:FEI (NL), Embedded Systems Institute (NL), The Scripps Research Institute (USA), TNODefense Security and Safety (NL), Royal Institute for the Marine, KIM (NL), EADS Astrium(GE), TNO (NL), Siemens AG (GE), ICIS consortium (NL).

Mechatronics and MicrosystemsUniversity collaboration: TUD Department PME/3mE, TUD Department BME/3mE, TUDFaculty of Aerospace Engineering, Eindhoven University of Technology (NL), Vrije UniversiteitAmsterdam (NL), Leiden University (NL), Graz University of Technology (A), University ofMunich (GE), Lund University (SE), Katholieke Universiteit Leuven (B), Université Libre deBruxelles (B), Technical University of Darmstadt (GE), University of the Federal ArmedForces Hamburg (GE), Budapest University of Technology and Economics (H), Politecnicodi Milano (I), University of California at Santa Barbara (USA).

Industrial/Institutional collaboration: Océ Nederland B.V. (NL), SKF (NL), Embedded SystemsInstitute (NL), Dutch Aerospace Laboratory NLR (NL), Veeco (USA), ESA ESTEC (NL),Philips AppTech (NL), Siemens (NL), LMS International (B), ERAS GmbH (GE), SiemensAG (GE), Renault Direction de la Recherche (F), Institute of Mechanics of Materials andGeostructures S.A. (G), VTT Technical Research Centre of Finland (F), Centro RicercheFIAT (I), KTH Royal Institute of Technology (S), MicroNed consortium (NL), Britisch Aerospase(UK), CIRA (I), Alenia (I), Israelian Arcraft Industry (Is), IOP Adaptive Optics (NL), IOPIntegrale Product Creatie- en Realisatie (NL).

Sustainable Industrial ProcessesUniversity collaboration: RWTH Aachen (GE), NTNU Trondheim (N), Department P&E/3mE,Department MSP/TNW, Faculty CiTG/TUD, Eindhoven University of Technology (NL).

Industrial/Institutional collaboration: PSE (UK), Shell Global Solutions (NL), Shell Explorationand Production (NL), Purac (NL), BASF (GE), TNO Industrie en Techniek (NL), IPCOS (NL),DHV (NL), Waternet (NL), Applicon (NL), DSM (NL), IHC (NL).

Automotive and intelligent transportation systemsUniversity collaboration: Eindhoven University of Technology (NL), TRAIL Research School(NL), TUD/CiTG (NL), TUD/TBM (NL), Katholieke Universiteit Leuven (B), University ofGhent (B).

Industrial/Institutional collaboration: TNO (NL), Rijkswaterstaat (NL), Siemens (D/NL), Shell(NL), Rups BV (NL), TNO (NL), Ministry of Transportation (NL), Witteveen+Bos (NL), NGIconsortium (NL), Transumo consortium (NL).

Participation in trans-national networksERNSI: European Research Network in System Identification.HYCON: Hybrid Control, Network of Excellence, EU 6th FP.SICONOS consortium: Modelling, Simulation, and Control of Non-smooth Dynamical Systems,EU 6th FP.INMAR consortium; European network for Intelligent materials for active noise reduction,EU 6th FP.

KeywordsComputational intelligence, condition monitoring, fault tolerant control, fuzzy modeling andcontrol, hybrid systems, inversion of non-linear systems, knowledge-based control,mechatronics, model-based control, multi–variable control, non-linear systems, parameterestimation, physical measurement systems, predictive control, real-time control, robotics,

Delft University of TechnologyFaculty of Mechanical, Maritime and Materials Engineering (3mE)

Delft Center for Systems and Control (DCSC)

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robust control, servo-mechanisms, signal processing, system identification, traffic control,vehicle dynamics, x-by-wire.

Brief descriptionDelft Center for Systems and Control (DCSC) coordinates the education and researchactivities in systems and control at the Delft University of Technology.

The core research activity of the DCSC is twofold: the development of new theories andnumerical tools for modeling and control of dynamic systems, and the validation of thesenew contributions in engineering applications.

The deliberately selected integration of the fundamental research line with the applicationoriented one, creates the ideal platform to systematically address problems in emergingtechnologies and to stimulate the development of innovative industrial control technology.The fundamental research activities concentrate on the three major areas of model basedcontrol design, i.e.:

• modeling• system identification• controller design

The application oriented research aims at the adaptation and integration of fundamentalinnovations in laboratory demonstrations and for industrial pilot plants covering the followingapplication domains:

• industrial process control• mechatronics and micro systems• automotive and intelligent transportation systems• physical imaging systems

The research activities in these domains are multi-disciplinary in nature and for the first 3domains are defined in concurrence with the “Speerpunt” programs of Delft University ofTechnology.

Applications

Optics and imagingThe research activities of DCSC cover the application of (newly developed) methods and toolsfor modeling, measurement and control to practical problems in various fields of physics. Oneof the target application domains is formed by physical imaging systems. It is shown how aquantitative model-based approach, accompanied by statistical experimental design, allowsprecise measurement of the atomic structure of materials from electron microscopy images.Furthermore, optimal statistical tests are developed for the detection of neural activity by meansof functional magnetic resonance imaging.We also apply modern control strategies to adaptiveoptics systems, with emphasis on ground-based telescopes.


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DISC projects

Adaptive optics for optical scanning microscopy

Prof.Dr.sc.techn G. Schitter, prof.dr.ir. M. VerhaegenProjectleader:H.W.Yoo, MScPhD students:STWSponsored by:

DescriptionThis Ph.D. project is a part of the Integrated Smart Microscopy (ISM) project, amultidisciplinary project collaborated with multiple academical and industrial groups. Theindustrial partner are Flexible Optical BV (also known as OKO technologies), ScientificVolume Imaging BV, and Leica Microsystems BV.The academic partners are Delft Universityof Technology and Erasmus MC.

The ISM project aims to develop an integrated smart confocal microscope for live cell imaging,which combines adaptive optics in the imaging path with adaptive postprocessing of theresulting 3D image data. Objective of this PhD project is to integrate prediction and controldesign methodologies in optimizing the overall performance of the new microscope system,in terms of resolution as well as product complexity and costs. In addition to investigatingthe optimal size, location of the type of sensors and actuators, we also aim to achieve higheroverall imaging performance by optimizing the tradeoff between feedback and postprocessing.

During the past few decades, the optical microscopy techniques have achieved significantimprovements in terms of spatial resolutions. For the most biological samples, however,even the diffraction limited resolution is hardly obtained due to various aberrations due tomisalignment in microscope and sample induced aberrations. In this regards, adaptive optics,which actively compensate for wavefront distortions as has been demonstrated in high-endtelescopes, has recently attracted much attention as a promising approach to obtain neardiffraction limited performance in the above mentioned applications.

At DCSC, various methodologies have been investigated to correct aberrations in variousoptical systems such as telescope and microscopes. As an extension, fast and robustadaptive optics systems for commercial confocal microscopy are developed to achieve areal time sharp image over a wide field of view.

Image manipulation for wafer plane conformity in optical lithography

prof.dr.ir. M. VerhaegenProjectleader:R.I. MustataPhD students:Delft University of Technology, STW, ASML , AAESponsored by:

DescriptionOne of the main challenges in semiconductor industry is to continue following Moore's Lawtowards ever smaller, cheaper, more powerful and energy-efficient chips, thereby improvingthe performance of electronic devices, including consumer electronics (laptops, smartphonesetc.).

Lithography is a technology used by chip manufacturers, which consists in transferring ashrunk geometrical pattern of circuit lines from a photomask to a wafer, by photomaskillumination.



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Conventional static resolution enhancement techniques are no longer sufficient when aimingfor sub-32 nanometer minimum feature size, since dynamic optical path distortions becomesignificant. For example, illumination scanning induces rapidly changing local in-plane andout-of-plane wafer deformations around the exposed area. This leads to unconformitybetween the projected image and the wafer surface.

To continue shrinking the minimum feature size, we are interested in compensating for thelocal heat-induced wafer deformations. A distributed actuation and sensing concept at thewafer stage is proposed and the implementation of fast and optimal control algorithms isinvestigated. It is expected that the above approach will contribute to the development ofnovel technologies in optical lithography that meet future requirements of sub-32 nanometerlevel feature size.

Integrated High-Resolution Observing Through Turbulence

prof.dr.ir. M. VerhaegenProjectleader:dr.ir. R.M. MarinicaParticipants:

DescriptionDynamic optical aberrations induced by atmospheric turbulence form a major limitation inthe achievable resolution of high-end optical imaging instruments, like ground-basedtelescopes and long-range surveillance cameras. Several techniques have been developedto reduce the e ect of these distortions on the imaging quality, including adaptive optics (AO)and post-facto reconstruction algorithms. Although, the two approaches have been combinedin the past, they have not been studied as constituents of an overall system, such as tooptimize the total system performance.This research proposal aims at an integrated approachof optimization of overall image quality, in which the actions of the AO deformable mirrorand the post-facto reconstruction algorithm are geared to one another.

Major improvements in resolution are expected with the joint optimization approach, inparticular with the aspects of (i) the use of AO wavefront sensor signal data and deformablemirror signal data as input to post-facto reconstruction and (ii) introducing known phaseaberrations during the real-time correction with the AO system to improve the performanceof post-facto reconstruction, in particular of phase-diversity algorithms. Moving towards anoverall real-time system, (iii) the

feedback of wavefront aberration information deduced by post-facto reconstruction into theadaptive optics system is also a very promising aspect. Furthermore, important issues likeadaptivity with respect to the time-variant turbulence statistics and the use of robust estimationtools taking into account the uncertainty in the point spread function will be addressed inthis research.

The developed techniques will be tested and validated on a laboratory set-up fi rst and lateron by performing real-life turbulence experiments on a telescope and with a long-rangesurveillance camera.


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i-OCT (Optical coherence tomography)

prof.dr.ir. M. VerhaegenProjectleader:dr. J. KalkmanParticipants:H.R.G.W. VerstraetePhD students:AgentschapNLSponsored by:

DescriptionOptical coherence tomography (OCT) is a high resolution imaging technique that can take3D images of tissue. OCT is similar to ultrasound in that it measures the echo of light reflectedfrom tissue, however it uses interferometry to determine the extremely small time-of-flightof light reflected from a few millimeters depth.

OCT technology can be used to form high resolution depth scans of biological specimens,such as the retina (see figure) or arterial all, and plays a key role in early detection ofanomalies in vision, heart conditions, etc. The spatial resolution enables an accurate (up to4-10 micron) imaging of the biological layers up to few millimeters deep. However due toaberrations induced by the imaging optics or the specimen, the lateral resolution is limited.

In this project we develop adaptive optics technology that can compensate for the wavefrontaberrations and yield high resolution images both axially and laterally, but at the same timeresult into a cost-effective hardware design.This leads to a multi-criteria optimization problemwhere from the beginning the presence of a feedback loop is taken into consideration in thedesign of the imaging instrument.

Smart microscopy of biological tissues

prof.dr.ir. M. VerhaegenProjectleader:J. Antonello, MScPhD students:STWSponsored by:

DescriptionMicroscopy has become increasingly more important in biological and biomedical work.Thisis to a great extent due to the development of advanced imaging methods such as confocalmicroscopy and multi-photon excitation microscopy that provide 3-D imaging in (opticallythick) specimens. At present, multi-photon excitation microscopy is the technique of choicefor high-resolution in-vivo imaging. Unfortunately, the use of these techniques is seriouslyhampered by specimen-induced aberrations that result in reduced depth penetration, lossof spatial resolution, and increased phototoxicity.

Current implementations of adaptive optics (AO) provide evidence that AO can significantlyimprove image quality, depth penetration, and spatial resolution while reducing phototoxicityin scanning microscopy. However, severe speed limitations render them impractical forreal-life applications. Here, we will focus on the development of fast, active compensationmethods for specimen-induced wavefront aberrations. High compensation speeds will berealized by using adaptive optics in combination with smart predictive algorithms that takeinto account all system properties including the scanning nature of the acquisition, thedynamic properties of the deformable mirror based AO and the nature of the opticaloptimization. To realize the above, academic experts in the area of advanced microscopy(Molecular Biophysics group), adaptive optics (Leiden Observatory group) and advanced



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control systems (Delft Center for Systems and Control) will closely collaborate. The team isfurther strengthened by the involvement of relevant industrial partners.

The method will be validated in tissue imaging experiments including in-vivo imaging of skin,in-vivo tumour mouse models and isolated arteries. The latter part of the project will becarried out in collaboration with (bio)medical groups.

Process technologyThe relevant trends in process industry could be summarized as: better profitability, increasedflexibility and the incorporation of sustainability.The current research focus is on profitabilityand flexibility and could be summarized as model-based control/optimization of ``difficult''unit operations and complete plants. In this research three aspects can be recognized:Modeling: this includes modeling, validation, identification and reduction. After modeling weshould end up with a model that has sufficient accurate predictive power at acceptablecomputational cost. Observation: Attention is paid to extended Kalman filters and horizonestimators. Control/optimization: The research in this area concentrates on dynamicoptimization (sequential and simultaneous approach) but also on the integration of controland optimization.This research is done in close cooperation with the process industry: Bayer,Shell, Solvay, AKZO, Unilever, ...

Batch-to-batch learning for process control with application to coolingcrystallization.

prof.dr.ir. P.M.J. Van den HofProjectleader:dr.ir. X.J.A. BomboisParticipants:M. Forgione, MScPhD students:ISPTSponsored by:

DescriptionCrystallization can be defined as phase change in which a solid product is obtained from asolution, melt or a gas. In the industrial practice crystallization is utilized as a separation andpurification step in sectors such as pharmaceutical, food and fine chemicals.

The process is often operated in batch mode. The solution is loaded into the vessel at thebeginning of a batch and the solid product is removed at the end. The batch time is of theorder of few hours. Multiple batches are performed in order to fulfil the production demand.

In many cases, stringent requirements on the quality of the final product have to be met.The control of a number of variables throughout the batch infuences the quality of the finalproduct to a large extent. For this reason, the industries in the field are interested into theintroduction of advanced automation technology.

Batch operations bring both challanges and opportunities for identification and control. Fromone hand, batch process system are operated over a wide dynamical range. For this reason,strategies based on linearization around a single operating point lead often to poor results.In some cases, first-principles models describing the full nonlinear dynamic behavior areavailable. Unfortunately, these models are often either not very accurate or not suitable forcontrol purposes.

On the other hand, the repetitive nature of batch processing allows the use of iterativetechniques based on the information collected during the previous runs.

In this project we are developing identification and control strategies


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suitable for industrial batch processes such as crystallization. We are particularly interestedin Batch-to batch Identification & Optimization, Iterative Learning Control, Experiment Design

Least costly identification experiment for control

prof.dr.ir. P.M.J. Van den HofProjectleader:dr.ir. X.J.A. Bombois, M. Gevers (Université Catholique de Louvain, Belgium),G. Scorletti (Université de Caen, France), H. Hjalmarsson (KTH, Sweden),M. Barenthin (KTH, Sweden), M. Gilson (CRAN, France)

Participants:

DescriptionModel-based control has nowadays reached many industrial sectors (chemical industry,high-tech manufacturing industry, ...) as a crucial technology in realizing optimal processoperation. However, the development of model-based control is still restrained by variousopen issues in control and system theory. In most of these issues, the harmonious interactionbetween system identification and robust control design is very important. Since the beginningof the nineties, important steps have been taken towards this harmonious interaction. Indeed,it is now possible, given a model and its related uncertainty as delivered by systemidentification, to check whether a controller meets the robust performance requirements.However, until very recently, there was still a complete lack of results allowing the designof robust controllers based on cheap and plant-friendly identification. Indeed, until then, veryfew attention had been devoted on the choice of the data used to identify the model and itsuncertainty region and the lack of clear guidelines for the choice of these data generally leadto identification experiments that were more expensive than actually necessary, i.e. theidentified uncertainty region was either too large (and thus unusable) or smaller than strictlynecessary for the required level of performance. Knowing that the generation of informativedata for an identification experiment is the most expensive step of the whole robust controldesign procedure, the related economic loss could be very important.

Based on these considerations, a brandnew line of research has recently been defined.Thisresearch aims at developing tractable techniques for an optimal design of the identificationexperiment. In particular, the objective is to determine the least costly identification experimentthat delivers sufficient information on the true system dynamics (i.e. that delivers a modelwith a sufficiently small uncertainty region) for the design of a robust controller with asatisfactory performance. In particular, the influence of short data sets and the extension ofthe concepts towards performance monitoring and robust filtering are currently investigated.

Robotics and mechatronicsControl engineering methods are developed for mechatronic systems of the scale ofmillimeters and micrometers. Examples of applications are in adaptive optics where use ismade of a deformable mirror with a large array of sensors and actuations, position controlin a micro compact disk or hard disk, etc. Also on the macro-scale the DCSC collaborateswith industrial partners like Océ, IHC-Systems, SKF, TNO, etc. to develop control strategiesfor innovative mechatronic designs, such as X-by-wire steering or braking.



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Adaptive learning control for offshore windturbines

prof.dr.ir. M. VerhaegenProjectleader:dr.ir. J.W. van WingerdenParticipants:H.J. Bijl, MScPhD students:STWSponsored by:

DescriptionThe STW project "Smart Design Technology for Reliable Smart Rotors to make Large ScaleWind Turbines economically attractive (SMART-WIND)" will contribute to the developmentof offshore wind energy by investigating the control of fatigue loads and active damping ofstructural vibrational modes. The proposed way to go is the use of smart dynamic rotorcontrol: every rotor blade will be controlled separately and the properties of each blade willbe altered by making use of distributed control over the blade length. This will be possibleby making use of "Smart" actuators and sensors.

In this project an innovative approach of model based robust controller design will bedeveloped based on the strong past performance of the members of the DCSC. Thedevelopment of system identification tools for robust controller design will be extendedtowards Linear Parameter Varying (LPV) systems. Further, this fundamental experience willbe combined with the application expertise the DCSC has acquired in vibration reductionusing "Smart" materials.

Automatic autorotation of a rotorcraft Unmanned Aerial Vehicle (UAV)

prof.dr.ir. P.M.J. Van den HofProjectleader:dr.ir. X.J.A. BomboisParticipants:S. Taamallah, MScPhD students:NLRSponsored by:

DescriptionAutorotation is a rotorcraft flight condition in which the lifting rotor is driven entirely by actionof the air when the rotorcraft is in motion with an engine-out situation. During an autorotation,the main rotor is not driven by a power plant, but by air flowing through the rotor discbottom-up while the vehicle is descending rapidly. The power required to keep the rotorspinning is obtained from the aircraft's potential and kinetic energy. An autorotation is thusused when the engine fails in a helicopter, or when a tail rotor failure requires the pilot toshut down the engine. It is comparable to gliding in a fixed-wing aircraft without an operatingpower plant.

The objective of this project is to design an on-board automatic system which would kick inonce engine failure had been detected. Such a system could indeed improve the overallsystem safety of manned and unmanned helicopters. Its purpose would be to optimallymanage the available energy (potential, kinematic in airspeed and rotor RPM) at the instantof engine failure, and perform a safe landing.

Four main research areas have been identified in this project: (i) modeling of the helicopterflight dynamics, (ii) model validation, (iii) avionics and sensors data fusion, and finally (iv)control and optimal 3D flight.


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Automatic generation of control software for mechatronic systems

prof.dr. R. Babuška, prof.dr.ir. B. De SchutterProjectleader:dr. G.A.D. LopesParticipants:SenterNovemSponsored by:

DescriptionDesign of a mechatronic system consists of many domains: mechanics, electronics,embedded hardware and software, and control. The design begins with the functionaldescription of the mechatronic system. In traditional design approach the design continueswith the mechanical design followed by the electronics design, and then the embeddedhardware and software co-design is completed. Finally the controller which will maintain theglobal behavior of the mechatronic system is designed and the control code is embeddedinto the system whose body is almost completed before control design phase.

What we want to achieve is a new design methodology for the design of mechatronic systemswhere the four domains: mechanics, electronics, embedded hardware and software, andcontrol designs are initiated right after the functional description of the system specifications(see Figure 1). In this approach, we will need an integration framework to bring these domainstogether so that all these four domains will interact with each other during the whole designprocess of the mechatronic system.

We will mainly focus on the integration of the control design and the electronics designincluding the embedded hardware and software design, basically the control board on whichthe generated control software will be validated to meet the system specifications, consideringthe real-time embedded systems programming issues.

The first thing to be done is to find a way to design controllers using the qualitative behaviorsof the plant to be controlled and the performance requirements for the closed loop controlsystem. We will investigate which qualitative parameters related to the plant and theperformance requirements are necessary to design the controller.

After having the qualitative behaviors, some quantitative parameters will be obtainedconsidering the timing issues for real-time implementation of the control algorithm on theactual hardware which is the control board. There will be interaction with the control designand electronics design domains in this sense of having the flexibility of choosing themicroprocessor's processing speed to meet the sampling time constraint, and choosing theA/D, D/A converters to meet the resolution needs, choosing the ROM, RAM size such thatall the control code and the data to be processed simultaneously can be fit in.

Data-driven control for the next generation of wind turbines

dr.ir. J.W. van WingerdenProjectleader:S.T. Navalkar, MScPhD students:EU, FLOWSponsored by:

DescriptionAn ongoing trend in wind turbine development is the increase in rotor size. These largerotors inherently become more flexible and introduce more interaction between blades andtower. Several new technologies have been conceived to reduce loads on these future windturbines. Among these are individual pitch control (IPC) and the smart rotor, where distributedtrailing edge flaps are used to influence the lift locally. To allow effective control of fatigue



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and extreme loads, new measurement techniques are being developed such as LIDAR andlocal flow measurements. Such measurement techniques may allow a degree of feed-forwardcontrol by anticipating wind disturbances.

In this research programme we investigate data-driven methodologies to design controllersfor future wind turbines. These include, for example, novel system identification techniques,online disturbance modelling and efficient model predictive control.The basis for all methodsis formed by numerically reliable and robust algorithms from the fields of linear algebra andconvex optimisation.

Intelligent control of legged robots

prof.dr. R. BabuškaProjectleader:dr. G.A.D. LopesParticipants:Delft University of TechnologySponsored by:

DescriptionThis project aims to study various classes of machine learning tools applied to real leggedrobots.

Nature provides the best inspiration for the field of robotics. The complex neuromechanicaltools inherited through DNA endows animals with a collection of sophisticated reactive andlearning capabilities. In this project we take inspiration from nature to focus on the study ofspecific machine learning tools applied to concrete robotics applications. Reinforcementlearning, thanks to its attractive bio-inspired mathematical framework, is our main tool ofresearch.

The multi-disciplinary nature of this project encompasses the following topics:• Low level control of nonlinear hybrid dynamical systems via traditional control

methodology combined with machine learning tools. This includes the synthesis ofmotion gaits and energetic optimizations of motion.

• Supervisory control for navigation augmented with identification/fault detection andfault tolerant control.

• Hardware/software development of a modular high dynamical robotic platform.• The development of a vision sensor for odometry and integration of exteroceptive

sensors with inertial measurements for state estimation and fault detection.

Learning in Sequential Composition of Control

prof.dr. R. BabuškaProjectleader:dr. G.A.D. LopesParticipants:E. Najafi, MScPhD students:

DescriptionDesigning motion controllers for ground robots that need to traverse unstructured terrainsis a challenging problem. This is due to the fact that such controllers should able to copewith modeled and unmodeled situations. For example, a mobile robot should be able toexecute different tasks such as walking, jumping, running, going up stairs, in different typesof terrain. This class of problems cannot be solved by linear controllers and nonlinearcontrollers must be used. In this framework each task requires a specialized nonlinearcontroller. A supervisory mechanism is then needed to compose the specialized controllers.This is called sequential composition of controllers and such an approach requires a


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supervisor whose task is to switch between the controllers in appropriate way. In theformulation of sequential composition of controllers, when the system reaches its goal whichhas been designed to lie inside the domain of attraction, a transition event occurs betweendiscrete supervisor states.

This project explores automatic synthesis of composable controllers and of the supervisor.Some challenges are: 1) Describing the domain of attraction for each controller, particularlyfor nonlinear controllers; 2) Describing the goal set for each controller; 3) Solving the problemof when the desired goal does not lie within the domain of attraction of any controller; 4)Solving the problem of when there is no intersections between the domains of attraction ofthe controllers; 5) Employ model based and learning approaches to enlarge the domains ofattraction.

Three case study scenarios will be considered within this project which are: a) Anunderactuated 1-DOF nonlinear system; b) Mode transition in an autonomous six-leggedmobile robot; c) Negotiation of complex terrains on the same robot.

Transportation and infrastructureThe traffic and transportation research of DCSC focusses on the control of large-scaletransportation system with a main emphasis on freeway and road traffic networks. In addition,we also consider control of railway networks.The primary control strategy is model predictivecontrol. Furthermore, we also consider distributed control of large-scale traffic networksusing a distributed and/or hierarchical multi-agent control approach.

Ant Colony Optimization for Dynamic Traffic Routing

prof.dr.ir. B. De Schutter, prof.dr. R. BabuškaProjectleader:Z. Cong, MScPhD students:

DescriptionAnt Colony Optimization (ACO), in Swarm Intelligence methods, refers to an optimizationtechnique of mimicking the intelligent collective behavior of groups of ants that may inthemselves have only very limited intellectual capabilities. The class of ACO algorithms hasproven to be very powerful optimization heuristic of solving combinatorial optimizationproblems.

In this project, we investigate the use of the ACO algorithm for dynamic traffic routingproblems. Because ants and vehicles are similarly individual moving agents in networks,we use ants to assist to (re)direct traffic at junctions in a traffic network corresponding to theevolving traffic conditions as time progresses. However, the standard ACO algorithm is notcapable of solving the routing optimization problem aimed at the system optimum, which isvery important in traffic system, and therefore a new ACO algorithm is developed to achievethe goal of finding the optimal traffic assignment in the network.

Optimal and model predictive control of railway systems

dr.ir. T.J.J. van den Boom, prof.dr.ir. B. De SchutterProjectleader:

DescriptionIn this project we extend the model predictive control framework (MPC), which is a verypopular controller design method in the process industry, to railway systems. Usually MPCuses linear (or nonlinear) discrete-time models. However, railway networks and subwaynetworks cannot adequately be described by such models.



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First, we have introduced a modeling framework for railway systems with both hard and softconnection constraints. A typical example of a hard connection constraint in a railway contextis when a train should give a guaranteed connection to another train. However, in somecases (e.g., if there are delays) we could allow a train to depart although not all trains towhich it should give connections according to the schedule have arrived at the station: ifsome of these trains have a too large delay, then it is sometimes better -- from a globalperformance viewpoint -- to let the train depart anyway in order to prevent an accumulationof delays in the network. Of course, missed connections lead to a penalty due to dissatisfiedpassengers or due to compensations that have to be paid. Synchronization constraints thatmay be broken (but at a cost) are called soft connection constraints. We also consider anextra degree of freedom for the control to recover from delays by letting trains run fasterthan their nominal speed if necessary. Of course, this control action will also lead to extracosts (due to increased energy consumption or faster wear of the material).

Next, we have extended the MPC framework to railway systems while still retaining theattractive features of conventional MPC. The main aim of the control is to obtain optimaltransfer coordination and/or to recover from delays in an optimal way by breaking connectionsand/or letting some trains run faster than usual (both at a cost). In general the MPC controldesign problem for railway systems leads to a nonlinear non-convex optimization problem.We have shown that the optimal MPC strategy can be computed using extended linearcomplementarity problems or integer programming algorithms.

Other examples of systems with both hard and soft synchronization constraints for whichthis approach can be used are subway networks and logistic operations.

Sustainable mobility with cooperative vehicle infrastructure systems

prof.dr.ir. B. De Schutter, prof.dr.ir. J. HellendoornProjectleader:M. Hajiahmadi, MScPhD students:

DescriptionLarge-scale mixed urban and freeway networks needs hierarchical elegant control andmanagement frameworks. In this research, we tackle some important parts of this hugeproblem. In the modeling part, recently developed traffic flow models are studied and extendedfor our control purposes. The link transmission model for freeway networks and themacroscopic fundamental diagram (MFD) approach for high-level modeling of urban areasare considered as the base of our research. In the hierarchical control scheme, we mainlyfocus on the high level and later on we develop the connection to the lower level controlusing coordination and cooperation techniques.

In the control part, we utilize the theories from the hybrid and switched systems to improvethe traffic conditions, maximize the throughput, reducing the travel delays in the network,etc. To be more precise, we have two approaches; hybrid model predictive control and itsdistributed versions, and the robust feedback control for switched systems and also theconnection between these two. In both cases, we use the existing methods available in theliterature and as for our challenging application, we need to develop theories at some points.All in all, this research focuses on the traffic flow modeling and the application oriented hybridand switched systems theory.

Wind energyWind enery is increasingly used as as source of clean, renewable power. The research ofDCSC in this field focusses on lowering maintenace costs by applying mechatronic


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techniques. Large wind farms consist of hundreds of individual wind turbines which areconnected to the electric power transmission network. Offshore wind is steadier and strongerthan on land, and offshore farms have less visual impact, but construction and maintenancecosts are considerably higher. Small onshore wind farms provide electricity to isolatedlocations. Utility companies increasingly buy surplus electricity produced by small domesticwind turbines.



DescriptionThe trend with offshore wind turbines is to increase the rotor diameter as much as possible.The reason is that the foundation costs of offshore wind turbines amount to a large part ofthe total costs. Therefore designers want to increase the energy yield (which increasesquadratically with the rotor diameter) per wind turbine as much as possible to reduce thecosts

The STW project "Smart Design Technology for Reliable Smart Rotors to make Large ScaleWind Turbines economically attractive (SMART-WIND)" will contribute to the developmentof offshore wind energy by investigating the control of fatigue loads and active damping ofstructural vibrational modes. The proposed way to go is the use of smart dynamic rotorcontrol: every rotor blade will be controlled separately and the properties of each blade willbe altered by making use of distributed control over the blade length. This will be possibleby making use of "Smart" actuators and sensors.

Control of Wind Farms

prof.dr.ir. M. VerhaegenProjectleader:dr.ir. J.W. van WingerdenParticipants:ir. P.M.O. GebraadPhD students:Delft University of Technology, Far and Large Offshore Wind (FLOW)Sponsored by:

DescriptionBy extracting kinetic energy from the wind flow, a wind turbine reduces the wind speed in awake that forms downstream of the wind turbine rotor. In a wind farm, in which turbines areplaced relatively close to each other, this wake effect can reduce the power production ofdownstream turbines. Also, the wake may introduce additional loads on downstream turbines.The aim of this project is to develop data-driven distributed control algorithms for maximizingthe total power output of a wind farm, and balancing the loads on each of the turbines, thattakes into account the wake interaction effect between the turbines.



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DescriptionAn ongoing trend in wind turbine development is the increase in rotor size. These largerotors inherently become more flexible and introduce more interaction between blades andtower. Several new technologies have been conceived to reduce loads on these future windturbines. Among these are individual pitch control (IPC) and the smart rotor, where distributedtrailing edge flaps are used to influence the lift locally. To allow effective control of fatigueand extreme loads, new measurement techniques are being developed such as LIDAR andlocal flow measurements. Such measurement techniques may allow a degree of feed-forwardcontrol by anticipating wind disturbances.


Offshore Wind Power Plant control for minimal loading

dr.ir. J.W. van WingerdenProjectleader:ir. P.M.O. GebraadPhD students:

DescriptionThe economical feasibility of the wind energy industry greatly depends on the reliability andmaintainability of new large scale wind parks/wind farms. Especially for offshore wind farmswhere the distributed turbines are connected into a network, the topic of predictivemaintenance is crucial in the explosive growth. On a wind farm, individual optimization ofeach turbine is now mainly done temporally, taking the local (temporal) changes of the windinto account. The optimization on a global scale is of interest and has been investigated ina centralized framework.The global fault tolerant optimization of a wind farm in a distributedframework is of interest for scalability, maintainability and reliability and therefore will havegreat economical impact.

So far the problem of wind farm control only considered the problem of nominal performanceoptimization. The challenge is still open to develop algorithms to accurately update andreconfigure the distributed controller when the wind profile is changing, and/or when theperformance of individual components on wind turbines degrades, fault tolerant control. Forexample when a turbine fails this has to be detected, communicated towards the otherturbines and their controller should be reconfigured to optimize the performance of the windfarm (global performance).

Objectives of this project are:

Set-up of a state-of-the-art virtual simulation environment that models the dynamics of thewind farm on a time-scale appropriate for real-time control.

Optimize the energy production by the development of a distributed controller, taking theglobal (spatial) changes in the wind profile into account.


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Development of novel system identification techniques and adaptive control strategies fornonlinear/distributed systems. This enables taking into account changes in the dynamics ofthe wind turbine system due to wear and tear or changing wind profiles, and adapting thecontroller accordingly: the data-driven control methodology.

The methodology is evaluated on a number of challenging load cases and fault scenarios.In which the effectiveness of the proposed approach is presented and computational aspectsare investigated.

This PhD project is part of the Far and Large OffshoreWind (FLOW) innovation program.

FundamentalsResearch at DCSC covers a variety of conceptual and algorithmic aspects related to modelingof and controller design for dynamical systems. Addressed are first-principal modeling aswell as deterministic and statistical data-based system identification, including a descriptionof the potential plant-model mismatch. Techniques for analyzing and designing controllersinclude the application of physical principles, semi-definite programming and nonlinearoptimization, both for off-line and on-line implementation. Particular emphasis is laid on anunderstanding of how to synthesize structured, robust and fault-tolerant controllers forpossibly large scale-systems, and on developing the related computationally efficientalgorithms.

Distributed and large-scale systems

Control of Wind Farms

prof.dr.ir. M. VerhaegenProjectleader:dr.ir. J.W. van WingerdenParticipants:ir. P.M.O. GebraadPhD students:Delft University of Technology, Far and Large Offshore Wind (FLOW)Sponsored by:

DescriptionBy extracting kinetic energy from the wind flow, a wind turbine reduces the wind speed in awake that forms downstream of the wind turbine rotor. In a wind farm, in which turbines areplaced relatively close to each other, this wake effect can reduce the power production ofdownstream turbines. Also, the wake may introduce additional loads on downstream turbines.The aim of this project is to develop data-driven distributed control algorithms for maximizingthe total power output of a wind farm, and balancing the loads on each of the turbines, thattakes into account the wake interaction effect between the turbines.

Distributed control of large-scale multi-class traffic networks

prof.dr.ir. B. De Schutter, prof.dr.ir. J. HellendoornProjectleader:S. Liu, MScPhD students:

DescriptionMulti-class traffic models describe traffic network based on different classes of vehicles,such as trucks, vans, and cars. In comparison with single-class models, this leads torepresentations that are closer to real traffic networks . Applying multi-class traffic modelsin traffic management therefore offers promising prospects of improving the control efficiency.

In this project, we develop multi-class traffic flow models and multi-class emission models.These multi-class traffic models are used in on-line model-based control approach (Model



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Predictive Control). We integrate multi-class traffic flow models with multi-class emissionmodels and use them to find a balanced trade-off between total time spent and totalemissions. We investigate the performance of both fast, first-order models (FASTLANE)and slower, more accurate models (METANET).

As a next step, Distributed Model Predictive Control will be applied in the multi-class trafficcontrol approach, to improve the computation speed and refine the control performance. Inaddition, we will also consider robust control.

Image manipulation for wafer plane conformity in optical lithography

prof.dr.ir. M. VerhaegenProjectleader:R.I. Mustata, MScPhD students:Delft University of Technology, STW, ASML , AAESponsored by:

DescriptionOne of the main challenges in semiconductor industry is to continue following Moore's Lawtowards ever smaller, cheaper, more powerful and energy-efficient chips, thereby improvingthe performance of electronic devices, including consumer electronics (laptops, smartphonesetc.).

Lithography is a technology used by chip manufacturers, which consists in transferring ashrunk geometrical pattern of circuit lines from a photomask to a wafer, by photomaskillumination.

Conventional static resolution enhancement techniques are no longer sufficient when aimingfor sub-32 nanometer minimum feature size, since dynamic optical path distortions becomesignificant. For example, illumination scanning induces rapidly changing local in-plane andout-of-plane wafer deformations around the exposed area. This leads to unconformitybetween the projected image and the wafer surface.

To continue shrinking the minimum feature size, we are interested in compensating for thelocal heat-induced wafer deformations. A distributed actuation and sensing concept at thewafer stage is proposed and the implementation of fast and optimal control algorithms isinvestigated. It is expected that the above approach will contribute to the development ofnovel technologies in optical lithography that meet future requirements of sub-32 nanometerlevel feature size.

Modeling and Optimization on Local Traffic Networks

prof.dr.ir. J. HellendoornProjectleader:Y. Hu, MScPhD students:

DescriptionThe increasing number of cars and bicycles and the growing population make traffic systemsmore and more unstable. One accident can lead to a huge traffic jam. In order to improvethe reliability and capacity of traffic networks, this research aims at the modeling of trafficnetworks and the finding of optimization solutions. Multi-agent multilayer control methodsbased on MPC will be adopted.


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Model-Predictive Railway Traffic Management

dr.ir. T.J.J. van den Boom, prof.dr.ir. B. De SchutterProjectleader:ir. B. KersbergenPhD students:STW, NWOSponsored by:

DescriptionDue to the increased traffic on the roads people are looking for attractive alternatives toreach their destination. Especially for longer trips railway transportation is an attractivealternative. Because of this more people are traveling by train, resulting in the railwaynetworks being operated closer to their maximum capacity. This has negative effects on therobustness of the timetable: a few small delays in the network can cause numerous secondarydelays and spread over large parts of the network. It is therefore important that these initialdelays are detected and dealt with as efficiently as possible.

Current practice of many railway operators is to divide the network into several dispatchingareas, each with their own dispatcher, who tries to deal with the problems of his dispatchingarea as efficiently as possible. The dispatcher can make changes in the order of the trainsdeparting and arriving at stations, cancel trains and connections, or reroute trains. Thedispatchers base their decisions on a given set of rules and their experience. Thesedispatching decisions might be optimal for the given dispatching area, but the dispatchersare often unable to get a clear picture of the situation in the entire network and as a resulttheir actions might cause unnecessary delays in other parts of the network.

To address this problem we are developing a strategy to determine the dispatching actionsthat result in the largest reduction of the sum of delays in the entire network. We use arailway traffic model, described as a discrete event system, to predict the propagation of thedelays and the effects of dispatching actions on this propagation. Based on the model wedefine a mixed integer linear programming problem. By solving the Mixed Integer LinearProgramming (MILP) problem the optimal dispatching action are determined.

The main is solving this problem within a very short time period. The problem needs to besolved very quickly because the results need to be applied during the daily operation of therailway network and the operation cannot be delayed because the problem has not beensolved yet. We aim to achieve a reduction in the computation time by reducing the size ofthe discrete event system and by doing so we also reduce the problem size of the MILPproblem, resulting in shorter computation times. We are also performing research ondistributed optimization, further reducing the computation time by distributing the problemover multiple computers, while still solving the original problem optimally.

Multi-agent control of a fleet of cybercars

dr.ir. T.J.J. van den Boom, prof.dr.ir. B. De SchutterProjectleader:R. Luo, MScPhD students:CSCSponsored by:

DescriptionCybercars are road vehicles with fully automated driving capabilities. A fleet of such vehiclesforms a managed transportation system for passengers, with on-demand and door-to-doorcapabilities. Therefore, personal mobility will be greatly enhanced if cybercars were widelyused in the future.



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Although automated driving technology has been developed for individual vehicles, the lackof efficient control strategies for a fleet of vehicles is still one of the biggest challenges thatcybercars are facing. Actually, centralized control is tractable when the number of vehiclesis small. However, for reasons of scalability, fast computation, and robustness, a centralizedcontrol strategy will not be tractable for large-scale deployments. In order to overcome thischallenge, a distributed control method where cybercars cooperate with each other is needed.

When it comes to cooperation, cybercars can be characterized as decision-making agentswith extensive on-board processing capabilities and communication as well as abundantinformation of the environment. Our aim is to develop efficient distributed control methodfor cybercars where on-board controllers optimize the routes of all vehicles in a distributedand cooperative way and the total time spent (TTS) of passengers and total energyconsumption is minimal.

Model predictive control (MPC) is widely recognized as a high performance control approachthat can be used to determine optimal control actions for constrained systems. It determinesthese control actions by solving a constrained finite-horizon optimal control problem in areceding horizon fashion. In our research, MPC is used as base to develop efficient distributedcontrol methods.

The route that we follow to conduct our research is:

1. Describing the overall problem using hybrid model.

2. Decomposing the overall problem such that the subproblems are tractable and the resultingsolution is as close as to the globally optimal solution.

3. Solving the resulting optimization problem in a distributed way.

4. Developing new approaches for distributed MPC.






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Objectives of this project are:• Set-up of a state-of-the-art virtual simulation environment that models the dynamics

of the wind farm on a time-scale appropriate for real-time control.• Optimize the energy production by the development of a distributed controller, taking

the global (spatial) changes in the wind profile into account.• Development of novel system identification techniques and adaptive control strategies

for nonlinear/distributed systems. This enables taking into account changes in thedynamics of the wind turbine system due to wear and tear or changing wind profiles,and adapting the controller accordingly: the data-driven control methodology.

• The methodology is evaluated on a number of challenging load cases and faultscenarios. In which the effectiveness of the proposed approach is presented andcomputational aspects are investigated.

Sustainable mobility with cooperative vehicle infrastructure systems

prof.dr.ir. B. De Schutter, prof.dr.ir. J. HellendoornProjectleader:M. Hajiahmadi, MScPhD students:

DescriptionLarge-scale mixed urban and freeway networks needs hierarchical elegant control andmanagement frameworks. In this research, we tackle some important parts of this hugeproblem. In the modeling part, recently developed traffic flow models are studied and extendedfor our control purposes. The link transmission model for freeway networks and themacroscopic fundamental diagram (MFD) approach for high-level modeling of urban areasare considered as the base of our research. In the hierarchical control scheme, we mainlyfocus on the high level and later on we develop the connection to the lower level controlusing coordination and cooperation techniques.

In the control part, we utilize the theories from the hybrid and switched systems to improvethe traffic conditions, maximize the throughput, reducing the travel delays in the network,etc. To be more precise, we have two approaches; hybrid model predictive control and itsdistributed versions, and the robust feedback control for switched systems and also theconnection between these two. In both cases, we use the existing methods available in theliterature and as for our challenging application, we need to develop theories at some points.All in all, this research focuses on the traffic flow modeling and the application oriented hybridand switched systems theory.

Hybrid and nonlinear systems

Analysis and Control of Stochastic Hybrid Systems

dr.ir. A. AbateProjectleader:I. Tkachev, MScPhD students:NWO, MoVeSSponsored by:

DescriptionStochastic models are important when dealing with system affected by an uncertainty.Theyallow for a range of application areas, a few examples being Biology, Power Networks andFinance.

This project is focused on the analysis and control synthesis performed over complexstochastic models, in particular Markov processes and Stochastic Hybrid Systems. We use



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the tools of Applied Mathematics and Computer Science to come up with novel approachesto the problem, formal on the one hand and computationally efficient on the other. A specialattention is paid to such methods as model-checking and approximate bisimulation:non-classical optimal control techniques that have quickly showed their advantages.

The outcomes of our research on a theoretical side are further tested on the benchmarkexamples in Finance (ruin of an insurance company, default cascades in financial networks)and Biology (control of a protein expression in a cell).

Analysis and Verification of Stochastic Hybrid Systems

dr.ir. A. AbateProjectleader:.Participants:S. Esmaeil Zadeh, MScPhD students:MoVeS, AMBISponsored by:

DescriptionStochastic Hybrid Systems (SHS) are dynamical models that are employed to characterizethe probabilistic evolution of systems with interleaved and interacting continuous and discretecomponents.

The formal analysis, verification, and optimal control of SHS models represent relevant goalsbecause of their theoretical generality and for their applicability to a wealth of studies in theSciences and in Engineering.

In this project, we investigate and develop innovative analysis and verification techniquesthat are directly applicable to general SHS models, while being computationally scalable.The first stage of the study entails mostly analytical work: the project aims at generatingresults that are both theoretically formal and computationally attractive. It will furthermoredevelop dedicated software for the analysis of SHS.

The theoretical and computational outcomes will be tested in or applied to a number ofstudies, in particular to models drawn from Biology and power networks.

Analysis and Verification of Stochastic Hybrid Systems

dr.ir. A. AbateProjectleader:NWOSponsored by:

DescriptionStochastic Hybrid Systems (SHS) are dynamical models that are employed to characterizethe probabilistic evolution of systems with interleaved and interacting continuous and discretecomponents.

The formal analysis, verification, and optimal control of SHS models represent relevant goalsbecause of their theoretical generality and for their applicability to a wealth of studies in theSciences and in Engineering.

Indeed in a number of practical instances the presence of a discrete number of continuouslyoperating modes (e.g., in fault-tolerant industrial systems), the effect of uncertainty (e.g., insafety-critical air-traffic systems), or both occurrences (e.g., in models of biological entities)advocate the use of a mathematical framework, such as that of SHS, which is structurallypredisposed to model such heterogeneous systems.


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In this project, we plan to investigate and develop innovative analysis and verificationtechniques that are directly applicable to general SHS models, while being computationallyscalable.

The first stage of the study entails mostly analytical work: the project aims at generatingresults that are both theoretically formal and computationally attractive.

It will furthermore develop dedicated software for the analysis of SHS.

The theoretical and computational outcomes will be tested in or applied to a number ofstudies, in particular to models drawn from Biology.

This latter stage will thus involve the collaboration with researchers from the ComputerScience or the cooperation with experimentalists from the Life Sciences.

Hierarchical and hybrid control of railway systems

prof.dr.ir. B. De Schutter, dr.ir. T.J.J. van den BoomProjectleader:Y. Wang, BScPhD students:

DescriptionThe general goal of this research is to build a hierarchical and hybrid model of railway trafficsystem and to design new optimization and control approach to enhance the safety, efficiency,punctuality of railway systems. First, the hybrid model for single train operation will be built,and the optimization and control methods will be applied, such as model predictive control.Second, the hierarchical and distributed model for railway system will be built, as well asmulti-level control structure with local agents at the lowest level and higher supervisorycontrol levels.

Identification of enzyme kinetics from dynamic data in large-scale metabolicnetworks

dr.ir. A. AbateProjectleader:

DescriptionMetabolic flux distributions are a result of genetic, transcriptional, and enzyme kineticmechanisms.The identification of steady-state fluxes is a state of the art technique and hasbeen improved significantly using 13C labeling techniques.The next crucial step for a broaderunderstanding of metabolism is to identify in-vivo kinetics. This step faces three mainchallenges: the model for the evaluation contains highly nonlinear functions, the availabledata set contains only a few observations of noisy large-dimensional data, and the data setis extracted from experiments with limited dynamical range.

This work pursues a novel approach based on a decomposition of the problem over thetime- and the concentration-dependent domain. We resort to a class of dynamical modelsknown as piecewise affine (PWA), a subclass of the hybrid systems framework, which iswidely investigated, recently used in systems biology studies, and prone to formalmathematical analysis.

The approach is scalable and is to be applied to larger, realistic metabolic networks. Anexample from Penicillium chrysogenum is under study and leverages data provided bybiologists. The project is in collaboration with dr. A. Wahl from the Bioprocess Technologygroup (Prof. Sef Heijnen) in the Department of Biotechnology.



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prof.dr. R. BabuškaProjectleader:dr. G.A.D. LopesParticipants:Delft University of TechnologySponsored by:









prof.dr. R. BabuškaProjectleader:dr. G.A.D. LopesParticipants:E. Najafi, MScPhD students:

DescriptionDesigning motion controllers for ground robots that need to traverse unstructured terrainsis a challenging problem. This is due to the fact that such controllers should able to copewith modeled and unmodeled situations. For example, a mobile robot should be able toexecute different tasks such as walking, jumping, running, going up stairs, in different typesof terrain. This class of problems cannot be solved by linear controllers and nonlinearcontrollers must be used. In this framework each task requires a specialized nonlinearcontroller. A supervisory mechanism is then needed to compose the specialized controllers.This is called sequential composition of controllers and such an approach requires asupervisor whose task is to switch between the controllers in appropriate way. In theformulation of sequential composition of controllers, when the system reaches its goal whichhas been designed to lie inside the domain of attraction, a transition event occurs betweendiscrete supervisor states.

This project explores automatic synthesis of composable controllers and of the supervisor.Some challenges are: 1) Describing the domain of attraction for each controller, particularlyfor nonlinear controllers; 2) Describing the goal set for each controller; 3) Solving the problemof when the desired goal does not lie within the domain of attraction of any controller; 4)


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Solving the problem of when there is no intersections between the domains of attraction ofthe controllers; 5) Employ model based and learning approaches to enlarge the domains ofattraction.


Model predictive control for discrete-event systems


DescriptionModel predictive control (MPC) is a very popular controller design method in the processindustry. An important advantage of MPC is that it allows the inclusion of constraints on theinputs and outputs. Usually MPC uses linear discrete-time models. In this project we extendMPC to a class of discrete-event systems. Typical examples of discrete-event systems are:flexible manufacturing systems, telecommunication networks, traffic control systems,multiprocessor operating systems, and logistic systems. In general models that describethe behavior of a discrete-event system are nonlinear in conventional algebra. However,there is a class of discrete-event systems - the max-plus-linear discrete-event systems -that can be described by a model that is "linear" in the max-plus algebra.

We have further developed our MPC framework for max-plus-linear discrete-event systemsand included the influences of noise and disturbances. In addition, we have also extendedour results to discrete-event systems that can be described by models in which the operationsmaximization, minimization, addition and scalar multiplication appear, and to discrete-eventsystems with both hard and soft synchronization constraints.

Our current research in this context is focus on developing efficient algorithms

for MPC for the classes of discrete-event systems described above, and on

extending the approach to other classes of discrete-event systems.

Model predictive control for hybrid systems


DescriptionBoth academia and industry have recently directed a considerable amount of research efforton hybrid systems. Hybrid systems typically arise when continuous plants are coupled withcontrollers that involve discrete logic actions. Although hybrid systems are encountered inmany practical situations, up to now most controllers for such systems are designed usingad hoc and

heuristic procedures. Due to the complex nature of hybrid systems, it is infeasible to comeup with generally applicable control design methods. In this project we focus on structuredcontrol design methods for specific classes of hybrid systems that are industrially relevant.These methods will be extensions of the model predictive control (MPC) framework forcontinuous systems, so as to include hybrid systems. The MPC scheme is nowadays verypopular in the oil refining and (petrochemical) process industry and has adequately provedits usefulness in practice. MPC offers attractive features that makes this control approachalso interesting and relevant for extension to hybrid systems. In this project we will develop



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high performance MPC controller design techniques for hybrid systems. Currently, we havealready obtained some initial results on MPC for special subclasses of hybrid systems, viz.piecewise-affine systems and max-plus linear systems. In this project we keep on extendingthese results to other relevant classes of hybrid systems, and we thoroughly investigate andformalize the design process, improve optimization procedures to realize real-timeimplementation, and use the results for practical problems of the partners from industry.

Switched Linear Quadratic Regulator in discrete-time: theory and algorithms

dr.ir. A. AbateProjectleader:NWO, European CommissionSponsored by:

DescriptionThis project studies the discrete-time switched LQR problem based on a dynamicprogramming approach.

We provide an analytical characterization of both the value function and the optimal hybridcontrol strategy of the DSLQR problem. Their connections to the Riccati equation and theKalman gain of the classical LQR problem are also investigated.

The study connects with the problem of stabilizability of switched linear systems, which isachieved by a stationary hybrid-control law that consists of a homogeneous switching-controllaw and a piecewise-linear continuous-control law under which the closed-loop system hasa piecewise quadratic Lyapunov function.

Efficient algorithms are proposed to solve the finite-horizon and infinite-horizon DSLQRproblems, or to provide sub-optimal solutions with proven error bounds.

We are currently looking at theoretical extensions of the project, as well as into practicalapplications (e.g., optimal sensor scheduling).

In collaboration with Dr. W. Zhang (UC Berkeley), Prof. J. Hu (Purdue), and Prof. C. Tomlin(UC Berkeley).

Verification and Control of Stochastic Systems with Applications in PowerNetworks

dr.ir. A. AbateProjectleader:dr. M. ZamaniParticipants:MoVeSSponsored by:

DescriptionThe aim is to propose novel methods for analysis, verification and control of complex, largescale models, under the general framework of stochastic hybrid systems (SHS). SHS allowone to describe the interleaving between continuous and discrete dynamics and the effectof probabilistic uncertainty.

We plan to combine techniques for SHS from the computer science (giving rise to theoremproving and model checking methods) and from systems and control engineering (givingrise to optimal control and randomized techniques).

Fundamental research will be applied to problems in power networks, where SHS arisenaturally: continuous dynamics model the evolution of voltages, frequencies, etc., discretedynamics changes in network topology, and probability the uncertainty about power demandand power supply.


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Identification and estimationWhen an actual plant exists, the problem of developing a model for a model based controlleris addressed primarily based on the signals acquired from the plant to be controlled. In thedevelopment of solutions for such identification problems research is conducted along 3different approaches: First, the intelligent modeling approach. Intelligent methodologiesemploy techniques inspired by the functionality of intelligent biological systems. Second, toimprove the user interaction and performance of identification methods novel techniquesfor specific classes of linear, non-linear and hybrid systems are developed. Third, the keyquestion in identification for control is the development of low order models based on thedesign of appropriate experimental conditions and closed-loop system identificationtechniques. Considering applications with arrays of thousands and thousands of sensors(MEMS) and actuators the analysis paradigm is shifted from centralized processing methodstowards decentralised ones.

Distributed fault tolerant control of network connected systems: anapplication to wind farms

prof.dr.ir. M. VerhaegenProjectleader:dr.ir. J.W. van WingerdenParticipants:P.I. Torres, MScPhD students:

DescriptionThe objective of this research is to develop a new methodology for distributed fault detection,identification and controller reconfiguration for network connected systems with a targetapplication to wind farms. The economical feasibility of the wind energy industry greatlydepends on the reliability and maintainability of new large scale wind parks/farms. Especiallyfor offshore wind farms where the distributed turbines are connected with a wireless networkthe topic of predictive maintenance is crucial in the explosive growth. This proposal goes astep further in terms of scalability and reliability of wind farm control and monitoring.



DescriptionThe trend with offshore wind turbines is to increase the rotor diameter as much as possible.The reason is that the foundation costs of offshore wind turbines amount to a large part ofthe total costs. Therefore designers want to increase the energy yield (which increasesquadratically with the rotor diameter) per wind turbine as much as possible to reduce thecosts

The STW project "Smart Design Technology for Reliable Smart Rotors to make Large ScaleWind Turbines economically attractive (SMART-WIND)" will contribute to the developmentof offshore wind energy by investigating the control of fatigue loads and active damping ofstructural vibrational modes. The proposed way to go is the use of smart dynamic rotorcontrol: every rotor blade will be controlled separately and the properties of each blade willbe altered by making use of distributed control over the blade length. This will be possibleby making use of "Smart" actuators and sensors.



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In this project an innovative approach of model based robust controller design will bedeveloped based on the strong past performance of the members of the DCSC. Thedevelopment of system identification tools for robust controller design will be extendedtowards Linear Parameter Varying (LPV) systems. Further, this fundamental experience willbe combined with the application expertise the DCSC has acquired in vibration reductionusing "Smart" materials.

Adaptive optics for optical scanning microscopy

Prof.Dr.sc.techn G. Schitter, prof.dr.ir. M. VerhaegenProjectleader:H.W.Yoo, MScPhD students:STWSponsored by:

DescriptionThis Ph.D. project is a part of the Integrated Smart Microscopy (ISM) project, amultidisciplinary project collaborated with multiple academical and industrial groups. Theindustrial partner are Flexible Optical BV (also known as OKO technologies), ScientificVolume Imaging BV, and Leica Microsystems BV.The academic partners are Delft Universityof Technology and Erasmus MC.

The ISM project aims to develop an integrated smart confocal microscope for live cell imaging,which combines adaptive optics in the imaging path with adaptive postprocessing of theresulting 3D image data. Objective of this PhD project is to integrate prediction and controldesign methodologies in optimizing the overall performance of the new microscope system,in terms of resolution as well as product complexity and costs. In addition to investigatingthe optimal size, location of the type of sensors and actuators, we also aim to achieve higheroverall imaging performance by optimizing the tradeoff between feedback and postprocessing.

During the past few decades, the optical microscopy techniques have achieved significantimprovements in terms of spatial resolutions. For the most biological samples, however,even the diffraction limited resolution is hardly obtained due to various aberrations due tomisalignment in microscope and sample induced aberrations. In this regards, adaptive optics,which actively compensate for wavefront distortions as has been demonstrated in high-endtelescopes, has recently attracted much attention as a promising approach to obtain neardiffraction limited performance in the above mentioned applications.

At DCSC, various methodologies have been investigated to correct aberrations in variousoptical systems such as telescope and microscopes.[1,2] As an extension, fast and robustadaptive optics systems for commercial confocal microscopy are developed to achieve areal time sharp image over a wide field of view.

Advanced Autonomous Model-Based Operation of Industrial ProcessSystems

dr.ir. X.J.A. BomboisProjectleader:dr.ir. J.H.A. Ludlage, dr.ir. A. MesbahParticipants:European Union via the Seventh Framework Programme for research andtechnological development (FP7).

Sponsored by:

DescriptionThis project is a joint endeavor of an international consortium of industrial and academicpartners. Academic partners are Delft University of Technology (The Netherlands), Eindhoven


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University of Technology (The Netherlands), RWTH Aachen (Germany) and KTH Stockholm(Sweden).The industrial partners are ABB (Sweden), Boliden (Sweden) and SASOL (SouthAfrica).

The cost related to the industrial implementation of current model-based operation supportsystems, like Model Predictive Control (MPC), Real-Time Optimization (RTO) and soft-sensorsfor large-scale complex dynamic processes are currently very high. Moreover it is widelyrecognized that the life-time performance of these systems is rather limited, particularly dueto the fact that the underlying dynamic models need to be adapted/calibrated regularly,requiring dedicated measurement campaigns executed by highly specialized engineers.Given the importance of increasing demands on economic and sustainable process operation,there is a strong need to reduce the costs and increase the performance of model-basedoperation support systems. Therefore in this project a model-based operation supporttechnology is developed that enables control and model calibration at a considerable higherlevel of autonomy than currently possible. The technology to be developed operates on thebasis of the least costly principle.The influence of the invasive testing on process’ operationand economics will be minimised, to the extent possible given the necessary accuracy ofthe resulting identified model. Moreover all decisions are based on an economic trade-offbetween process operation costs and benefits. This operation support system should beable to optimise plant performance under varying operational conditions and adapting tochanging circumstances.

Advanced monitoring of railway infrastructure

prof.dr.ir. B. De Schutter, prof.dr. R. BabuškaProjectleader:ir. K.A.J. VerbertPhD students:STW, ProrailSponsored by:

DescriptionPrevention of disruptions and minimization of costs are of paramount importance for railwayinfrastructure managers like ProRail in order to guarantee robust performance of the railwaynetwork and to satisfy requirements from customers and government. Therefore, ProRailneeds an information and monitoring system that can detect, localize, and diagnosedisruptions and emergent problems in a fast and efficient way, and that can proposepreventive maintenance, repair, or replacement actions. In this way, effects of incidents anddisturbances will eventually be minimized and predictive repair or maintenance actions canbe optimized, resulting in minimum disruptions and costs.Various measurement and detectionmethods have been employed and new technologies are being developed to monitor thecondition of the railway infrastructure. Currently, a large amount of measurement andmanagement data are available at different sources. To make use of all relevant availabledata an integrated decision support system is therefore desired. Such a system should beintelligent and it should make use of the increasing number of sensing, measuring,communication, and control equipment present in today's railway infrastructure.

This project will develop new, intelligent, systematic, efficient, and robust methods formonitoring of railway infrastructure, i.e., methods that are continuously fed with new datacollected from the various measurement units in the railway network and that continuouslymonitor these data and raise an alarm as soon as an actual or emergent problem is detected.The main challenges to be addressed are increasing the reliability, efficiency, robustness,and scope (both with respect to amounts and types of data used, missing data, and typesof properties being monitored) of the monitoring process. To this aim we will combinestate-of-the-art information fusion methods with new (possibly probabilistic) models for the



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dynamics and evolution of tracks and trains, for degradation, and for faults, as well asadvanced fault diagnosis and detection methods, statistical analysis, and risk managementmethods. The innovative combination and integration of Artificial Intelligence (AI) methods(such as neural networks, fuzzy logic, and learning) with model-based methods will provideadditional levels of efficiency and scope that cannot be obtained by a purely AI or a purelymodel-based approach. The project will yield efficient and effective methods for the quickdetection, diagnosis, and localization of

disruptions as well as for the determination of preventive and corrective (maintenance orrepair) actions to deal with these problems.



DescriptionAn ongoing trend in wind turbine development is the increase in rotor size. These largerotors inherently become more flexible and introduce more interaction between blades andtower. Several new technologies have been conceived to reduce loads on these future windturbines. Among these are individual pitch control (IPC) and the smart rotor, where distributedtrailing edge flaps are used to influence the lift locally. To allow effective control of fatigueand extreme loads, new measurement techniques are being developed such as LIDAR andlocal flow measurements. Such measurement techniques may allow a degree of feed-forwardcontrol by anticipating wind disturbances.





Major improvements in resolution are expected with the joint optimization approach, inparticular with the aspects of (i) the use of AO wavefront sensor signal data and deformablemirror signal data as input to post-facto reconstruction and (ii) introducing known phase


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aberrations during the real-time correction with the AO system to improve the performanceof post-facto reconstruction, in particular of phase-diversity algorithms. Moving towards anoverall real-time system, (iii) the

feedback of wavefront aberration information deduced by post-facto reconstruction into theadaptive optics system is also a very promising aspect. Furthermore, important issues likeadaptivity with respect to the time-variant turbulence statistics and the use of robust estimationtools taking into account the uncertainty in the point spread function will be addressed inthis research.


Least costly identification experiment for control

prof.dr.ir. P.M.J. Van den Hof (Paul),Projectleader:dr.ir. X.J.A. Bombois, M. Gevers (Université Catholique de Louvain, Belgium),G. Scorletti (Université de Caen, France), H. Hjalmarsson (KTH, Sweden),M. Barenthin (KTH, Sweden), M. Gilson (CRAN, France)

Participants:

DescriptionModel-based control has nowadays reached many industrial sectors (chemical industry,high-tech manufacturing industry,...) as a crucial technology in realizing optimal processoperation. However, the development of model-based control is still restrained by variousopen issues in control and system

theory. In most of these issues, the harmonious interaction between system identificationand robust control design is very important. Since the beginning of the nineties, importantsteps have been taken towards this harmonious interaction. Indeed, it is now possible, givena model and its related uncertainty as delivered by system identification, to check whethera controller

meets the robust performance requirements. However, until very recently, there was still acomplete lack of results allowing the design of robust controllers based on cheap andplant-friendly identification. Indeed, until then, very few attention had been devoted on thechoice of the data used to identify the model and its uncertainty region and the lack of clearguidelines for the choice of these data generally lead to identification experiments that weremore expensive than actually necessary, i.e. the identified uncertainty region was either toolarge (and thus unusable) or smaller than strictly necessary for the required level ofperformance. Knowing that the generation of informative data for an identification experimentis the most expensive step of the whole robust control design procedure, the related economicloss could be very important. Based on these considerations, a brandnew line of researchhas recently been defined. This research aims at developing tractable techniques for anoptimal design of the identification experiment. In particular, the objective is to determinethe least costly identification experiment that delivers sufficient information on the true systemdynamics (i.e. that delivers a model with a sufficiently small uncertainty region) for the designof a robust controller with a satisfactory performance.



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Objectives of this project are:• Set-up of a state-of-the-art virtual simulation environment that models the dynamics

of the wind farm on a time-scale appropriate for real-time control.• Optimize the energy production by the development of a distributed controller, taking

the global (spatial) changes in the wind profile into account.• Development of novel system identification techniques and adaptive control strategies

for nonlinear/distributed systems. This enables taking into account changes in thedynamics of the wind turbine system due to wear and tear or changing wind profiles,and adapting the controller accordingly: the data-driven control methodology.

• The methodology is evaluated on a number of challenging load cases and faultscenarios. In which the effectiveness of the proposed approach is presented andcomputational aspects are investigated.

Smart microscopy of biological tissues

prof.dr.ir. M. VerhaegenProjectleader:J. Antonello, MScPhD students:STWSponsored by:

DescriptionMicroscopy has become increasingly more important in biological and biomedical work.Thisis to a great extent due to the development of advanced imaging methods such as confocalmicroscopy and multi-photon excitation microscopy that provide 3-D imaging in (opticallythick) specimens. At present, multi-photon excitation microscopy is the technique of choicefor high-resolution in-vivo imaging. Unfortunately, the use of these techniques is seriouslyhampered by specimen-induced aberrations that result in reduced depth penetration, lossof spatial resolution, and increased phototoxicity.


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Current implementations of adaptive optics (AO) provide evidence that AO can significantlyimprove image quality, depth penetration, and spatial resolution while reducing phototoxicityin scanning microscopy. However, severe speed limitations render them impractical forreal-life applications. Here, we will focus on the development of fast, active compensationmethods for specimen-induced wavefront aberrations. High compensation speeds will berealized by using adaptive optics in combination with smart predictive algorithms that takeinto account all system properties including the scanning nature of the acquisition, thedynamic properties of the deformable mirror based AO and the nature of the opticaloptimization. To realize the above, academic experts in the area of advanced microscopy(Molecular Biophysics group), adaptive optics (Leiden Observatory group) and advancedcontrol systems (Delft Center for Systems and Control) will closely collaborate. The team isfurther strengthened by the involvement of relevant industrial partners.

The method will be validated in tissue imaging experiments including in-vivo imaging of skin,in-vivo tumour mouse models and isolated arteries. The latter part of the project will becarried out in collaboration with (bio)medical groups.

Intelligent control

Ant Colony Optimization for Dynamic Traffic Routing

prof.dr.ir. B. De Schutter, prof.dr. R. BabuškaProjectleader:Z. Cong, MScPhD students:

DescriptionAnt Colony Optimization (ACO), in Swarm Intelligence methods, refers to an optimizationtechnique of mimicking the intelligent collective behavior of groups of ants that may inthemselves have only very limited intellectual capabilities. The class of ACO algorithms hasproven to be very powerful optimization heuristic of solving combinatorial optimizationproblems.

In this project, we investigate the use of the ACO algorithm for dynamic traffic routingproblems. Because ants and vehicles are similarly individual moving agents in networks,we use ants to assist to (re)direct traffic at junctions in a traffic network corresponding to theevolving traffic conditions as time progresses. However, the standard ACO algorithm is notcapable of solving the routing optimization problem aimed at the system optimum, which isvery important in traffic system, and therefore a new ACO algorithm is developed to achievethe goal of finding the optimal traffic assignment in the network.


prof.dr. R. Babuška, prof.dr.ir. B. De SchutterProjectleader:dr. G.A.D. LopesParticipants:SenterNovemSponsored by:

DescriptionDesign of a mechatronic system consists of many domains: mechanics, electronics,embedded hardware and software, and control. The design begins with the functionaldescription of the mechatronic system. In traditional design approach the design continueswith the mechanical design followed by the electronics design, and then the embeddedhardware and software co-design is completed. Finally the controller which will maintain the



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global behavior of the mechatronic system is designed and the control code is embeddedinto the system whose body is almost completed before control design phase.

What we want to achieve is a new design methodology for the design of mechatronic systemswhere the four domains: mechanics, electronics, embedded hardware and software, andcontrol designs are initiated right after the functional description of the system specifications.In this approach, we will need an integration framework to bring these domains together sothat all these four domains will interact with each other during the whole design process ofthe mechatronic system.




Game-theoretic multi-level methods for the control of large-scale systems

prof.dr.ir. B. De Schutter, prof.dr.ir. J. HellendoornProjectleader:N.B. Groot, MScPhD students:DCSCSponsored by:

DescriptionOne of the major challenges in the control of large-scale intelligent infrastructures such asroad traffic networks is to find an efficient multi-level control scheme in which decisions byseveral controllers on different, mutually interacting control layers are taken into account.

This research project focuses on adopting game-theoretic elements in the modeling ofcommunication and interaction between controllers on the various control levels. Here thetrade-offs due to the multi-objective character of the problems have to be taken into account.Other extensions to consider are the different time scales on which controllers of differentlevels may operate and cases in which the leader does not have perfect information on e.g.,the follower's actions.

A theory that seems to be particularly applicable to tackle these problems is the theory ofreverse Stackelberg games. Reverse Stackelberg games are defined on the basis of ahierarchy between players; a player called the leader acts first by announcing her strategyas a mapping of the follower's decision space into her own decision space, while taking theresponse of the follower into account. The game is flexible in the sense that it may involveany number of leaders and followers, levels (i.e., some players have both a leader and afollower position towards lower and higher levels respectively), number of stages or timeduration, etc.


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Since the problem of finding an optimal strategy for the leader belongs to the realm ofcomposed functions, these problems are known to be very difficult to solve in an analyticway. In this project we will therefore focus on the development of a solid framework formulti-level control based on the reverse Stackelberg game, which is moreover computationallyefficient when applied to real-life problems.


prof.dr. R. Babuška (Robert), dr. G.A.D. Lopes (Gabriel)Projectleader:Delft University of TechnologySponsored by:









dr. G.A.D. Lopes, prof.dr. R. BabuškaProjectleader:E. Najafi, MScPhD students:

DescriptionDesigning motion controllers for ground robots that need to traverse unstructured terrainsis a challenging problem. This is due to the fact that such controllers should able to copewith modeled and unmodeled situations. For example, a mobile robot should be able toexecute different tasks such as walking, jumping, running, going up stairs, in different typesof terrain. This class of problems cannot be solved by linear controllers and nonlinearcontrollers must be used. In this framework each task requires a specialized nonlinearcontroller. A supervisory mechanism is then needed to compose the specialized controllers.This is called sequential composition of controllers and such an approach requires asupervisor whose task is to switch between the controllers in appropriate way. In theformulation of sequential composition of controllers, when the system reaches its goal whichhas been designed to lie inside the domain of attraction, a transition event occurs betweendiscrete supervisor states.



83

This project explores automatic synthesis of composable controllers and of the supervisor.Some challenges are: 1) Describing the domain of attraction for each controller, particularlyfor nonlinear controllers; 2) Describing the goal set for each controller; 3) Solving the problemof when the desired goal does not lie within the domain of attraction of any controller; 4)Solving the problem of when there is no intersections between the domains of attraction ofthe controllers; 5) Employ model based and learning approaches to enlarge the domains ofattraction.


Model-based control

Advanced Autonomous Model-Based Operation of Industrial ProcessSystems

dr.ir. X.J.A. Bombois, dr.ir. J.H.A. LudlageProjectleader:dr.ir. A. MesbahParticipants:European Union via the Seventh Framework Programme for research andtechnological development (FP7).

Sponsored by:

DescriptionThis project is a joint endeavor of an international consortium of industrial and academicpartners. Academic partners are Delft University of Technology (The Netherlands), EindhovenUniversity of Technology (The Netherlands), RWTH Aachen (Germany) and KTH Stockholm(Sweden).The industrial partners are ABB (Sweden), Boliden (Sweden) and SASOL (SouthAfrica).

The cost related to the industrial implementation of current model-based operation supportsystems, like Model Predictive Control (MPC), Real-Time Optimization (RTO) and soft-sensorsfor large-scale complex dynamic processes are currently very high. Moreover it is widelyrecognized that the life-time performance of these systems is rather limited, particularly dueto the fact that the underlying dynamic models need to be adapted/calibrated regularly,requiring dedicated measurement campaigns executed by highly specialized engineers.Given the importance of increasing demands on economic and sustainable process operation,there is a strong need to reduce the costs and increase the performance of model-basedoperation support systems. Therefore in this project a model-based operation supporttechnology is developed that enables control and model calibration at a considerable higherlevel of autonomy than currently possible. The technology to be developed operates on thebasis of the least costly principle.The influence of the invasive testing on process’ operationand economics will be minimised, to the extent possible given the necessary accuracy ofthe resulting identified model. Moreover all decisions are based on an economic trade-offbetween process operation costs and benefits. This operation support system should beable to optimise plant performance under varying operational conditions and adapting tochanging circumstances.


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prof.dr. R. Babuška, prof.dr.ir. B. De SchutterProjectleader:dr. G.A.D. Lopes (Gabriel)Participants:SenterNovemSponsored by:

DescriptionDesign of a mechatronic system consists of many domains: mechanics, electronics,embedded hardware and software, and control. The design begins with the functionaldescription of the mechatronic system. In traditional design approach the design continueswith the mechanical design followed by the electronics design, and then the embeddedhardware and software co-design is completed. Finally the controller which will maintain theglobal behavior of the mechatronic system is designed and the control code is embeddedinto the system whose body is almost completed before control design phase.

What we want to achieve is a new design methodology for the design of mechatronic systemswhere the four domains: mechanics, electronics, embedded hardware and software, andcontrol designs are initiated right after the functional description of the system specifications.In this approach, we will need an integration framework to bring these domains together sothat all these four domains will interact with each other during the whole design process ofthe mechatronic system.




Batch-to-batch learning for process control with application to coolingcrystallization.

prof.dr.ir. P.M.J. Van den HofProjectleader:dr.ir. X.J.A. BomboisParticipants:M. Forgione, MScPhD students:ISPTSponsored by:

DescriptionCrystallization can be defined as phase change in which a solid product is obtained from asolution, melt or a gas. In the industrial practice crystallization is utilized as a separation andpurification step in sectors such as pharmaceutical, food and fine chemicals. The process



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is often operated in batch mode. The solution is loaded into the vessel at the beginning ofa batch and the solid product is removed at the end. The batch time is of the order of

few hours. Multiple batches are performed in order to fulfil the production demand.

In many cases, stringent requirements on the quality of the final product have to be met.The control of a number of variables throughout the batch infuences the quality of the finalproduct to a large extent. For this reason, the industries in the field are interested into theintroduction of advanced automation technology.

Batch operations bring both challanges and opportunities for identification and control. Fromone hand, batch process system are operated over a wide dynamical range. For this reason,strategies based on linearization around a single operating point lead often to poor results.In some cases, first-principles models describing the full nonlinear dynamic behavior areavailable. Unfortunately, these models are often either not very accurate or not suitable forcontrol purposes.

On the other hand, the repetitive nature of batch processing allows the use of iterativetechniques based on the information collected during the previous runs.

In this project we are developing identification and control strategies suitable for industrialbatch processes such as crystallization. We are particularly interested in

• Batch-to batch Identification & Optimization• Iterative Learning Control• Experiment Design

We are collaborating with several industrial partners such as DSM, Albemarle,

Frieslandcampina, MSD and DotX Control Solutions.

Distributed control of large-scale multi-class traffic networks

prof.dr.ir. B. De Schutter, prof.dr.ir. J. HellendoornProjectleader:S. Liu, MScPhD students:

DescriptionMulti-class traffic models describe traffic network based on different classes of vehicles,such as trucks, vans, and cars. In comparison with single-class models, this leads torepresentations that are closer to real traffic networks . Applying multi-class traffic modelsin traffic management therefore offers promising prospects of improving the control efficiency.

In this project, we develop multi-class traffic flow models and multi-class emission models.These multi-class traffic models are used in on-line model-based control approach (ModelPredictive Control). We integrate multi-class traffic flow models with multi-class emissionmodels and use them to find a balanced trade-off between total time spent and totalemissions. We investigate the performance of both fast, first-order models (FASTLANE)and slower, more accurate models (METANET).

As a next step, Distributed Model Predictive Control will be applied in the multi-class trafficcontrol approach, to improve the computation speed and refine the control performance. Inaddition, we will also consider robust control.


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Major improvements in resolution are expected with the joint optimization approach, inparticular with the aspects of (i) the use of AO wavefront sensor signal data and deformablemirror signal data as input to post-facto reconstruction and (ii) introducing known phaseaberrations during the real-time correction with the AO system to improve the performanceof post-facto reconstruction, in particular of phase-diversity algorithms. Moving towards anoverall real-time system, (iii) the feedback of wavefront aberration information deduced bypost-facto reconstruction into the adaptive optics system is also a very promising aspect.Furthermore, important issues like adaptivity with respect to the time-variant turbulencestatistics and the use of robust estimation tools taking into account the uncertainty in thepoint spread function will be addressed in this research.


i-OCT (Optical coherence tomography)

prof.dr.ir. M. VerhaegenProjectleader:dr. J. KalkmanParticipants:H.R.G.W. VerstraetePhD students:AgentschapNLSponsored by:

DescriptionOptical coherence tomography (OCT) is a high resolution imaging technique that can take3D images of tissue. OCT is similar to ultrasound in that it measures the echo of light reflectedfrom tissue, however it uses interferometry to determine the extremely small time-of-flightof light reflected from a few millimeters depth.

OCT technology can be used to form high resolution depth scans of biological specimens,such as the retina (see figure) or arterial all, and plays a key role in early detection ofanomalies in vision, heart conditions, etc. The spatial resolution enables an accurate (up to4-10 micron) imaging of the biological layers up to few millimeters deep. However due toaberrations induced by the imaging optics or the specimen, the lateral resolution is limited.

In this project we develop adaptive optics technology that can compensate for the wavefrontaberrations and yield high resolution images both axially and laterally, but at the same time



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result into a cost-effective hardware design.This leads to a multi-criteria optimization problemwhere from the beginning the presence of a feedback loop is taken into consideration in thedesign of the imaging instrument.

Model predictive control for hybrid systems


DescriptionBoth academia and industry have recently directed a considerable amount of research efforton hybrid systems. Hybrid systems typically arise when continuous plants are coupled withcontrollers that involve discrete logic actions. Although hybrid systems are encountered inmany practical situations, up to now most controllers for such systems are designed usingad hoc and heuristic procedures. Due to the complex nature of hybrid systems, it is infeasibleto come up with generally applicable control design methods.

In this project we focus on structured control design methods for specific classes of hybridsystems that are industrially relevant. These methods will be extensions of the modelpredictive control (MPC) framework for continuous systems, so as to include hybrid systems.The MPC scheme is nowadays very popular in the oil refining and (petrochemical) processindustry and has adequately proved its usefulness in practice. MPC offers attractive featuresthat makes this control approach also interesting and relevant for extension to hybrid systems.In this project we will develop high performance MPC controller design techniques for hybridsystems.

Currently, we have already obtained some initial results on MPC for special subclasses ofhybrid systems, viz. piecewise-affine systems and max-plus linear systems. In this projectwe keep on extending these results to other relevant classes of hybrid systems, and wethoroughly investigate and formalize the design process,improve optimization proceduresto realize real-time implementation, and use the results for practical problems of the partnersfrom industry.

Multi-level and multi-agent control of intermodal container transport systems

prof.dr.ir. B. De Schutter (Bart)Projectleader:Dr. R. R. NegenbornParticipants:L. Li, MScPhD students:CSC , STWSponsored by:

DescriptionDue to the increasing demand for container transport in national and international trade,hinterland haulage among major deep-sea ports and the containers' original/final inlandlocations has become an important component in modern logistic systems. Intermodalcontainer transport integrates the use of different modalities (e.g., trucks, trains, barges,etc.) during the container delivery process to improve the efficiency and sustainability ofhinterland haulage. One crucial challenge for hinterland haulage is to provide reliable transportservices in a cost and time-efficient way with the existing transport infrastructures whileconsidering physical capacities and environmental regulations.

The research problem of this project is to investigate “how containers can be transportedefficiently over intermodal container transport networks including the Port of Rotterdam andhinterland terminals?”. The proposed research approach is to improve the operational


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performance of the intermodal container transport network via better real-time coordination.To implement the proposed research approach, two main tasks are considered:

(1) In the modeling task, dynamic intermodal container transport network models aredeveloped. The models capture the characteristics of intermodal container transport, e.g.,modality changes at intermodal terminals, due time requirements for container transport,capacity constraints of terminals and transport connections, etc.

(2) In the control task, the main work is to develop real-time and coordinated intermodalcontainer flow assignment methods. A distributed and coordinated model predictive controlmethodology will be applied for real-time and coordinated container flow assignments overintermodal container transport networks while considering capacity constraints, modal splittargets, information privacy, etc.

This is a joint DCSC-MTT project.

Publications

Book chapters/parts

Busoniu, IL, Lazaric, A, Ghavamzadeh, M., Munos, R, Babuska, R & De Schutter, B (2012).Least-Squares Methodes for Policy Iteration. In M. Wiering & M. van Otterlo (Eds.),Reinforcement Learning (pp. 75-110). Springer.

Corno, M, Wingerden, JW van & Verhaegen, M (2012). Linear Parameter-Varying SystemIdentification: The Subspace Approach. In D Alberer, H Hjalmarsson & L del Re (Eds.),Identification for Automotive Systems (Lecture Notes in Control and Information Sciences,418) (pp. 53-66). London: Springer.

De Schutter, B, Ploeg, J, Baskar, LD, Naus, G & Nijmeijer, H. (2012). Hierarchical, Intelligentand Automatic Controls. In A. Eskandarian (Ed.), Handbook of Intelligent Vehicles (pp.81-116). London: Springer.

Kalbasenka, AN, Huesman, AEM & Kramer, HJM (2012). Advanced model-based recipe control.In A. Chianese & H.J.M. Kramer (Eds.), Industrial crystallization process monitoring andcontrol (pp. 161-174). Weinheim Germany: Wiley-VCH Verlag & Co. KGaA.

Kalbasenka, AN, Huesman, AEM & Kramer, HJM (2012). Advanced recipe control. In A.Chianese & H.J.M. Kramer (Eds.), Industrial crystallization process monitoring and control(pp. 139-159). Weinheim Germany: Wiley-VCH Verlag & Co. KGaA.

Kalbasenka, AN, Huesman, AEM & Kramer, HJM (2012). Basic recipe control. In A. Chianese& H.J.M. Kramer (Eds.), Industrial crystallization process monitoring and control (pp.105-125). Weinheim Germany: Wiley-VCH Verlag & Co. KGaA.

Kalbasenka, AN, Huesman, AEM & Kramer, HJM (2012). Model predictive control. In A. Chianese& H.J.M. Kramer (Eds.), Industrial crystallization process monitoring and control (pp.185-201). Weinheim Germany: Wiley-VCH Verlag & Co. KGaA.

Stankova, K (2012). On Dynamic Games in the European Electricity market. In S.P. Sethi (Ed.),Industrial Engineering: Innovative Networks, Annals of Industrial Engineering 2011 (pp.191-199). London: Springer.

Tarau, A, De Schutter, B & Hellendoorn, J (2012). Hierarchical model-based control forautomated baggage handling systems. In R Johansson & A Rantzer (Eds.), DistributedDecision Making and Control (Lecture Notes in Control and Information Sciences, ISSN:0170-8643) (pp. 359-386). London: Springer.

Tejada, A., Dekker, AJ den & Van den Hof, PMJ (2012). A matlab-based dynamic TEM simulator.In R Doornbos & S van Loo (Eds.), From Scientific Instrument to Industrial Machine (pp.38-42). Dordrecht: Springer.



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Verdult, V & Verhaegen, M (2012). Reducing the Dimensions of Data Matrices in LPV SubspaceIdentification. In P Lopes dos Santos, TP Azevedo Perdicoulis, C Novara, JA Ramos &DE Rivera (Eds.), Linear parameter-varying system identification (Advanced Series inElectrical and Computer Engineering, 14) (pp. 133-166). World Scientific.

Wingerden, JW van & Verhaegen, M (2012). Subspace identification of MIMO LPV systems.In P Lopes dos Santos, TP Azevedo Perdicoulis, C Novara, JA Ramos & DE Rivera(Eds.), Linear parameter-varying system identification (Advanced Series in Electrical andComputer Engineering, 14) (pp. 167-200). World Scientific.

International journal papers

Abate, A, Hillen, RC & Wahl, SA (2012). Piecewise affine apporximations of fluxes and enzymekinetics from in vivo 13C labeling experiments. International Journal of Robust andNonlinear Control, 22, 1120- 1139.

Abate, A, Vincent, S, Dobbe, R, Silletti, A, Master, N, Axelrod, JD & Tomlin, C.J. (2012). Amathematical model to study the dynamics of epithelial cellular networks. IEEE - ACMTransactions on Computational Biology and Bioinformatics, 9(6), 1607-1620.

Adam, S, Busoniu, L & Babuska, R (2012). Experience replay for real-time reinforcementlearning control. IEEE Transactions on Systems, Man and Cybernetics, Part C:Applications and Reviews, 42(2), 201-212.

Balandat, M., Zhang, W & Abate, A (2012). On infinite horizon switched LQR problems withstate and control constraints. Systems & Control Letters, 61(4), 464-471.

Barlas, A, Wingerden, JW van, Hulskamp, AW, Kuik, GAM van & Bersee, HEN (2012). Smartdynamic rotor control using active flaps on a small-scale wind turbine: aerolastic modelingand comparison with wind tunnel measurements. Wind Energy, 1-15.

Baskar, LD, De Schutter, B & Hellendoorn, H (2012).Traffic management for automated highwaysystems using model-based predictive control. IEEE Transactions on IntelligentTransportation Systems, 13(2), 838- 847.

Bazanella, A.S, Bombois, XJA & Gevers, M (2012). Necessary and sufficient conditions foruniqueness of the minimum in Prediction Error Identification. Automatica, 48, 1621-1630.

Bombois, XJA & Scorletti, G (2012). Design of least costly identification experiments.The mainphilosophy accompanied by illustrative examples. Journal Européen des SystèmesAutomatisés, 46(6-7), 587-610.

Boom, AJJ van den & De Schutter, B (2012). Modeling and control of switching max-plus-linearsystems with random and deterministic switching. Discrete Event Dynamic Systems:theory and applications, 22(3), 293-332.

Brinkman, EK, Schipper, K, Bongaerts, N, Voges, MJ, Abate, A & Wahl, SA (2012). A toolkitto enable hydrocarbon conversion in aqueous environments. Journal of VisualizedExperiments, 1-13.

Bron, EE, Tiel, J, Smit, H, Poot, DHJ, Niessen, WJ, Krestin, GP, Weinans, H, Oei, E, Kotek, G& Klein, S. (2012). Image registration improves human knee cartilage T1 mapping withdelayed gadolinium-enhanced MRI of cartilage (dGEMRIC). European Radiology: journalof the European Congress of Radiology, 1-7.

Cerone, V, Piga, D & Regruto, D (2012). Bounded error identification of Hammerstein systemsthrough sparse polynomial optimization. Automatica, 48, 2693-2698.

Corno, M, Gerard, M, Verhaegen, M & Holweg, EGM (2012). Hybrid ABS control using forcemeasurements. IEEE Transactions on Control Systems Technology, 20(5), 1223-1235.

Dong, J & Verhaegen, M (2012). Identification of fault estimation filter from I/O data for systemswith stable inversion. IEEE Transactions on Automatic Control, 57(6), 1347-1361.


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Dong, J , Verhaegen, M & Gustafsson, F (2012). Robust Fault Isonation With StatisticalUncertainty in Identified Parameters. IEEE Transactions on Signal Processing, 60(10),5556-5561.

Dong, J , Verhaegen, M & Gustafsson, M (2012). Robust fault detection with statistical uncertaintyin identified parameters. IEEE Transactions on Signal Processing, 60(10), 5064-5076.

Dumitrache, DC, De Schutter, B, Huesman, AEM & Dulf, E (2012). Modeling, analysis, andsimulation of a cryogenic distillation process for 13C isotope separation. Journal of ProcessControl, 22(4), 798-808.

Gerald, M, Pasillas-Lepine, W, Vries, EJH de & Verhaegen, M (2012). Improvements to afive-phase ABS algorithm for experimental validation. International Journal of HeavyVehicle Systems, 50(10), 1585-1611.

Gerard, M, Pasillas-Lepine, W, Vries, EJH de & Verhaegen, M (2012). Improvements to ahybridfive-phase ABS algorithm for experimental validation. Vehicle System Dynamics:international journal of vehicle mechanics and mobility, 1-27.

Grondman, I, vaandrager, M, Busoniu, IL, Babuska, R & Schuitema, E (2012). Efficient modellearning methods for actor-critic control. IEEE Transactions on Systems, Man andCybernetics, Part B: Cybernetics, 42(3), 591-602.

Haber, A, Fraanje, PR & Verhaegen, M (2012). Linear computational complexity design ofconstrained optimal ILC. Automatica, 48(6), 1102-1110.

Houtzager, I, Wingerden, JW van & Verhaegen, M (2012). Recursive Predictor-Based SubspaceIdentification With Application to the Real-Time Closed-Loop Tracking of Flutter. IEEETransactions on Control Systems Technology, 20(4), 934-949.

Houtzager, I, Wingerden, JW van & Verhaegen, M (2012). Wind turbine load reduction byrejecting the periodic load disturbances. Wind Energy, may, 1-22.

Kadam, SS, Vissers, JAW, Forgione, M, Geertman, RM, Daudey, P, Stankiewicz, AI & Kramer,HJM (2012). Rapid crystallization process development strategy from lab to industrialscale with pat tools in skid configuration. Organic Process Research and Development,16(5), 769-780.

Khalate, AA, Bombois, XJA, Scorletti, G, Babuska, R, Koekebakker, SH & Zeeuw, W de (2012).A waveform design method for a piezo inkjet printhead based on robust feedforwardcontrol. IEEE Journal of Microelectromechanical Systems, 21(6), 1365-1374.

Khalate, AA, Bombois, XJA, Ye, S, Babuska, R & Koekebakker, SH (2012). Minimization ofcross-talk in a piezo inkjet printhead based on system identification and feedforwardcontrol. Journal of Micromechanics and Microengineering, 22(11), 1-21.

Koepsell, DR & Stankova, K (2012). Non-proliferation regimes, immoral and risky: agame-theoretic approach. International Journal on World Peace, 29(2), 61-81.

Koepsell, DR & Stankova, K (2012). Non-proliferation regimes: immoral and risky. InternationalJournal on World Peace, 29(2), 63-83.

Korkiakoski, V., Keller, C, Doelman, N, Fraanje, PR & Verhaegen, M (2012). Joint optimizationof phase diversity and adaptive optics: demonstration of potential. Applied Optics, 51(1),102-113.

Kulcsar, BA & Verhaegen, M (2012). Robust inversion based fault estimation for discrete-timeLPV systems. IEEE Transactions on Automatic Control, 57(6), 1581-1586.

Li, Y & De Schutter, B (2012). Control of a String of Identical Pool Using Non-Identical FeedbackControllers. IEEE Transactions on Control Systems Technology, 20(6), 1638-1646.

Lin, S, De Schutter, B, Xi, Y & Hellendoorn, H (2012). Efficient network-wide model-basedpredictive control for urban traffic networks. Transportation Research. Part C: EmergingTechnologies, 24, 122-140.



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Massioni, P, Ankersen, F & Verhaegen, M (2012). A matching pursuit algorithm approach tochaser-target formation flying problems. IEEE Transactions on Control SystemsTechnology, 20(2), 513-519.

Mesbah, A, Nagy, ZK, Huesman, AEM, Kramer, HJM & Van den Hof, PMJ (2012). nonlinearmodel-based control of a semi-industrial batch crystallizer using a population balancemodeling framework. IEEE Transactions on Control Systems Technology, 20(5),1188-1201.

Nikacevic, N, Huesman, AEM, Van den Hof, PMJ & Stankiewicz, AI (2012). Opportunities andchallenges for process control in process intensification. Chemical Engineering andProcessing: process intensification, 52(February 2012), 1-15.

Pasillas-Lepine, W, Gerard, M & Loria, A (2012). Design and experimental validation of anonlinear wheel slip control algorithm. Automatica, 48(8), 1852-1859.

Polo, A, Haber, A, Pereira, SF, Verhaegen, MHG & Urbach, HP (2012). An innovative andefficient method to control the shape of push-pull membrance deformable mirror. OpticsExpress, 20(25), 27922-27932.

Stankova, K, Abate, A & Sabelis, M.W. (2012). Irreversible prey diapause as an optimal strategyof a physiologically extended Lotka-Volterra model. Journal of Mathematical Biology, okt,1-28.

Tejada Ruiz, A & Dekker, AJ den (2012). Defocus polar rose estimation method (POEM): afast defocus estimation method for STEM. IEEE Transactions on Instrumentation andMeasurement, 61(10), 2723-2730.

Vitus, MP, Zhang, W, Abate, A, Hu, J & Tomlin, C.J. (2012). On efficient sensor scheduling forlinear dynamical systems. Automatica, 48(8), 2482-2493.

Zegeye, SK, De Schutter, B, Hellendoorn, J, Breunesse, EA & Hegyi, A (2012). A PredictiveTraffic Controller for Sustainable Mobility Using Parameterized Control Policies. IEEETransactions on Intelligent Transportation Systems, 13(3), 1420-1429.

Zhang, W, Hu, J & Abate, A (2012). Infinite-horizon switched LQR problems in discrete time:a suboptimal algorithm with performance analysis. IEEE Transactions on AutomaticControl, 57(7), 1815-1821.

International congress papers

Adzkiya, D, De Schutter, B & Abate, A (2012). Abstraction and verification of autonomousmax-plus-linear systems. In Tariq Samad (Ed.), 2012 American Control Conference (pp.721-726). Montreal, Canada: ACC.

Alirezaei, M, Boom, TJJ van den & Babuska, R (2012). Max-Plus algebra for optimal schedulingof multiple sheets in a printer. In Tariq Samad (Ed.), 2012 American Control Conference(pp. 1973-1978). Montreal, Canada: ACC.

Andrei, RM, Fraanje, PR, Verhaegen, M, Korkiakoski, V., Keller, CU & Doelman, NJ (2012).Bilinear solution to the pase diversity problem for extended objects based on the Bornapproximation. In B.L. Ellenbroek (Ed.), Spie Astronomical Telescopes + Instrumentation2012 (pp. 1-11). Amsterdam: Spie.

Andrei, RM, Smith, S, Fraanje, PR, Verhaegen, M, Korkiakoski, V., Keller, CU & Doelman, N(2012). Linear analytical solution to the pase diversity problem for extended objects basedon the Born approximation. In B.L. Ellerbroek, E. Marchetti & J-P Véran (Eds.), SpieAstrononical Telescopes + Instrumentation 2012 (pp. 1-9). Amsterdam: Spie.

Antonello, J, Fraanje, PR, Song, H, Verhaegen, M, Gerritsen, H, Keller, CU & Werkhoven, Tvan (2012). Data driven identification and aberration correction for model based sensorlessadaptive optics. In F Berghmans, R Burgess, J Popp & P Hartmann (Eds.), SPIE PhotonicsEurope 2012 (pp. 1-9). Brussels, Belgium: SPIE.


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Bernhammer, LO, Teeuwen, SPW, Breuker, R de, Solingen, E van & Veen, GJ van der (2012).Performance optimization and gust load alleviation of a UAV wind using variable camber.In s.n. (Ed.), ICAST2012: 23rd International conference on adaptive structures andtechnologies (pp. 1-12). s.l.: s.n..

Boom, AJJ van den, Kersbergen, B & De Schutter, B (2012). Structured modeling, analysisand control of complex railway operations. In J.A. Farrell (Ed.), 51st IEEE Conferenceon Decision and Control (pp. 7366- 7371). Maui, USA: IEEE.

Burger, M, De Schutter, B & Hellendoorn, J (2012). An improved method for solving micro-ferryscheduling problems. In N Geroliminis & M Bierlaire (Eds.), 1st European Symposiumon Quantitative Methods in Transportation Systems (pp. 1-8). Lausanne, Switzerland:École polytechnique fédérale de Lausanne.

Burger, M, De Schutter, B & Hellendoorn, J (2012). Micro-Ferry Scheduling Problem withCharging and Embarking Times. In T Stoilov (Ed.), 13th IFAC Symposium on Control inTransportation Systems (pp. 164- 171). Bulgaria: IFAC.

Burger, M, De Schutter, B & Hellendoorn, J (2012). Micro-Ferry scheduling problem with timewindows. In Tariq Samad (Ed.), 2012 American Control Conference (pp. 3998-4003).Montreal, Canada: ACC.

Cerone, V, Piga, D & Regruto, D (2012). Bounded-error identification of linear systems withinput and output backlash. In J. Schoukens (Ed.), Sysid 2012. 16th IFAC symposium onsystem identification. (pp. 256-261). Brussels, Belgium: IFAC.

Cerone, V, Piga, D & Regruto, D (2012). FIR approximation of linear systems from quantizedrecords. In J. Schoukens (Ed.), Sysid 2012. 16th IFAC symposium on system identification(pp. 1179-1184). Brussels, Belgium: IFAC.

Cerone, V, Piga, D & Regruto, D (2012). Polytopic outer approximations of semialgebraic sets.In J.A. Farrell (Ed.), 51st IEEE Conference on Decision and Control (pp. 7793-7798).Maui, USA: IEEE.

Cerone, V, Piga, D & Regruto, D (2012). Robust pole placement for plants with semialgebraicparametric uncertainty. In Tariq Samad (Ed.), 2012 American Control Conference (pp.5240-5245). Montreal, Canada: ACC.

Cerone, V, Piga, D & Toth, R (2012). Fixed order LPV controller design for LPV models ininput-output form. In J.A. Farrell (Ed.), 51st IEEE Conference on Decision and Control(pp. 6297-6302). Maui, USA: IEEE.

Cerone, V, Piga, D, Regruto, D & Berehanu, S (2012). LPV identification of the glucose-insulindynamics in Type I diabetes. In J. Schoukens (Ed.), 16th IFAC symposium on systemidentification (pp. 1179-1184). Brussels, Belgium: IFAC.

Cerone, V, Piga, D, Regruto, D & Toth, R (2012). Input-output LPV model identification withguaranteed quadratic stability. In J Schoukens (Ed.), 16th IFAC symposium on systemidentification (pp. 1767-1772). Brussels, Belgium: IFAC.

Cerone, V, Piga, D, Regruto, D & Toth, R (2012). Minimal LPV state-space realization drivenset- membership identification. In Tariq Samad (Ed.), 2012 American Control Conference(pp. 3421-3426). Montreal, Canada: ACC.

Corno, M, Bhatt, N & Verhaegen, M (2012). An efficient control oriented modeling approachfor Lithium Ion cells. In Tariq Samad (Ed.), 2012 American Control Conference (pp.4733-4738). Montreal, Canada: ACC.

D'Innocenzo, A, Abate, A & Katoen, J.P. (2012). Robust PCTL model checking. In T Dang & IMitchell (Eds.), Hybrid Systems: Computation and Control 2012 (pp. 275-285). Beijing,China: HSCC 2012.

Dankers, AG, Van den Hof, PMJ, Heuberger, PSC & Bombois, XJA (2012). Dynamic NetworkIdentification Using the Direct Prediction-Error Method. In J.A. Farrell (Ed.), 51st IEEEConference on Decision and Control (pp. 901-906). Maui, USA: IEEE.



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Dankers, AG, Van den Hof, PMJ, Heuberger, PSC & Bombois, XJA (2012). Dynamic networkstructure identification with prdiction error methods - basic examples. In J Schoukens &R Bitmead (Eds.), 16st IFAC Symposium on System Identification (pp. 876-881). Brussels:IFAC.

Doan, MD, Keviczky, T & De Schutter, B (2012). Application of distributed and hierarchicalmodel predictive control in hydro power valleys. In M Lazar & F Allgower (Eds.), 4th IFACNonlinear Model Predictive Control Conference (pp. 375-383). Noordwijkerhout: IFAC.

Esmaeil Zadeh Soudjani, S & Abate, A (2012). Higher-Order Approximations for Verification ofStochastic Hybrid Systems. In Supratik Chakraborty & Madhavan Mukand (Eds.), ATVA2012 (pp. 416-434). Thiruvananthapuram: s.n..

Esmaeil Zadeh Soudjani, S & Abate, A (2012). Probabilistic Invariance of MixedDeterministic-Stochastic Dynamical Systems. In Thao Dang & Ian Mitchell (Eds.), HSCC2012 (pp. 207-216). Beijing: ACM.

Essen, GM van, Hof, PMJ van den & Jansen, JD (2012). A two-level strategy to realize life-cycleproduction optimization in an operational setting. In s.n. (Ed.), SPE intelligent energyinternational (pp. 1-11). London: Society of Petroleum Engineers.

Forgione, M, Mesbah, A, Bombois, XJA & Van den Hof, PMJ (2012). Batch-to-Batch Strategiesfor Cooling Crystallization. In J.A. Farrell (Ed.), 51st IEEE Conference on Decision andControl (pp. 6364-6369). Maui, USA: IEEE.

Forgione, M, Mesbah, A, Bombois, XJA & Van den Hof, PMJ (2012). Iterative learning controlof supersaturation in batch cooling crystallization. In Tariq Samad (Ed.), 2012 AmericanControl Conference (pp. 6455-6460). Montreal, Canada: ACC.

Gebraad, PMO, Wingerden, JW van & Verhaegen, M (2012). Sparse Estimation forPredictor-Based Subspace Identification of LPV Systems. In J Schoukens (Ed.), 16thIFAC Symposium on System Identification (pp. 1749-1754). Brussels, Belgium: IFAC.

Grondman, I, Busoniu, IL & Babuska, R (2012). Model Learning Actor-Critic Algorithms:Performance Evaluation in a Motion Control Task. In J.A. Farrell (Ed.), 51st IEEEConference on Decision and Control (pp. 5272-5277). Maui, USA: IEEE.

Groot, NB, De Schutter, B & Hellendoorn, J (2012). A Full Characterization of the Set of OptimalAffine Solutions to the Reverse Stackelberg Game. In J.A. Farrell (Ed.), 51st IEEEConference on Decision and Control (pp. 6483-6488). Maui, USA: IEEE.

Groot, NB, De Schutter, B & Hellendoorn, J (2012). Achieving system-optimal splitting rates ina freeway network using a reverse Stackelberg approach. In T Stoilov (Ed.), 13th IFACSymposium on Control in Transportation Systems (pp. 132-137). Bulgaria: IFAC.

Groot, NB, De Schutter, B & Hellendoorn, J (2012). Dynamic optimal routing based on a reverseStackelberg game approach. In J Miller (Ed.), 15th International IEEE Conference onIntelligent Transportation Systems (ITSC 2012) (pp. 782-787). Anchorage, USA: IEEE.

Groot, NB, De Schutter, B & Hellendoorn, J (2012). Existence conditions for an optimal affineleader function in the reverse Stackelberg game. In L Lambertini, G Pelloni & E Agliardi(Eds.), 15th IFAC Workshop on Control Applications of Optimization (pp. 56-61). Rimini,Italy: IFAC.

Groot, NB, De Schutter, B & Hellendoorn, J (2012). Reverse Stackelberg games, Part I: Basicframework. In S Bogdan (Ed.), 2012 IEEE International Conference on Control Applications(pp. 421-426). Dubrovnik, Croatia: IEEE.

Groot, NB, De Schutter, B & Hellendoorn, J (2012). Reverse Stackelberg games, Part II: Resultsand Open Issues. In S Bogdan (Ed.), 2012 IEEE International Conference on ControlApplications (pp. 427-432). Dubrovnik, Croatia: IEEE.


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Hajiahmadi, M, De Schutter, B & Hellendoorn, J (2012). Control of Traffic Networks Using theLink Transmission Model and Mixed Integer Linear Programming. In N Geroliminis & MBierlaire (Eds.), 1st European Symposium on Quantitative Methods in TransportationSystems (pp. 1-5). Lausanne, Switzerland: École polytechnique fédérale de Lausanne.

Hajiahmadi, M, De Schutter, B & Hellendoorn, J (2012). Model predictive traffic control: Amixed-logical dynamic approach based on the link transmission model. In T Stoilov (Ed.),13th IFAC Symposium on Control in Transportation Systems (pp. 144-149). Bulgaria:IFAC.

Herpen, RAP van, Oomen, T & Bosgra, OH (2012). Bi-Orthonormal Basis Functions for ImprovedFrequency-Domain System Identification. In J.A. Farrell (Ed.), 51st IEEE Conference onDecision and Control (pp. 3451-3456). Maui, USA: IEEE.

Hidayat, Z, Nunez Vicencio, AA, Babuska, R & De Schutter, B (2012). Identification of distributed-parameter systems with missing data. In S Stjepan Bogdan (Ed.), 2012 IEEE Internationalconference on control applications. Part of 2012 Multi-conference on systems and control(pp. 1014-1019). Dubrovnik, Croatia: IEEE.

Hu, Y & Hellendoorn, J (2012). An approach for traffic networks optimization based on urbanproperties. In Fei-yue Wang & Liuqin Yang (Eds.), 2012 9th ieee international conferenceon networking, sensing and control (pp. 91-96). china: ieee.

Keller, CU, Korkiakoski, V., Doelman, NJ, Fraanje, PR, Andrei, RM & Verhaegen, M (2012).Extremely fast focal-plane wavefront sensing for extreme adaptive optics. In B.L.Ellerbroek, E. Marchetti & Véran J-P(Eds.), Spie Astronomical Telescopes +Instrumentation 2012 (pp. 1-10). Amsterdam: Spie.

Korkiakoski, V., Keller, CU, Doelman, N, Fraanje, PR, Andrei, RM & Verhaegen, M (2012).Experimental validation of optimization concepts for focal-plane image processing withadaptive optics. In B.L. Ellenbroek, E. Marchetti & J-P Véran (Eds.), Spie AstronimicalTelescopes + Instrumentation 2012 (pp. 1- 11). Amsterdam: Spie.

Korkiakoski, V., Venema, L, Agocs, T, Keller, CU, Doelman, N, Fraanje, PR, Andrei, RM &Verhaegen, M (2012). Potential of phase-diversity for metrology of active instruments.In B.L. Ellerbroek, E. Marchetti & J- P Véran (Eds.), Spie Astronimical Telescopes +Instrumentation 2012 (pp. 1-11). Amsterdam: Spie.

Lemmen, BP, Koekebakker, SH, Bosch, PFA van den & Bosgra, OH (2012). ParameterizedIterative Learning Control: Aplication to a wide format inkjet printer. In Tariq Samad (Ed.),2012 American Control Conference (pp. 1961-1966). Montreal, Canada: ACC.

Li, Y & De Schutter, B (2012). A robust feasability problem for the design of a reference governor.In Tariq Samad (Ed.), 2012 American Control Conference (pp. 6745-6750). Montreal,Canada: ACC.

Loenhout, S. van, Boom, AJJ van den, Farahani, SS & De Schutter, B (2012). Model predictivecontrol for stochastic switching max-plus-linear systems. In A. Ramirez (Ed.), Proceedingsof the 11th International Workshop on Discrete Event Systems (WODES 2012) (pp.79-84). Guadalajara, Mexico: WODES2012.

Lopes, GAD, De Schutter, B & Boom, AJJ van den (2012). On the synchronization of cyclicdiscrete-event systems. In J.A. Farrell (Ed.), 51st IEEE Conference on Decision andControl (pp. 5810-5815). Maui, USA: IEEE.

Maestre, JM, Doan, MD, Munoz de la pena, D, Overloop, PJ van, Keviczky, T, Ridao, MA &De Schutter, B (2012). Benchmarking the operation of a hydro power network throughthe application of agent-based model predictive controllers. In R Hinkelmann (Ed.), 10thInternational Conference on Hydroinformatics (pp. 1-8). Hamburg: TuTech Verlag.

Maestre, JM, Raso, L, Overloop, PJ van & De Schutter, B (2012). Distributed tree-based modelpredictive control on an open water system. In Tariq Samad (Ed.), American ControlConference (ACC), 2012 (pp. 1985-1990). Montreal, QC: ACC.



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Mesbah, A, Bombois, XJA, Forgione, M, Ludlage, JHA, Modén, PE, Hjalmarsson, H & Van denHof, PMJ (2012). A Unified Experiment Design Framework for Detection and Identificationin Closed-loop Performance Diagnosis. In J.A. Farrell (Ed.), 51st IEEE Conference onDecision and Control (pp. 2152- 2157). Maui, USA: IEEE.

Mesbah, A, Bombois, XJA, Ludlage, JHA & Van den Hof, PMJ (2012). Experiment design forclosed-loop performance diagnosis. In J Schoukens & R Bitmead (Eds.), 16st IFACSymposium on System Identification (pp. 1341-1346). Brussels: IFAC.

Narasimhan, S & Bombois, XJA (2012). Plant Friendly Input Design for System Identificationin Closed Loop. In J Schoukens (Ed.), 16th IFAC symposium on system identification(pp. 1335-1340). Brussels, Belgium: IFAC.

Nunez, A & De Schutter, B (2012). Distributed Identification of Fuzzy Confidence Intervals forTraffic Measurements. In J.A. Farrell (Ed.), 51st IEEE Conference on Decision and Control(pp. 6995-7000). Maui, USA: IEEE.

Oomen, T, Herpen, RAP van, Quist, S, Wal, M van de, Bosgra, OH & Steinbuch, M (2012).Next- Generation Wafer Stage Motion Control: Connecting System Identification andRobust Control. In Tariq Samad (Ed.), 2012 American Control Conference (pp. 2455-2460).Montreal, Canada: ACC.

Overloop, PJ van & Bombois, XJA (2012). Identification of properties of open water channelsfor controller design. In J Schoukens (Ed.), 16th IFAC symposium on system identification(pp. 1019-1024). Brussels, Belgium: IFAC.

Portilla, C, Valencia, F, Lopez, J, Espinosa, J, Nunez, A & De Schutter, B (2012). Non-linearmodel predictive control based on game theory for traffic control on highways. In M Lazar& F Allgower (Eds.), 4th IFAC Nonlinear Model Predictive Control Conference (pp.436-441). Noordwijkerhout: IFAC.

Rinaldi, M, Capisani, L, Ferrara, A, Núñez, A, Hajiahmadi, M & De Schutter, B (2012). Distributedidentification of the cell transmission traffic model: A case study. In Tariq Samad (Ed.),2012 American Control Conference (pp. 6545-6550). Montreal, Canada: ACC.

Rungger, M, Mazo Espinosa, M & Tabuada, P (2012). Scaling up controller synthesis for linearsystems and safety specifications. In J.A. Farrell (Ed.), 51st IEEE Conference on Decisionand Control (pp. 7638- 7643). Maui, USA: IEEE.

Saathof, R, Haber, A, Spronck, JW, Verhaegen, M & Munnig Schmidt, RH (2012). Closed loopthermal control of a lithographic optical component. In n.a. (Ed.), Proceedings of theASPE Summer Topical Meeting, June 24-26, 2012, Berkeley, CA, USA (pp. 1-6). Berkeley,CA, USA: ASPE.

Simonetto, A, Keviczky, T & Dimarogonas, DV (2012). Distributed solution for a maximumvariance unfolding problem with sensor and robotic network applications. In B. Hajek &T. Basar (Eds.), 50th annual allerton conference on communication, control, and computing(pp. 1-8). Illinois, USA: Allerton-12.

Simonetto, A, Keviczky, T & Johansson, M (2012). A Reularized Saddle-Point Algorithm forNetworked Optimization with Resource Allocation Contraints. In J.A. Farrell (Ed.), 51stIEEE Conference on Decision and Control (pp. 7476-7481). Maui, USA: IEEE.

Smith, S, Dekker, AJ den, Andrei, RM, Fraanje, PR & Verhaegen, M (2012). Fast phase diversitywavefront sensing using object independent metrics. In B.L. Ellerbroek, E. Marchetti &J-P Véran (Eds.), Spie Astronimical Telescopes + Instrumentation 2012 (pp. 1-9).Amsterdam: Spie.

Strelec, M, Macek, K & Abate, A (2012). Modeling and simulation of a microgrid as a stochastichybrid systems. In K Strunz (Ed.), 3th IEEE PES Innovative Smart Grid TechnologiesEurope Conference 2012 (pp. 1-9). Berlin, Germany: ISGT12.


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Taamallah, S (2012). Low-order modeling for a small-scale flybarless helicopter UAV. A grey-boxtime- domain approach. In S.C. Komadina (Ed.), AIAA Atmospheric flight mechanicsconference (pp. 1-42). Minneapolis, Minnesota: AIAA.

Taamallah, S (2012). Optimal autorotation with obstacle avoidance for a small-scale flybarlesshelicopter UAV. In J. Thienel (Ed.), AIAA Guidance, Navigation and Control Conference(pp. 1-25). Minneapolis: AIAA.

Taamallah, S, Bombois, XJA & Van den Hof, PMJ (2012). Optimal control for power-off landingof a small- scale helicopter a pseudospectral approach. In Tariq Samad (Ed.), 2012American Control Conference (pp. 914-919). Montreal, Canada: ACC.

Tkachev, I & Abate, A (2012). Regularization of Bellman equations for infinite-horizon probabilisticproperties. In T Dang & I Mitchell (Eds.), Hybrid Systems: Computation and Control 2012(pp. 227-236). Beijing, China: HSCC 2012.

Tkachev, I & Abate, A (2012). Stability and attractivity of absorbing sets for discrete-time Markovprocesses. In J.A. Farrell (Ed.), 51st IEEE Conference on Decision and Control (pp.7652-7657). Maui, USA: IEEE.

Vaandrager, M, Babuska, R, Busoniu, IL & Lopes, GAD (2012). Imitation Learning withNon-Parametric Regression. In L Miclea & I Stoian (Eds.), 2012 IEEE InternationalConference on Automation, Quality and Testing, Robotics (AQTR) (pp. 91-96).Cluj-Napoca, Romania: IEEE.

Van den Hof, PMJ, Dankers, AG, Heuberger, PSC & Bombois, XJA (2012). Identification inDynamic Networks with Known Interconnection Topology. In J.A. Farrell (Ed.), 51st IEEEConference on Decision and Control (pp. 895-900). Maui, USA: IEEE.

Van den Hof, PMJ, Jansen, JD & Heemink, AW (2012). Recent developments in model-basedoptimization and control of subsurface flow in oil reservoirs. In L Imsland & M Nikolaouet al (Eds.), Proceeding of the 1st IFAC Workshop on Automatic Control in Offshore Oiland Gas Production (pp. 189-200). Kidlington, UK: Elsevier Ltd.

Veen, GJ van der, Couchman, I.J. & Bowyer, R.O. (2012). Control of floating wind turbines. InTariq Samad (Ed.), 2012 American Control Conference (pp. 3148-3153). Montreal,Canada: ACC.

Wang, Y, De Schutter, B, Boom, AJJ van den & Ning, B (2012). Optimal trajectory planning fortrains under operational constraints using mixed integer linear programming. In NGeroliminis & M Bierlaire (Eds.), 1st European Symposium on Quantitative Methods inTransportation Systems (pp. 1-4). Lausanne, Switzerland: École polytechnique fédéralede Lausanne.

Wang, Y, De Schutter, B, Boom, AJJ van den & Ning, B (2012). Optimal trajectory planning fortrains under operational constraints using mixed integer linear programming. In T Stoilov(Ed.), 13th IFAC Symposium on Control in Transportation Systems (pp. 158-163). Bulgaria:IFAC.

Wingerden, JW van & Torres Tapia, PI (2012). Identification of Spatially Interconnected Systemsusing a Sequentially Semi-Separable Gradient Method. In J Schoukens (Ed.), 16th IFACSymposium on System Identification (pp. 173-178). Brussels, Belgium: IFAC.

Wingerden, JW van (2012).The asymptotic variance of the PBSIDopt algoritm. In J Schoukens(Ed.), 16th IFAC Symposium on System Identification (pp. 1167-1172). Brussels, Belgium:IFAC.

Zeinaly, Y, De Schutter, B & Hellendoorn, J (2012). A model predictive control approach forthe line balancing in baggage handling systems. In T Stoilov (Ed.), 13th IFAC Symposiumon Control in Transportation Systems (pp. 120-125). Bulgaria: IFAC.



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Ph.D. theses

Doan, MD (2012, november 21). Distributed model predictive controller design ased ondistributed optimization. TUD Technische Universiteit Delft (118 pag.). Prom./coprom.:Prof.dr.ir. B De Schutter & T Keviczky.

Kuiper, S (2012, mei 08). Mechatronics and Control Solutions for Increasing the Imaging Speedin Atomic Force Microscopy.TUD Technische Universiteit Delft (133 pag.). Prom./coprom.:Prof.dr.ir. PMJ Van den Hof & Dr.ir. G Schitter.

Simonetto, A (2012, november 02). Distributed Estimation and Control for Robotic Networks.TUD Technische Universiteit Delft (175 pag.). Prom./coprom.: Prof.dr. R Babuska & TKeviczky.

Other publications

Abate, A, Hillen, RC, Wahl, SA, Troch, I & Breitmeier, F (2012, februari 15). Identification offlux profiles and kinetic equations from dynamic labeling experiments: Theory andComputations. Vienna, Austria, Lezing: 7th Vienna International Conference onMathematical Modelling.

Babuska, R (Ed.). (2012). International Journal of General Systems: a comprehensive periodicaldevoted to general systems methodology, applications and education.

De Schutter, B (Ed.). (2012). 4th IFAC Conference on analysis and design of hybrid systems.Eindhoven, The Netherlands: ADHS 12.

De Schutter, B (Ed.). (2012). Automatica.De Schutter, B (Ed.). (2012). IEEE Transactions on Intelligent Transportation Systems.De Schutter, B (Ed.). (2012). Nonlinear Analysis: Hybrid Systems.Keviczky, T (2012). IFAC Conference on nonlinear model predictive control. IFAC Conference

on nonlinear model predictive control: Noordwijkerhout, The Netherlands (2012, augustus23 - 2012, augustus 27).

Octrooi: Groot Wassink, MB (11-04-2012). Inkjet printer and method actuating this inkjet printer.no EP 1690686 B1.

Octrooi: Tejada Ruiz, A & Dekker, AJ den (25-02-2011). POEM: A Fast Defocus EstimationMethod for STEM microscopes. no 2006300.

Suarez-Mendez, C, Sousa, AC de, Abate, A & Wahl, SA (2012). Identification of flux profilesfrom dynamic labeling experiments: S. cerevisiae cultivation under fast feast/famineconditions. Poster: Metabolic Engineering IX: Biarritz, France (2012, juni 03 - 2012, juni07)

Suarez-Mendez, C, Sousa, AC de, Abate, A, Wahl, SA, Troch, I & Breitmeier, F (2012, februari15). Identification of flux profiles from dynamic labeling experiments: S. cerevisiaecultivation under fast feast/famine conditions. Vienna, Austria, Lezing: 7th ViennaInternational Conference on Mathematical Modelling.

Wingerden, JW van (Ed.). (2011). Mechatronics, 21(4).


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Delft University of TechnologyFaculty: Electrical Engineering, Mathematics and ComputerScienceDepartment: Delft Institute of Applied MathematicsChair: Optimization and Systems Theory (OST)

General Information

AddressDelft University of Technology Mekelweg 4 2628 CD Delft The Netherlands Phone (secretary):+31-(0)15-2784109 Fax (secretary) +31-(0)15-2787295 e-mail (secretary):[email protected]

Scientific staffprof.dr. G.J. Olsder (retired), prof.dr.ir. A.W. Heemink, prof.dr.ir. J.H. van Schuppen, dr.ing.D. Jeltsema, dr.ir. J.G. Maks, drs. N. Tholen, dr. J.W. van der Woude

Technical and administrative staffC.P.A. Schneider, D. Engering

PhD studentsE. Budiarto, I.D.T.F. Garcia, M.V. Krymskaya, W. Lawniczak, C. Maris, S. Muhammad, J.S.Pelc, S.P. Szklarz

Cooperation withLaboratoire d’Ingènierie des sysètemes automatisés, Université d’Angers,

INRIA, France, University of Illinois, Urbana-Champaign, USA, Laboratoire d’Automatiquede Grenoble, France, London School of Economics, MIT, University of Waterloo, Shell,Deltares, TNO.

Keywordsconflict analysis, optimal control, game theory, filter theory, large scale systems, max-plusalgebra, dynamical system, differential equation, time table design, production planning,stabilization, traffic planning, road toll, mooring, hierarchy, feedback, structural analysis,discrete events, network analysis, control of distributed systems.

Brief descriptionMathematical Systems Theory (MST) is concerned with the study, analysis, and control ofinput/output phenomena. The emphasis is on the dynamic, i.e. time dependent, behavior ofsuch phenomena. One tries to design control systems such that a desired behavior isachieved as well as possible. MST is at the forefront of the creative interplay of puremathematics, engineering and computer science. Research in the group is on linear as wellas nonlinear systems, and is specifically focused on the system theory of physical modelsand on control of distributed/decentralized systems.

Delft University of TechnologyFaculty: Electrical Engineering, Mathematics and Computer Science

Department: Delft Institute of Applied MathematicsChair: Optimization and Systems Theory (OST)

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DISC projects

Systems theory with algebraic properties

dr. J.W. van der WoudeProjectleader:

DescriptionControl and systems theory with algebraic properties. Study of max-plus and Clifford algebras.Applications of the former in production planning and specifically in timetable design fortransportation systems (such as railways). The latter deals with the description (or better:avoidance of) singularities in modelling.

Filtering, identification and control of large scale systems

prof.dr.ir. A.W. HeeminkProjectleader:

DescriptionData assimilation methods are used to combine the results of a large scale numericalmodelwith the measurement information available in order to obtain an optimal reconstructionof the dynamic behavior of the model state. A number of new filter algorithms for large scalesystems has been developed. Applications are for instance in the areas of mooring shipsat oil platforms, air pollution prediction problems.

Publications

Book chapters/parts

Jeltsema, D & Scherpen, JMA (2012). Power-based Modelling. In F Vasca & L Iannelli (Eds.),Dynamics and Control of Switched Electronic Systems (Advances in Industrial Control)(pp. 245-271). London: Springer-Verlag.


Altaf, MU, Verlaan, M & Heemink, AW (2012). Efficient identification of uncertain parametersin a large-scale tidal model of the European continental shelf by proper orthogonaldecomposition. International Journal for Numerical Methods in Fluids, 68(4), 422-450.

Jeltsema, D & Doria Cerezo, A (2012). Post-Hamiltonian formulation of systems with memory.Institute of Electrical and Electronics Engineers. Proceedings, 100(6), 1928-1937.

Meza, C, Biel, D, Jeltsema, D & Scherpen, JMA (2012). Lyapunov-based control scheme forsingle-phase grid-connected PV central inverters. IEEE Transactions on Control SystemsTechnology, 20(2), 520-529.

Pelc, JS, Simon, E, Bertino, L, El Serafy, GY & Heemink, AW (2012). Application of modelreduced 4D-Var to a 1D ecosystem model. Ocean Modelling, 57-58, 43-58.


Jeltsema, D (). Memory elements: a paradigm shift in Lagrangian modeling of electrical circuits.In Proceedings 7th International Conference on Mathematical Modelling (pp. 1-5). s.l.:s.n..

Delft University of TechnologyFaculty: Electrical Engineering, Mathematics and Computer ScienceDepartment: Delft Institute of Applied MathematicsChair: Optimization and Systems Theory (OST)

100

Koopman, J & Jeltsema, D (). Casimir-based control beyond the dissipation obstacle. InProceedings 4th IFAC Workshop on Lagrangian and Hamiltonian methods for non linearcontrol (pp. 173-177).

Szklarz, SP, Rojas Larrazabal, MDLC & Kaleta, MP (). Efficient solution of the optimizationproblem in model-reduced gradient-based history matching. In Proceedings of ECMORXIII, September 2012, A27 (pp. 1-17). s.l.: s.n..

Szklarz, SP, Rojas Larrazabal, MDLC & Kaleta, MP (). The optimization problem inmodel-reduced gradient-based history matching. In L Imsland (Ed.), Proceedings of the2012 IFAC Workshop on Automatic Control in Offshore Oil and Gas Production (pp.13-18). s.l.: s.n..

Van den Hof, PMJ, Jansen, JD & Heemink, AW (2012). Recent developments in model-basedoptimization and control of subsurface flow in oil reservoirs. In L Imsland & M Nikolaouet al (Eds.), Proceeding of the 1st IFAC Workshop on Automatic Control in Offshore Oiland Gas Production (pp. 189-200). Kidlington, UK: Elsevier Ltd.

Ph.D. theses

Lawniczak, W (2012, december 10). Feature-based estimation for applications in geosciences.Delft University of Technology (125 pag.). Prom./coprom.: Prof.dr.ir. AW Heemink &Prof.dr.ir. JD Jansen.

Muhammad, S (2012, april 23). Dynamic positioning of ships. Delft University of Technology(137 pag.). Prom./coprom.: Prof.dr.ir. AW Heemink & Dr. JW van der Woude.

Delft University of TechnologyFaculty: Electrical Engineering, Mathematics and Computer Science

Department: Delft Institute of Applied MathematicsChair: Optimization and Systems Theory (OST)

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Delft University of TechnologyFaculty of Aerospace EngineeringControl and Simulation

General Information

AddressDelft University of Technology, Faculty of Aerospace Engineering, Control and Simulation,Kluyverweg 1, 2629 HS Delft, The Netherlands. Phone (secretary): +31–15–2782094. Fax(secretary): +31–15–2786480.

Scientific staffProf.dr. ir. M. Mulder, Prof.dr.ir. J.A. Mulder, Dr.ir. M.M. van Paassen, Dr. Q.P. Chu, Dr. ir.A.C. in ’t Veld, Dr.ir. E. van Kampen, Dr.ir. C. Borst, Dr. M.D. Pavel. Dr.ir. C.C. de Visser,Dr.ir. H.J. Damveld, Dr.ir. D.M. Pool

Technical and administrative staffing. H. Lindenburg, ing. A. Damman, ing. A. Muis, F.N. Postema, M.M. Klaassen, G.F. denToom, ing. E.H.H. Thung, Ir. T.J. Mulder. Ir. B.D.W. Remes, Ir. C. de Wagter, Ir. S. Tijmons,Ir. H.M. Ruijsink, Ir. O. Stroosma

PhD studentsir. C. de Wagter, ir. J.L. de Prins, ir. S.J.B. van Dam, ir. J. Ellerbroek, ir. A.R. Valente Pais,ir. A.M.P. de Leege, B.J. Correia Gracio, ir. J. Comans, ir. J. Venrooij, ir. M.A. Rahman, ir.P.M.A. de Jong, Y. Hui, L. Sun, ir. L. van Eykeren, H.J. Koolstra, J. Wan, D.Yilmaz, R.E.Klomp, F.M. Drop, Y.I. Jenie, M. Tielrooij, V.A.V. Caetano, J. Smisek, M.F. Bin Zakaria,D.Jatiningrum, P. Lu, G.A. Mercado Velasco, Y. Ibrahim Jenie

Cooperation withESA/ESTEC, Deimos Space, Dutch Space, EADS, LM, Navionex, RAF, NAL, Boeing,Minnesota University, NLR, TNO/FEL, NIVR, DLR, Garteur, Misat/MicroNed, NASA, VictoriaUniversity, Wright State University, Max Planck Institute, Heidelberg, Georgia Tech, MIT,Boeing Research and Technology Europe.

Brief descriptionWithin the research programme ‘Control and Simulation’, two fields of aerospace scienceplay an equally important role. The first is concerned with the flight dynamics of aerospacevehicles as aircraft, rotorcraft and spacecraft, their mathematical models, the analysis oftheir dynamic properties, and the design and analysis of manual and automatic guidanceand control of these vehicles through computers. It is in this field, ‘Aerospace GuidanceNavigation and Control (AGNC)’, that a variety of control-theoretic concepts are the focusof interest.The second field studies the interaction of the human operator with the aerospacevehicle, in many cases in the context of a complex operational environment. In this field ofaerospace science, ‘Aerospace Human-Machine Systems (AHMS)’, the cybernetic propertiesof human operators are studied, i.e., their perception and control behaviour in manual controltasks, but also aims at supporting human operators in a more automated environment, actingas a ‘supervisor’.While the two fields AGNC and AHMS are distinct in their subjects, theoriesand mathematics, they are often closely interlinked and mutually dependent in many problems


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such as in the design of manual flight control systems leading to good handling qualitiesand in the optimal design of flight simulator motion cueing systems.

Aerospace Guidance, Navigation and Control (AGNC)

The goal of our research within AGNC can be formulated as to enhance manoeuvringperformance, safety, and survivability of aerospace vehicles ranging from small UninhabitedAreal Vehicles (UAV) to transport aircraft, and from rotorcraft to re-entry vehicles andsatellites.The long track record in research in dynamic flight test techniques and identificationof nonlinear aerodynamic models of a variety of aircraft enabled the group to naturally moveits research towards nonlinear, robust and fault-tolerant GNC systems as its main focal point.The research is more than just a pure theoretical development, and aims at applying a widerange of available theoretical concepts to problems of practical significance. The group isthought to be in a very good position to do just that as it can combine expertise from controltheoretical subjects as linear and nonlinear control, state estimation, system identification,nonlinear optimisation and intelligent and knowledge based systems with deep domainknowledge of subjects as flight dynamics, aerodynamics, structural dynamics, flight testprocedures, flight instrumentation, carrier phase based GPS navigation and attitudedetermination, dynamic manoeuvre design, aircraft handling qualities and orbit and attitudedynamics. Also, as the group includes several professional pilots including the chair holder,our extensive operational experience is a guarantee that the proposed systems and solutionsare not just academically sound but do make practical sense too. While academic researchon GNC often remains in the realm of feasibility studies using simplified models and off-linecomputer simulations, the strength of our group is also in actual implementation of algorithmsfor real-time evaluation in the flight simulator as well as in the Cessna Citation laboratoryaircraft, to be evaluated by professional civil transport aircraft- and air force test pilots.

The field of ‘Aerospace Human-Machine Systems’ (AHMS)

The interest in the area of human-machine interaction started during the second World War.Large groups of (military) personnel were required to operate complex machinery. The keyto success of these combined human-machine systems was often found in the proper designof the interface between the system and its human operator. This has led to aninterdisciplinary research field called cybernetics with contributions from engineering (mainlycontrol system engineering), psychology (including cognitive and perceptual psychology),and from physiology. Cybernetics is therefore the first core area of research within the fieldof Aerospace Human-Machine Systems.

With the advent of automated systems, research was started on the role of the humanoperator as an observer of largely automated processes, and as a supervisor issuingcommands and set-points to the automation. Increases in scale and system complexity ledto the development of various new approaches to the design of human-machine interfaces.One very powerful of these is currently known as Cognitive Systems Engineering (CSE),which uses the ‘work domain’ of the human-machine system to be (re-) designed as itsstarting point.This in contrast to earlier techniques that start with an analysis of and a focuson the proposed task that the human will have in the new system, or on the knowledge thatexperts have acquired in existing (similar) systems. By starting with an analysis of the workdomain, however, cognitive systems engineering has proven to be more suitable tohuman-machine system and interface design for future applications of large scale andcomplexity. CSE is the second core area of research within AHMS.

Delft University of TechnologyFaculty of Aerospace Engineering

Control and Simulation

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Publications

Publications

Book chapters/parts

Abdul Rahman, SMB, Borst, C, Mulder, M & Paassen, MM van (2012). Measuring SectorComplexity: Solution Space Based Method. In T Magister (Ed.), Advances in Air NavigationServices (pp. 11-34). Croatie: Intech.

Pavel, MD (2012). Effects of Automatic Flight Control System on Chinook Underslung LoadFailures. In TJJ Lombaerts (Ed.), Flight Controls (pp. 151-184). Croatia: Intech-OpenAccess Publisher.


Chen, T, Kampen, E van, Yu, H & Chu, QP (2012). Optimization of Time-Open ConstrainedLambert Rendezvous Using Interval Analysis. Journal of Guidance, Control, and Dynamics:devoted to the technology of dynamics and control, 35(7), 1-10.

Clare, AS, Maere, PCP & Cummings, ML (2012). Assessing operator strategies for real-timereplanning of multiple unmanned vehicles. Intelligent Decision Technologies, 221-231.

Correia Gracio, BJ & Bos, JE (2012). Measuring dynamics of the subjective vertical and tiltusing a joystick. Journal of Vestibular Research: Equilibrium and Orientation: aninternational journal of experimental and clinical vestibular science, 22(4), 181-189.

Correia Gracio, BJ, Winkel de, KN, Groen, E.L., Wentink, M & Bos, JE (2012).The time constantof the somatogravic illusion. Experimental Brain Research, 1-9.

Croon, GCHE de, Groen, MA, Wagter, C de, Remes, BDW, Ruijsink, HM & Oudheusden, BWvan (2012). Design, aerodynamics and autonomy of the Delfly. Bioinspiration &Biomimetics: learning from nature, 7(2), 64-79.

Croon, GCHE de, Wagter, C de, Remes, BDW & Ruijsink, HM (2012).The Appearance VariationCue for Obstacle Avoidance. IEEE Transactions on Robotics, 28(2), 529-534.

Croon, GCHE de, Weerdt, E De, Wagter, C de, Remes, BDW & Ruijsink, HM (2012).Sub-sampling: Real-time vision for micro air vehicles. Robotics and Autonomous Systems,60(2), 167-181.

Hoencamp, A & Pavel, MD (2012). Concept of a predictive tool for ship-helicopter operationallimitations of various in-service conditions. American Helicopter Society. Journal, 57(3),1-9.

Leege, AMP de, Mulder, M & Paassen, MM van (2012). Novel Method for Wind EstimationUsing Automatic Dependent Surveillance-Broadcast. Journal of Guidance, Control, andDynamics: devoted to the technology of dynamics and control, 35(2), 648-652.

Lombaerts, TJJ, Looye, GHN, Chu, QP & Mulder, JA (2012). Design and simulation of faulttolerant flight control based on a physical approach. Aerospace Science and Technology,23(1), 151-171.

Mulder, M, Abbink, DA & Boer, ER (2012). Sharing Control With Haptics: Seamless DriverSupport From Manual Control to Automatic Control. Human Factors: the journal of thehuman factors and ergonomics society, 1-13.

Percin, M, Hu, Y, Oudheusden, BW van, Remes, BDW & Scarano, F (2012). Wing flexibilityeffects in clap-and-fling. International Journal of Micro Air Vehicles, 3(4), 217-227.

Pool, DM, Valente pais, AR, De Vroome, AM, Paassen, MM van & Mulder, M (2012).Identification of Nonlinear Motion Perception Dynamics Using Time-Domain Pilot Modeling.Journal of Guidance, Control, and Dynamics: devoted to the technology of dynamics andcontrol, 35(3), 749-763.


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Stuyven, G, Damveld, HJ & Borst, C (2012). Concept for an avionics multi touch flight deck.SAE International Journal of Aerospace, 5(1), 164-171.

Valente pais, AR, Pool, DM, De Vroome, AM, Paassen, MM van & Mulder, M (2012). PitchMotion Perception Thresholds During Passive and Active Tasks. Journal of Guidance,Control, and Dynamics: devoted to the technology of dynamics and control, 35(3), 904-918.

Van der Eijk, A, Borst, C, Veld, AC in 't, Paassen, MM van & Mulder, M (2012). Assisting AirTraffic Controllers in Planning and Monitoring Continuous-Descent Approaches. Journalof Aircraft: devoted to aeronautical science and technology, 49(5), 1376-1390.

Venrooij, J, Mulder, M, Abbink, DA, Paassen, MM van & Helm, FCT van der (2012). A NewView on Biodynamic Feedthrough Analysis: Unifying the Effects on Forces and Positions.IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics, PP(99), 1-14.

Visser, CC de, Kampen, E van, Chu, QP & Mulder, JA (2012). Intersplines: A New Approachto Globally Optimal Mutivariate Splines Using Interval Analysis. Reliable Computing (PrintEdition), 17(2), 153-191.

Weerdt, E De, Kampen, E van, Chu, QP & Mulder, JA (2012). Polynomial Inclusion Functions.Reliable Computing (Print Edition), 16(4), 283-307.

Winter, JCF de, Dodou, D & Mulder, M (2012). Training Effectiveness of Whole Body FlightSimulator Motion: A Comprehensive Meta-Analysis.The International Journal of AviationPsychology, 22(2), 164-183.

Zaal, PMT, Pool, DM, Paassen, MM van & Mulder, M (2012). Comparing Multimodal Pilot PitchControl Behavior Between Simulated and Real Flight. Journal of Guidance, Control, andDynamics: devoted to the technology of dynamics and control, 35(5), 1456-1471.


Abbink, DA, Cleij, D, Mulder, M & Paassen, MM van (2012). The importance of includingknowledge of neuromuscular behaviour in haptic shared control. In IEEE InternationalConference on Systems, Man & Cybernetics (pp. 1-6). Seoul, Korea.

Abbink, DA, Cleij, D, Mulder, M & Paassen, MM van (2012). The Importance of IncludingKnowledge of Neuromuscular Behaviour in Haptic Shared Control. In WL Seong (Ed.),Proceedings of the 2012 IEEE International Conference on Systems, Man and Cybernetics(pp. 3332-3337). Piscataway, NJ: IEEE.

Abdul Rahman, SMB, Borst, C, Mulder, M & Paassen, MM van (2012). Using the SolutionSpace Diagram to Map Sector Complexity. In G Boy (Ed.), Proceedings of the InternationalConference on Human-Computer Interaction in Aerospace (HCI-Aero) 2012 (pp. 1-8).Brussel, Belgie: Guy Boy, Florida Institute of technology, USA.

Acquatella, P, Falkena, W , Kampen, E van & Chu, QP (2012). Robust nonlinear SpacecraftAttitude Control using Incremental Nonlinear Dynamic Inversion. In J Thienel (Ed.),Proceedings of the AIAA Guidance, Navigation and Control Conference 2012 (pp. 1-20).Reston, VA: AIAA.

Beckers, NWM, Pool, DM, Valente pais, AR, Paassen, MM van & Mulder, M (2012). Perceptionand Behavioral Phase Coherence Zones in Passive and Active Control Tasks in Yaw. InSD Beard (Ed.), Proceedings of the AIAA Modeling and Simulation TechnologiesConference (pp. 1-24). Reston, VA: AIAA.

Beekhuyzen, M, Leege, AMP de, Veld, AC in 't, Paassen, MM van & Mulder, M (2012). In-TrailSequence Stability in Closed Path Continuous Descent Operations. In J Thienel (Ed.),Proceedings of the AIAA Guidance, Navigation and Control Conference (pp. 1-26).Reston, VA: AIAA.

Borst, C, Hilburn, B & Westin, C (2012). An Investigation into the Use of Novel Conflict Detectionand Resolution Automation in Air Traffic Management. In D Schaefer (Ed.), Proceedingsof the SESAR Innovation Days (pp. 1-8). Braunschweig: Eurocontrol.



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Bussink, FJL, Laan, JJ van der & Jong, PMA de (2012). Combining Flight-deck IntervalManagement with Continuous Descent Approaches in high density traffic and realisticwind conditions. In J Thienel (Ed.), Proceedings of the AIAA Guidance, Navigation andControl Conference (pp. 1-25). Reston: AIAA.

Chaves, H.M., Pauwelussen, JJA, Mulder, M, Paassen, MM van, Happee, R & Mulder, M (2012).Detecting Intermittent Steering Activity - Development of a Phase-detection Algorithm.In WL Seong (Ed.), Proceedings of the 2012 IEEE International Conference on Systems,Man and Cybernetics (pp. 144-149). Piscataway, NJ: IEEE.

Chen, T, Kampen, E van, Yu, H & Chu, QP (2012). Optimization of time-open constrainedLambert rendezvous using interval analysis. In DB Spencer (Ed.), Proceedings of theAIAA/AAS Astrodynamics Specialist Conference 2012 (pp. 1-28). Reston, VA: AIAA.

Correia Gracio, BJ, Bos, JE, Wentink, M, Paassen, MM van & Mulder, M (2012). PerceivedMismatch Between Visual and Inertial Cues in a Simulation Environment. In JS Berndt(Ed.), Proceedings of the AIAA Modeling and Simulation Technologies Conference (pp.1-7). Reston, VA: AIAA.

Correia Gracio, BJ, Wentink, M, Bos, JE, Paassen, MM van & Mulder, M (2012). An Applicationof the Canal-Otolith Interaction Model for Tilt-Coordination During a Braking Maneuver.In JS Berndt (Ed.), Proceedings of the AIAA Modeling and Simulation TechnologiesConference (pp. 1-13). Reston, VA: AIAA.

Damveld, HJ & Happee, R (2012). Identifying Driver Behaviour in Steering: Effects of PreviewDistance. In A Spink (Ed.), Proceedings of the Measuring Behavior 2012. 8th InternationalConference on Methods and Techniques in Behavioral Research (pp. 44-46).Wageningen:Noldus Information Technology.

Damveld, HJ, Wentink, M, Leeuwen, PM van & Happee, R. Dr.ir. (2012). Effects of MotionCueing on Curve Driving. In S Espie, A Kemeny & F Merienne (Eds.), Proceedings ofthe Driving Simulation Conference Europe 2012 (pp. 11-22). Bron Cedex, France:IFFSTTAR, the French Institute of Science and Technology for Transport, Developmentand Networks.

Drop, FM, Pool, DM, Damveld, HJ, Paassen, MM van, Bulthoff, HH & Mulder, M (2012).Identification of the Transition from Compensatory to Feedforward Behavior in ManualControl. In J.del.R Millan (Ed.), Proceedings of the IEEE International Conference onSystems, Man, and Cybernetics (SMC) 2012 (pp. 2008-2013). New York, USA: IEEE.

Ellerbroek, J, Brantegem, KCR, Mulder, M, Paassen, MM van & Gelder, N de (2012). Designof a Co-Planar Airborne Separation Display. In G Boy (Ed.), Proceedings of theHuman-Computer Interaction in Aerospace (pp. 1-8). Eurocontrol.

Ellerbroek, J, Brantegem, KCR, Mulder, M, Paassen, MM van & Gelder, N de (2012).Experimental Evaluation of a Co-Planar Airborne Separation Display. In WL Seong (Ed.),Proceedings of the IEEE Conference on Systems, Man and Cybernetics (pp. 1-6). IEEE.

Eykeren, L, Chu, QP & Mulder, JA (2012). Actuator Fault Detection by Aerodynamic ModelIdentification. In CM Astorga-Zaragoza & AM Gutierrez (Eds.), Proceedings of the 8thIFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes(pp. 1353-1357). Mexico City, Mexico: IFAC.

Eykeren, L, Chu, QP & Mulder, JA (2012). Sensor Fault Detection and Isolation using AdaptiveExtended Kalman Filter. In CM Astorga-Zaragoza & AM Gutierrez (Eds.), Proceedingsof the 8th IFAC Symposium on Fault Detection, Supervision and Safety of TechnicalProcesses (pp. 1155-1160). Mexico City, Mexico: IFAC.


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Happee, R, Damveld, HJ, Abbink, DA, Paassen, MM van & Mulder, M (2012). Driver and PilotIdentification and Model Parameter Estimation; Modelling the Visual, Vestibular andNeuromuscular Control Loops Describing Driver and Pilot Behaviour. In A Spink (Ed.),Proceedings of the Measuring Behavior 2012. 8th International Conference on Methodsand Techniques in Behavioral Research (pp. 51-54). Wageningen: Noldus InformationTechnology.

Hoencamp, A & Pavel, MD (2012). Flight Test Results NH90 NFH Helicopter-Ship QualificationProcess. In Curran Associates, Inc. (Ed.), Proceedings of the American Helicopter Society68th Annual Forum (pp. 1-12). Washington: American Helicopter Society.

Hoencamp, A & Pavel, MD (2012). Helicopter-Ship Qualification Testing for the NH90 NFHHelicopter. In NLR (Ed.), Proceedings of the European Rotorcraft Forum 38th (pp. 1-12).Amsterdam: NLR.

Jones, M, Jump, M, Lu, L, Yilmaz, D & Pavel, MD (2012). Using The Phase-Aggression Criterionto Identify Rotorcraft Pilot Coupling Events. In NLR (Ed.), Proceedings of the EuropeanRotorcraft Forum 38th (pp. 1-17). Amsterdam: NLR.

Jong, PMA de, Bussink, FJL, Gelder, N de, Verhoeven, RPM & Mulder, M (2012). Time andEnergy Management during Descent and Approach for Aircraft. In D Young & SSaunders-Hodge (Eds.), Proceedings of the 5th International Conference on Researchin Air Transportation-ICRAT 2012 (pp. 1-6). FAA and EUROCONTROL.

Klomp, RE, Paassen, MM van, Borst, C, Mulder, M, Bos, T, Leeuwen, P van & Mooij, M. (2012).Joint human-automation cognition through a shared representation of 4D TrajectoryManagement. In D Schaefer (Ed.), Proceedings of the SESAR Innovation Days (2012)(pp. 1-7). Braunschweig, Germany: Eurocontrol.

Koolstra, HJ, Damveld, HJ & Mulder, JA (2012). Envelope determination of damaged aircraft.In J Thienel (Ed.), Proceedings of the AIAA Guidance, Navigation and Control Conference2012 (pp. 1-22). Reston, VA: AIAA.

Leege, AMP de, Paassen, MM van & Mulder, M (2012). Using Automatic DependentSurveillance-Broadcast for Meteorological Monitoring. In J Thienel (Ed.), Proceedings ofthe AIAA Guidance, Navigation and Control Conference (pp. 1-21). Reston, VA: AIAA.

Leege, AMP de, Tielrooij, M, Eijk, A van der & Mulder, M (2012). A Time-Space Diagram basedController Support Tool for Continuous Descent Operations. In Proceedings of theInternational Conference on Human-Computer Interaction in Aerospace (pp. 1-8). Florida,USA: Guy Boy, Florida Institute of Technology.

Lopes, H, Kampen, E van & Chu, QP (2012). Attitude Determination of Highly DynamicFixed-wing UAVs with GPS/MEMS-AHRS integration. In J Thienel (Ed.), Proceedings ofthe AIAA Guidance, Navigation and Control Conference 2012 (pp. 1-17). Reston, VA:AIAA.

Mendes, A, Kampen, E van, Remes, BDW & Chu, QP (2012). Determining moments of inertiaof small UAVs: A comparative analysis of an experimental method versus theoreticalapproaches. In J Thienel (Ed.), Proceedings of the AIAA Guidance, Navigation andControl Conference 2012 (pp. 1-14). Reston, VA: AIAA.

Mertens, MM, Damveld, HJ & Borst, C (2012). An Avionics Touch Screen-Based Control DisplayConcept. In PL Marasco, PR Havig, D Desjardins & KR Sarma (Eds.), Proceedings ofthe SPIE Head- and Helmet-Mounted Displays XVII; and Display Technologies andApplications for Defense, Security and Avionics VI (pp. 1-13). Bellingham, Washington:SPIE.

Mulder, M, Abbink, DA, Boer, ER & Paassen, MM van (2012). Human-Centered STeer-by-wireDesign -- steering Wheel Dynamics Should be Task Dependent. In WL Seong (Ed.),Proceedings of the 2012 IEEE International Conference on Systems, Man and Cybernetics(pp. 3009-3013). Piscataway, NJ: IEEE.



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Olivari, M, Nieuwenhuizen, FM, Venrooij, J, Bulthoff, HH & Pollini, L (2012). Multi-loop PilotBehavior Identification in Response to Simultaneous Visual and Haptic Stimuli. In JThienel (Ed.), Proceedings of the AIAA Modeling and Simulation Technologies Conference(pp. 1-23). Reston, VA: AIAA.

Paassen, MM van, Ellerbroek, J, Comans, J, Borst, C & Mulder, M (2012). Ecological InterfaceDesign for Aircraft Guidance and Conflict Avoidance. In A Bernard & F Chinesta (Eds.),Proceedings of the ASME 2012 11th Biennial Conference on Engineering Systems Designand Analysis (ESDA 2012) (pp. 1-8). American Society for Mechanical Engineers.

Paassen, MM van, Gordijn, JRC, Ellerbroek, J, Borst, C & Mulder, M (2012). Emergent Featuresof Self Separation in Flight - Results from a Monte-Carlo Study. In Seong Whan Lee(Ed.), Proceedings of the 2012 IEEE International Conference on Systems, Man, andCybernetics (pp. 3033-3038). Piscataway, NJ: IEEE.

Pavel, MD, Malecki, J, Vu, BD, Masarati, P, Gennaretti, M, Jump, M, Smaili, H, Ionita, A &Zaicek, L (2012). A Retrospective Survey of Adverse Rotorcraft Pilot Couplings inEuropean Perspective. In Curran Associates, Inc (Ed.), Proceedings of the AmericanHelicopter Society 68th Annual Forum (pp. 1-14). Washington: American HelicopterSociety.

Percin, M, Eisma, HE, Baar, JHS de, Oudheusden, BW van, Remes, BDW, Ruijsink, HM &Wagter, C de (2012). Wake reconstruction of flapping-wing MAV `DelFly II¿ in forwardflight. In (pp. 1-13). Braunschweig: IMAV 2012 Organization Committee.

Percin, M, Eisma, HE, Oudheusden, BW van, Remes, BDW, Ruijsink, HM & Wagter, C de(2012). Flow visualization in the wake of flapping-wing MAV `DelFly II¿ in forward flight.In Online Publication (pp. 1-12). New Orleans, USA:The American Institute of Aeronauticsand Astronautics (AIAA).

Pool, DM, Zaal, PMT, Damveld, HJ, Paassen, MM van & Mulder, M (2012). Evaluating SimulatorMotion Fidelity using In-Flight and Simulator Measurements of Roll Tracking Behavior.In SD Beard (Ed.), Proceedings of the AIAA Modeling and Simulation TechnologiesConference (pp. 1-25). Reston, VA: AIAA.

Quaranta, G, Masarati, P & Venrooij, J (2012). Robust Stability Analysis: a tool to assess theimpact of biodynamic feedthrough on rotorcraft. In Curran Associates Inc. (Ed.),Proceedings of the American Helicopter Society International (pp. 1306-1315). Curran,Red Hook, NY, USA: American Helicopter Society.

Suliman, SMT, Yilmaz, D & Pavel, MD (2012). Harmonizing Real-Time Oscillation Verifier(Rover) With Handling Qualities Assessment For Enhanced Rotorcraft Pilot CouplingsDetection. In NLR (Ed.), Proceedings of the European Rotorcraft Forum 38th (pp. 1-18).Amsterdam: NLR.

Sun, L, Visser, CC de & Chu, QP (2012). A Recursive Sequential Method for Multivariate SplinesTowards Online Aerodynamic Model Identification. In J Thienel (Ed.), Proceedings of theAIAA Guidance, Navigation and Control Conference (pp. 1-19). Reston, VA: AIAA.

Veld, AC in 't & Karwal, AK (2012). Upgrading a multi-mission research aircraft. In R Curran,L Fischer & D Perez (Eds.), Proceedings of the Third International Air Transport andOperations Symposium (pp. 400-405). Amsterdam: IOS Press.

Venrooij, J, Mulder, M, Paassen, MM van, Abbink, DA, Helm, FCT van der, Mulder, M & Bulthoff,HH (2012). How effective is an armrest in mitigating biodynamic feedthrough? In WLSeong (Ed.), Proceedings of the 2012 IEEE International Conference on Systems, Man,and Cybernatics (pp. 2150-2155). Piscataway, NJ: IEEE.

Venrooij, J, Pavel, MD, Mulder, M, Helm, FCT van der & Bulthoff, HH (2012). A PracticalBiodynamic Feedthrough Model For Helicopters. In NLR (Ed.), Proceedings of theEuropean Rotorcraft Forum 38th (pp. 1-13). Amsterdam: NLR.


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Venrooij, J, Pavel, MD, Mulder, M, Helm, FCT van der & Bulthoff, HH (2012). A praticalbiodynamic feedthrough model for helicopters. In s.n. (Ed.), Proceedings of the 38thEuropean Rotorcraft Forum (pp. 1-13). Amsterdam: ERF / Kees Backer.

Wan, J & Pavel, MD (2012). Directional Handling Quality Assessment for Ornicopter. In NLR(Ed.), Proceedings of the European Rotorcraft Forum 38th (pp. 1-11). Amsterdam: NLR.

Yilmaz, D, Pavel, MD, Jones, M, Jump, M & Lu, L (extern) (2012). Identification of pilot controlbehavior during possible rotorcraft pilot coupling events. In SN (Ed.), Proceedings of the38th European Rotorcraft Forum (pp. 1-22). Amsterdam: NLR.

Ph.D. theses

Falkena, W . Investigation of Practical Flight Control Systems for Small Aircraft.TUD TechnischeUniversiteit Delft (306 pag.) (Zutphen:Wohrmann Print Service). Prom./coprom.: Prof.dr.ir.JA Mulder & Dr. QP Chu.

Nieuwenhuizen, FM (2012, juli 04). Changes in Pilot Control Behaviour across Stewart PlatformMotion Systems. TUD Technische Universiteit Delft (200 pag.) (Zutphen: WohrmannPrint Service). Prom./coprom.: Prof.dr.ir. M Mulder, HH Bulthoff & Dr.ir. MM van Paassen.

Pool, DM (2012, september 24). Objective Evaluation of Flight Simulator Motion Cueing FidelityThrough a Cybernetic Approach.TUD Technische Universiteit Delft (430 pag.) (Zutphen:Wöhrmann Print Service). Prom./coprom.: Prof.dr.ir. M Mulder & Dr.ir. MM van Paassen.

Other publications

Mulder, M & Abbink, DA (2012). Human-Steering Wheel and Vehicle-Driver BiodynamicPerturbation Interaction. Delft: Nissan Motor Company, Ltd..

Mulder, M (Ed.). (2012). ACM Transactions on Applied Perception.Mulder, M (Ed.). (2012). The International Journal of Aviation Psychology.Mulder, M (Ed.). (2012). The Open Aerospace Engineering Journal.Mulder, M, Abbink, DA, Boer, ER & Paassen, MM van (2012). Human-Centered steer-by-wire

design: streering wheel dynamics should be task dependent. In S.W. Lee (Ed.),Proceedings of the internation IEEE Conference on Systems, Man & Poster AOgeplastificeerd. Graag de witte randen verwijderen en In full colour printen. (pp. 1-5).Seoul, Korea: IEEE.

Paassen, MM van (Ed.). (2012). IEEE Transactions on Systems, Man and Cybernetics, PartA: Systems & Humans.

Pavel, MD (Ed.). (2012). CEAS Aeronautical Journal.Stroosma, O & Pavel, MD (2012). Rotorcraft Piloted Simulation Evaluation using the SIMONA

Research Simulator at TU Delft - Report on Handling Qualities experiment Phase 1. Delft:TU Delft.



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Eindhoven University of TechnologyDepartment of Mechanical EngineeringDynamics and Control Group, Control Systems TechnologyGroup & Hybrid and Networked Systems

General Information

AddressEindhoven University of Technology, Department of Mechanical Engineering, Section:Dynamics & Control (D&C, H. Nijmeijer) Control Systems Technology ( CST, M. Steinbuch)and Hybrid & Networked Systems ( H&NS, W.P.M.H. Heemels) Postbus 513, 5600 MBEindhoven, The Netherlands. Phone (secretary) : + 31-40-2474817/2796. Fax (secretary)+31-40-2461418. E-mail (secretary): [email protected] or [email protected]

Scientific staffProf.Dr. H. Nijmeijer, Prof.Dr.Ir. P.P. Jonker, Prof.Dr.Ir. N.B. Roozen, Dr.Ir. J.J.M. Besselink,Dr.Ir. R.H.B. Fey, Dr.Ir. M.F. Heertjes, Dr.Ir. A.D. de Kraker, Dr.Ir. D. Kostic, Dr.Ir. S.Koekebakker, Dr.ir. R. Huisman, Dr.Ir. I. Lopez, Dr.Ir. N. v.d. Wouw, Prof.Dr.Ir. M. Steinbuch,Prof.Ir. O.H. Bosgra, Prof.dr. M.R. de Baar, Prof.dr.ir. W.P.M.H. Heemels, Dr.i.r M.F. Heertjes,Dr.ir. T. Hofman, Dr.Ir. A.G. de Jager, Dr.Ir. M.J.G. v.d. Molengraft, Dr.Ir. P.W.J.M. Nuij,Dr.ir. T.A.E. Oomen, Dr.ir. P.C.J.N. Rosielle, Dr.Ir. F.P.T. Willems, Prof.dr. H.J. Zwart

Technical and administrative staffP.G.M. Hamels, P.W.C. v. Hoof, E. Meinders, G. Janssen-Dols, P.R.M. Aspers, R. v.d.Bogaert, M.A.P.M. v. Gils, H.C.T. v.d. Loo, W.J. Loor, J.G.M. de Vries

PhD studentsS. Adinandra MSc, A. Alvarez MSc, N. Bauer MSc, Ir. B. Biemond, Ir. A. Denasi, J. PenaMSc, Ir. J. Ploeg, MSc S. Öncü, Ir. D. Heck, Ir. M. Hoeijmakers, Ir. R.W. v. Gils, C.G. MurguiaMSc, I. Aladagli MSc., Ir. K. van Berkel, ir. M. van Berkel, ir. F.A.J. Boeren, Ir. J.J. Bolder,Ir. H. van den Brand, Ir. C.H.A. Criens, Ir. S. van den Dries, Ir. J. Elfring, E. Feru MSc, Ir.R.M.A. van Herpen, Ir. G. Hommen, Ir. R. Hoogendijk, Ir. R.J.M. Janssen, Ir. M. Lauret, Ir.R.J.R. van der Maas, S. Marinkov MSc, C.A. Lopez Martinez, M.Sc., Ir. J. Lunenburg, DacViet Ngo, M.Sc., I. Polat MSc, Ir. S.K. Ravensbergen, Ir. V. van Reeven, Ir. D.J. Rijlaarsdam,Ir. M.J.C. Ronde, I. Sahin MSc, Ir. T.P.J. van der Sande, E. Silvas MSc, Ir. P. Van Zutven

Temporary staff and postdocsDr.ir. D. Antunes, Dr.ir. D. Dirks, Dr.ir. S.Djordjevic, Dr.ir. F.A.A. Felici, J.F. Flores ResendizMSc, Dr.ir. D. Guerreio Tomé Antunes, Dr.ir. R. Hendrix, Dr.ir. H.C.M. Meenink, Dr. A.B.Morales Diaz, Dr.ir. D.V. Ngo, Dr.ir. I. Soute

Cooperation with

Structure of cooperation

Department of Mechanical EngineeringThe control activities in the Department of Mechanical Engineering are united comprised inthe Dynamics and Control Technology division which consists of three groups:

• The Dynamics & Control group chaired by Prof. Dr. H. Nijmeijer• The Control Systems Technology group headed by Prof.Dr.Ir. M. Steinbuch and

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• The Hybrid & Network Systems group headed by Prof.Dr.Ir. W.P.M.H. Heemels.

Where possible the control activities, in particular teaching graduate and undergraduatecourses are combined.The DCT division offers in cooperation with the Systems Engineeringand Manufacturing Network groups the Master Track Dynamical Systems Design (DSD)and with colleagues from Electrical Engineering the 3TU Masters Systems and Control.Various other co-operations within the Department exist.

Eindhoven University of TechnologyLocal cooperation exists in particular with the Department of Biomedical Engineering,Department of Electrical Engineering (Control Systems group, Electro-mechanics and PowerElectronics group), Department of Physics and with the Department of Mathematics andComputing Science, Department of Industrial Engineering & Innovation Sciences.

National Research SchoolsBesides participation in DISC the DCT division also takes part in the National ResearchSchool EM (Engineering Mechanics).

National research institutesAs far as national research institutes are concerned, important co-operation exists with TNOin the areas of structural acoustics, plasma fusion processes, high-speed chattering;automotive power trains, active control of vehicle restraint systems, and vehicle dynamicsand control.We started with a co-operation with FOM, regarding the control issues for nuclearfusion. Also Agentschap NL funded projects “Falcon” and “Condor” are running in cooperationwith the Embedded Systems Institute and VanderLande and FEI as industrial partnersrespectively.

Industrial ContactsApart from the mentioned Falcon and Condor projects, co-operations with industrial partnersexist in the form of a number of PhD projects. With Océ, Philips Innovation Services, FEI-and ASML co-operations are running on advanced motion control. Other PhD and MScprojects are running with Bosch Transmissions, DTI, MI Partners, GCI, NXP, DAF, CCM,Bosch RexRoth Control, 2M, Vredestein and many others. The DCT division has beenactively involved in the innovation programs High Tech Automotive Systems (HTAS) andPointOne.

International co-operationWithin the EU 7th framework programmes the DCT division participates in a number ofEuropean Projects and Networks of Excellence. The HNS group is active in the FP7-EUprojects –WIDE (Decentralized and Wireless Control of Large-Scale Systems), andMOBY-DIC (Model-based synthesis of digital embedded control systems) and the Networkof Excellence HYCON2 (Hybrid Control Network). In the latter also the D&C group is active.

Also the RoboEarth project is a very successful EU project within the CST group.

In the year 2012 again a substantial number of students went abroad for their 14 weekstraining period, to various colleagues in the field (Australia, Detroit, Florida, Amherst, Aalborg,Berkeley, San Diego, Buffalo, Mexico, Japan, Singapore, Shanghai, etc.)

Brief descriptionResearch in the Dynamics and Control Technology Division

The general research objective of the Dynamics and Control Technology division is the studyof all aspects related to design, dynamics and control of high-performance mechanicalsystems. This covers the full range of topics such as design, modelling and analysis ofsystems, controller synthesis, signal and performance analysis. Practical and experimental

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Dynamics and Control Group, Control Systems Technology Group & Hybrid and Networked Systems

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validation is, where possible, part of the research.The increasing requirements on accuracy,energy consumption, environmental aspects, and human comfort for many technical productsurge the need for a better understanding, modelling, analysis, and synthesis to improveperformance. This requires an accurate modelling of the dynamics, preferably in a formsuitable for analysis and, where possible, also for the synthesis of control systems. Inparticular for mechanical systems such an approach is feasible and promising, due to theexisting broad experience in the modelling of these systems. In other physical disciplinesthe situation is different and first principles are usually not so well developed. The inherentdynamic properties of mechanical systems are physical and geometric nonlinearities, possiblya large number of degrees of freedom, interactions between the degrees of freedom and,often, a relatively high speed of operation. The combination of these properties easily leadsto difficulties in the modelling and analysis, and thereby also in bringing a model-basedcontroller design to a successful end in practice. This is the basic challenge throughout theresearch in the DCT-division, thereby aiming at methods and tools of practical value. Clearly,it is the ambition of the group to work at the forefront of present-day technology and to aimat a highly recognizable research stature within the department, but also within and outsidethe Netherlands.

The research in the Dynamics and Control Technology division comprises DISC-related,research in the following areas:

• Advanced Motion systems• Process-control• Automotive technology

Special Activities

The Dynamics and Control group and the Control Systems Technology group both were ratedat the 2009 QANU research assessment of Mechanical Engineering as excellent regardingquality, productivity, relevance and viability [5555].

The Hybrid and Networked Systems group was awarded a prestigious VICI grant in the personof Prof.Dr.ir. W.P.M.H. Heemels.The topic of the VICI grant is related to wireless and networkedcontrol systems.

Overview of results and future developments

Advanced Motion Systems

DISC projects

Decentralized and Wireless Control

W.P.M.H. HeemelsProjectleader:N. BauerParticipants:

DescriptionThe project aims at developing a novel rigorous and integrated framework for advancedcontrol and real-time optimization of large-scale and spatially distributed processes that


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exploits wireless sensor networks as a pervasive and highly reconfigurable informationgathering system, and at validating the approach on a real city water distribution system.

W.P.M.H. Heemels,Projectleader:T.M.P. GommansParticipants:

DescriptionA coherent and consistent paradigm for the design of embedded control systems is the goalof the project. A new methodology and associated tool chain will be developed encompassingin a unique framework the modelling of the physical process, design of the control algorithms,design of embedded circuits, and the assessment of the overall performance properties ofthe system. MOBY-DIC will achieve such an integrated design flow by developing a coremethodology based on “piecewise affine” representations, that at the same time (i) providea rather flexible structure for control functions, and (ii) are directly mapped into digitalarchitectures of small-size and low-power. The effectiveness of the developed embeddedcontrol design approach will be demonstrated by MOBY-DIC on a set of challengingapplications arising in the automotive industry.

Hybrid Control for Performance Improvement of Linear Motion Systems

N. van de Wouw, W.P.M.H. Heemels, H. NijmeijerProjectleader:B. van Loon, B. HunnekensParticipants:

DescriptionThe project aims for a fundamentally new perspective on high-performance control of linearmotion systems by exploiting hybrid controllers. The use of hybrid feedback control formsa major innovation that will enable substantial improvements in speed and accuracy ofindustrial motion systems such as wafer scanners, optical disc drives, electron microscopes,copiers and robots. Given the major economic value of these systems, especially in theNetherlands, the envisioned methods will have an enormous impact on high-tech motionindustries.

Advanced Motion and Vision Control.

H. Nijmeijer, P.P. JonkerProjectleader:R. Pieters, Zhenyu YeParticipants:

DescriptionIn motion systems, such as robots, pick-and-place machines and disc drives, the fundamentallimitation with respect to controlled performance is primarily due to causality. Because highaccuracy plant models are relatively easy to acquire, feed forward is used for servo taskswhereas the primary role of feedback is to suppress disturbances.The causality is expressedby the Bode sensitivity integral theorem, stating that a reduction of the low-frequentdisturbances will always be accompanied with an amplification of high frequent signals, e.g.measurements noise (the waterbed effect). This fundamental limitation is the driving forcefor a few lines of research: (i) further exploration of feed forward, including iterative learningcontrol, (ii) disturbance- and data-based control, i.e. using the internal model principle andthe principle of ‘machine-in-the-loop’ for adjusting the controller parameters on the basis ofon-line measurements, (iii) non-linear control of linear motion systems and, finally, (iv)



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multivariable control of mechanical systems. Related to these areas, also the possibleextension of frequency response analysis towards non-linear dynamics is addressed. Here,the group has a track-record with respect to identification and control of systems with friction.Several research projects have started in the area of vision in the loop. Various projectsaddress mechatronics research questions. One project is on the control of lightweight motionsystems with more actuators (and sensors) than rigid body degrees of freedom.The combinedmotion and vibration task and the co-operation with researchers from the mechanical designand the electrical domain make the project multidisciplinary and challenging. New activities,concentrate on medical robotics, in particular on minimally invasive robotic surgery systems.

Control of nonlinear mechanical systems

H. Nijmeijer, N. v.d. Wouw, D. KosticProjectleader:Ir. B. Besselink, M.Sc. S. Adinandra, M.Sc. J. PenaParticipants:

DescriptionIn the nonlinear control area emphasis lies on (i) controllability and observability ofnonsmooth/piecewise linear systems, (ii) stability and stabilization of nonlinear systems (iii)tracking control of underactuated systems. In the latter case one should think of systemswith less independent inputs than degrees of freedom. Typically this includes certainflexibilities in robot-like constructions as well as non holonomic systems like mobile robots,vehicles and ships. An illustrative example forms the RRR robot with only two actuatorsactive. Also, related results on observability of piecewise linear systems have been derived,and tested on the nonlinear beam in the DCT lab.

In the context of stability and stabilization of non smooth systems a number of results havebeen obtained, and demonstrated on a lab set up of a drill system.

Also an IOP project on human robot interaction in cooperation with the dept. of IndustrialEngineering and Innovation Sciences is ongoing.

Embedded Systems.

H. Nijmeijer, N. v.d. Wouw, D. Kostic,Projectleader:J. Caarls, S. AdinandraParticipants:

DescriptionIt is our vision that the further development of embedded dynamical systems is very importantfor modern state-of-the-art motion system design. Also, Event driven control is a ESI fundedprogram.We developed a dedicated motion control course for the TWAIO-OOTI (OntwerpersOpleiding Technische Informatica) education, including hands-on experimentation. For thenear future we foresee further activities with the ESI. In the same spirit we continued ourRobocup activities on midsize and humanoid robots. An ESI Project in cooperation withvanderLande entitled Falcon is running with as main theme the development of the distributioncenter of the future. A student team working on Tulip, a humanoid robot, for robot soccer isa valuable test bed for this type of embedded systems using a network of autonomousvehicles.


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Teleservice Robotics (TSR)

H. Nijmeijer, D. KosticProjectleader:A.A. Alvarez Aguirre, K. van Hee (Inf), M. van Osch (Inf)Participants:

DescriptionThe TSR project aims at the development of a robot for care. Partners in this project includeZuidzorg, a care organization.

Mobile robot structures

H. Nijmeijer, N. v.d. Wouw, D. KosticProjectleader:A.A. Alvarez Aguirre, J. Caarls, S. AdinandraParticipants:

DescriptionThis research line in the Dynamics & Control Technology Motion Laboratory has beeninitiated in 2000. Mobile, autonomous structures are very attractive for numerous applicationareas (space traveling, mail delivery, cleaning, inspections in hazardous environments etc.).Apart from mechanical design issues, these systems exhibit specific control challenges,especially because the systems are often under actuated and accurate measurementinformation is not available. The aims for this research line are: (i) development of anexperimental set-up for validation of (theoretical) non-linear control concepts, (ii) developmentand validation of non-linear models, controllers, and observers, (iii) development of arepresentative demonstration object for mobile and under actuated mechanical structures.(iv) development of a test environment of autonomous guided vehicles (AGVs). Upcomingactivities in this direction is the activity regarding humanoid robotics under the 3TU-umbrella.Cooperation in this area exists with TNO-Automotive regarding the control and a design ofa moving base (AGV) for the TNO-VEHIL lab in Helmond.

Synchronisation of non-linear systems

H. Nijmeijer, N. v.d. Wouw, D. KosticProjectleader:A.A. Alvarez Aguirre, J. Pena Ramirez, C.G. MurgiaParticipants:

DescriptionIn this project fundamental methods are investigated for the design of synchronizingcontrollers for various types of mechanical systems. Also, the robustness and stability ofsynchronized controllers are studied. Synchronization, or co-ordination as it is often called,is relevant in various mechanical systems, for instance in case two or more robots, ships orvehicles are asked to coordinate their motions. As an experimental test-bed the pizza steppersare used. Similarly mobile robots are used for experimental vehicle coordination andformation. Future research in this field will concentrate on synchronization of mobile robotsand AGVs. Also, network synchronization, i.e. the synchronization of a large ensemble ofsystems, is becoming an important research theme. Potential applications are in coupledelectromechanical systems for secure communication and coupled neural cells.

A project in cooperation with Computer Science (Prof. C. van Hee) called TeleserviceRobotics aims at the master slave control of a service robot for care. Industrial partners aswell as care organizations cooperate in this project.



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High-Performance Motion Control

M. Steinbuch, M.J.G. v.d. Molengraft, S. KoekebakkerProjectleader:R.M.A. van Herpen, R. Hoogendijk, M.J.C. RondeParticipants:

DescriptionFast and accurate positioning devices constitute an essential part of today’s high-techsystems, including IC manufacturing machines, printers, and data storage systems. Smartcontrol systems provide the key to achieve the limits of performance beyond the presentstate-of-the-art. The CST group is actively involved in both the development of relevanttheory and its successful application in high-tech industries. Recent and ongoingdevelopments include i) experimental modeling techniques, including identification for controland nonlinear identification, ii) advanced and robust control for complex multivariable systems,including over-actuated systems and iii) repetitive and iterative learning control.

Robotics for Care and Cure

M.J.G. v.d. MolengraftProjectleader:J. Elfring, R.J.M. Janssen, J. Lunenburg, C. Lopes MartinezParticipants:

DescriptionIn the area of robotics for Care we develop algorithms for a www for robotics (Roboearth)and we are actively participating in the Robocup initiative. The homecare robot Amigo hasbeen realized and is under continuous development with the aim to serve as a both versatileand affordable platform for real life testing in various Care scenarios. For Cure, Sofie is thefirst Dutch master slave for minimal invasive surgery. Furthermore, we focus on small scaleprecision robotics, such as the robot for eye surgery. An important challenge is the designof haptics control in order to achieve performance in both positioning and force feedback.

Process Control

DISC projects

Dynamic stabilization of combustion, suppression of acoustic instabilities

H. Nijmeijer, I. Lopez, P. de GoeyProjectleader:Ir. M. HoeijmakersParticipants:

DescriptionJointly with the Combustion Technology Group two projects on model based control forsuppression of acoustic instabilities in gas-fired household boilers and heaters are running.Experimental result are promising, and match well with earlier obtained simulation results.Several publications have been prepared on the subject.


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Pool boiling

H. Nijmeijer, M. SpeetjensProjectleader:M. de Baar, P.W.J.M. Nuij,Projectleader:R. v. GilsParticipants:M. van Berkel, M. LauretParticipants:

DescriptionA novel control algorithm for the dedicated control for thermal management – so called poolboiling – is developed in cooperation with the Energy Technology group at the Departmentof Mechanical Engineering.

Controlled Fusion

DescriptionA new and emerging field of our activities is controlled nuclear fusion. At the high plasmatemperatures and densities as required for an economical fusion reactor, tokamak plasmasare prone to various magnetohydrodynamic (MHD) instabilities which limit the the plasmaboundary, NTMs and sawteeth instabilities.Within these topics the range from theory, controloriented modelling, design of dedicated sensors and controllers is covered in co-operationwith FOM. Experiments have been carried out on TEXTOR, and are foreseen on MAST,AUG and Tore Supra.

Automotive Technology

DISC projects

Vehicle Dynamics Control and Tyres

H. Nijmeijer, I.J.M. Besselink, I. Lopez, N. v.d. WouwProjectleader:T. Hofman, A.G. de Jager, F. Willems, R. HuismanProjectleader:C. Wang, J. Ploeg, S. Öncü, S. Ran, J. WangParticipants:I. Aladagli, K. van Berkel, C.H.A. Criens, D.V. NgoParticipants:

DescriptionDuring the year a large number of students have been working on internal and external(TNO, DAF, LMS, Vredestein) master thesis projects. Several Bachelor projects and internaland external (BMW, DAF, Daimler-Chrysler, Goodyear, Intec) traineeships have beenperformed.

In the AES lab the Flat Plank Tyre Tester has been used for various experiments (e.g.motorcycle tyre measurements, stiffness measurements, cleat tests). A four wheel steeredvehicle has been obtained from TNO and several students have been working on a designof a suitable controller for this vehicle.Vehicle and truck powertrain experiments are possibleusing the controllable large drum in the automotive lab. Also tire test experiments can becone on the large drum at realistic vehicle velocities.

Research has been done in three main areas: tire modeling, truck modeling and vehiclecontrol. A PhD student is working in cooperation with DAF and TNO on truck modeling andactive cabine control. Extensive research is initiated around cooperate driving in the frame



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of a HTAS project Connect and Drive and in cooperation with TNO and is continued invarious ways. Since 2010 the DC group has developed an electric LUPO EL as an electrictest vehicle for advanced study on energy usage of electric vehicles.

Finally, for the TUE Formula Student Racing Team various student projects are done as toimprove the vehicle’s performance.

Automotive Powertrains

DescriptionDriven by stringent legislation for CO2 and pollutant emissions, the automotive industryfaces enormous challenges to find an optimal, cost-efficient balance between drivability andenergy efficiency within the boundaries set by emission legislation. Hybridization of automotivepowertrains leads to challenging questions on topology design and energy managementsystems. Also the research on slip control of Continously Variable Transmissions (CVT) andnew concepts for hybrid and electrical drivetrains for passenger cars and commercial vehiclesis part of the research. Furthermore, the introduction of advanced low-emission engineconcepts require closed-loop combustion control systems to increase the stable operatingrange, to enhance transient performance, and to realize smooth switching between variousmodes. Ultimately, this research is heading towards integrated powertrain control, whereenergy and emission management of the overall powertrain is fully integrated.

Publications

Book chapters/parts

Heemels, W.P.M.H. (Ed.). (2012). Automatica.Schutter B. de, Ploeg J., Baskar L.D., Naus G.J.L. & Nijmeijer H. (2012). Hierarchical, intelligent

and automatic controls. In A. Eskandarian (Ed.), Handbook of Intelligent Vehicles (pp.81-116). London: Springer.

Steinbuch, M. , Molengraft van de R., Hofman T. (AE Mech) (Ed.). (2012). Mechatronics.


Aangenent, W.H.T.M., Heemels, W.P.M.H., Molengraft, M.J.G. van de, Henrion, D. & Steinbuch,M. (2012). Linear control of time domain constrained systems. Automatica, 48(5), 736-746.

Bauer, N.W., Maas, P.J.H. & Heemels, W.P.M.H. (2012). Stability analysis of networked controlsystems : a sum of squares approach. Automatica, 48(8), 1514-1524.

Berkel, K. van, Hofman, T., Vroemen, B.G. & Steinbuch, M. (2012). Optimal control of amechanical-hybrid powertrain. IEEE Transactions on Vehicular Technology, 61(2),485-497.

Berkel, K. van, Römers, L.H.J., Vroemen, B.G., Hofman, T. & Steinbuch, M. (2012). Performancesimulations of a low-cost hybrid powertrain with large fuel savings. International Journalof Powertrains, 1(4), 377-395.

Bolder, J.J., Witvoet, G., Baar, M.R. de, Wouw, N. van de, Haring, M.A.M., Westerhof, E.,Steinbuch, M. & Doelman, N.J. (2012). Robust sawtooth period control based on adaptiveonline optimization. Nuclear Fusion, 52(7), 1-16.

Comaschi, F., Genuit, B.A.G., Oliveri, A., Heemels, W.P.M.H. & Storace, M. (2012). FPGAimplementations of piecewise affine functions based on multi-resolution hyperrectangularpartitions. IEEE Transactions on Circuits and Systems I: Regular Papers, 59(12),2920-2933.


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Dijk N.J.M. van, Wouw N. van de, Doppenberg E.J.J., Oosterling J.A.J. & Nijmeijer H. (2012).Robust active chatter control in the high-speed milling process. IEEE Transactions onControl Systems Technology, 20(4), 901-917.

Donkers, M.C.F. & Heemels, W.P.M.H. (2012). Output-based event-triggered control withguaranteed L_infty-gain and improved and decentralised event-triggering. IEEETransactions on Automatic Control, 57(6), 1362-1376.

Donkers, M.C.F., Heemels, W.P.M.H., Bernardini, D., Bemporad, A. & Shneer, V. (2012).Stability analysis of stochastic networked control systems. Automatica, 48(5), 917-925.

Donkers, M.C.F., Tabuada, P. & Heemels, W.P.M.H. (2012). Minimum attention control forlinear systems. Discrete Event Dynamic Systems, 22, 1-22.

Genuit, B.A.G., Lu, L. & Heemels, W.P.M.H. (2012). Approximation of explicit model predictivecontrol using regular piecewise affine functions : an input-to-state stability approach. IETControl Theory & Applications, 6(8), 1015-1028.

Gils R.W. van, Speetjens M.F.M., Zwart H.J. & Nijmeijer H. (2012). Feedback stabilisation ofa two-dimensional pool-boiling system by modal control. International Journal of ThermalSciences, 61, 38-49.

Han, L., Camlibel, M.K., Pang, J.S. & Heemels, W.P.M.H. (2012). A unified numerical schemefor linear-quadratic optimal control problems with joint control and state constraints.Optimization Methods and Software, 27(4-5), 761-799.

Heertjes M.F. & Nijmeijer H. (2012). Self-tuning of a switching controller for scanning motionsystems. Mechatronics, 22, 310-319.

Hennen, B.A., Lauret, M., Hommen, G., Heemels, W.P.M.H., Baar, M.R. de & Westerhof, E.(2012). Nonlinear control for stabilization of small neoclassical tearing modes in ITER.Nuclear Fusion, 52(12), 1-14.

Hommen, G., Baar, M.R. de, Citrin, J., Blank, H.J. de, Voorhoeve, R.J., Bock, M.F.M. de &Steinbuch, M. (2012). A fast, magnetics-free flux surface estimation and q-profilereconstruction algorithm for feedback control of plasma profiles. Plasma Physics andControlled Fusion, 55, 025007-1/11.

Hoogendijk, R., Molengraft, M.J.G. van de & Steinbuch, M. (2012). Data-based control oflightweight high-precision motion systems. Mikroniek, 2012(5), 22-27.

Keulen, T.A.C. van, Mullem, D. van, Jager, Bram de, Kessels, J.T.B.A. & Steinbuch, Maarten(2012). Design, implementation, and experimental validation of optimal power split controlfor hybrid electric trucks. Control Engineering Practice, 20(5), 547-558.

Lei C., Eenennaam E.M. van, Klein Wolterink W., Ploeg J., Karagiannis G. & Heijenk G.J.(2012). Evaluation of CACC string stability using SUMO, Simulink and OMNeT++.EURASIP Journal on Wireless Communications and Networking, 116, 1-12.

Meulen, S.H. van der, Jager, Bram de, Veldpaus, F.E., Noll, E. van der, Sluis, F. van der &Steinbuch, M. (2012). Improving continuously variable transmission efficiency withextremum seeking control. IEEE Transactions on Control Systems Technology, 20(5),1376-1383.

Ngo, D.V., Hofman, T., Steinbuch, M. & Serrarens, A.F.A. (2012). Optimal control of the gearshiftcommand for hybrid electric vehicles. IEEE Transactions on Vehicular Technology, 61(8),3531-3543.

Pavlov A.V. & Wouw N. van de (2012). Steady-state analysis and regulation of discrete-timenonlinear systems. IEEE Transactions on Automatic Control, 57(7), 1793-1798.

Rijlaarsdam, D.J., Oomen, T.A.E., Nuij, P.W.J.M., Schoukens, J. & Steinbuch, Maarten (2012).Uniquely connecting frequency domain representations of given order polynomialWiener-Hammerstein systems. Automatica, 48(9), 2381-2384.



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Shladover S., Ploeg J., Nijmeijer H. & Wouw N. van de (2012). Introduction to the special issueon the 2011 Grand Cooperative Driving Challenge. IEEE Transactions on IntelligentTransportation Systems, 13(3), 989-993.

Steur E., Oguchi T., Leeuwen C. van & Nijmeijer H. (2012). Partial synchronization in diffusivelytime-delay coupled oscillator networks. Chaos, 22(043144).

Wouw N. van de, Neši D. & Heemels W.P.M.H. (2012). A discrete-time framework for stabilityanalysis of nonlinear networked control systems. Automatica, 48(6), 1144-1453.

Wouw, N. van de, Neši , D. & Heemels, W.P.M.H. (2012). A discrete-time framework for stabilityanalysis of nonlinear networked control systems. Automatica, 48(6), 1144-1453.

Yurtseven, E., Heemels, W.P.M.H. & Camlibel, M.K. (2012). Disturbance decoupling of switchedlinear systems. Systems and Control Letters, 61(1), 69-78.


Bauer, N.W., Donkers, M.C.F., Wouw, N. van de & Heemels, W.P.M.H. (2012). Decentralizedstatic output-feedback control via networked communication. In Proceedings of theAmerican Control Conference (ACC 2012), 27-29 June 2012, Montreal, Canada.

Bauer, N.W., Loon, S.J.L.M. van, Donkers, M.C.F., Wouw, N. van de & Heemels, W.P.M.H.(2012). Networked control systems toolbox : robust stability analysis made easy. InProceedings of the the 3rd IFAC Workshop on Distributed Estimation and Control inNetworked Systems, September 14-15, 2012, Santa Barbara, California. Oxford:Pergamon.

Belleter D.J.W., Nijmeijer H., Breu D.A. & Fossen T.I. (2012). Nonlinear observer design forparametric roll resonance. In N. Themelis, A.D. Paprikolaou & K.J. Spyrou (Eds.),Proceedings on Stability of Ships and Ocean Vehicles, 23-28 August 2012, Athens,Greece. Athens: National Technical University.

Berkel, K. van, Rullens, S.C.A., Hofman, T., Vroemen, B.G. & Steinbuch, Maarten (2012).Analysis of optimal mechanical-hybrid powertrain topologies. In Proceedings of the IFACWorkshop on Engine and Powertrain Control, Simulation and Modeling (ECOSM 12),23-25 October 2012, Rueil-Malmaison, France (pp. 61-68).

Berkel, M. van, Witvoet, G., Baar, M.R. de, Nuij, P.W.J.M., Morsche, H.G. ter & Steinbuch,Maarten (2012). Real-time period determination for relaxation oscillators using wavelets.In Proceedings of the American Control Conference (ACC 2012), 27-29 June 2012,Montreal, Canada. Piscataway: IEEE.

Biemond, J.J.B., Wouw, N. van de, Heemels, W.P.M.H. & Nijmeijer, H. (2012). Tracking controlof mechanical systems with impacts. In Proceedings of the 2012 American ControlConference, June 27-29, Montréal, Canada (pp. 258-263). Washington: AACC.

Biemond, J.J.B., Wouw, N. van de, Heemels, W.P.M.H., Sanfelice, R.G. & Nijmeijer, H. (2012).Tracking control of mechanical systems with a unilateral position constraint inducingdissipative impacts. In Proceedings of the 51st IEEE Conference on Decision and Control(CDC), 10-13 December 2012, Maui, Hawaii, USA (pp. 4223-4228). Piscataway: IEEE.

Bolder, J.J., Lemmen, B.P., Koekebakker, S.H., Oomen, T.A.E., Bosgra, O.H. & Steinbuch, M.(2012). Iterative learning control with basis functions for media positioning in scanninginkjet printers. In Proceedings of the 2012 IEEE Multi-Conference on Systems and Control(MSC 2012), 3-5 October 2012, Dubrovnik, Croatia.

Bolder, J.J., Witvoet, G., Baar, M.R. de, Wouw, N. van de, Haring, M.A.M., Westerhof, E.,Doelman, N.J. & Steinbuch, M. (2012). Robust adaptive control of the sawtooth instabilityin nuclear fusion. In Proceedings of the 2012 American Control Conference (ACC 2012),27-29 June 2012, Montréal, Canada (pp. 5023-5028).


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Broek T.H.A. van den, Netten B. D., Hoedemaeker M. & Ploeg J. (2012). The experimentalsetup of a large field operational test for cooperative driving vehicles at the A270. InProceedings of the 13th International IEEE Conference on Intelligent TransportationSystems (ITSC 2010), 19-22 September 2010, Madeira Island, Portugal (pp. 198-203).Madeira Island, Portugal.

Criens, C.H.A., Willems, F.P.T. & Steinbuch, M. (2012). Under actuated air path control ofDiesel engines for low emissions and high efficiency (F2012-A4-024). In Proceedings ofFISITA 2012 World Automotive Congress, 27-30 november 2012, Beijing, China Vol.189. Lecture Notes in Electrical Engineering (pp. 725-738). SAE-China and FISITA.

Dries, S. van den, Elfring, J., Molengraft, M.J.G. van de & Steinbuch, M. (2012). Probabilisticmultiple hypothesis reasoning in robotics. In H. Stigter & T. van den Boom (Eds.), 31thBenelux Meeting on Systems and Control, Book of Abstracts, 27-29 March 2012, Heijen,Netherlands (pp. 112). Wageningen: Wageningen University - Biometris.

Dries, S. van den, Elfring, J., Molengraft, M.J.G. van de & Steinbuch, M. (2012).World modelingin robotics : probabilistic multiple hypothesis anchoring. In Abstract presented at theWorkshop on semantic perception and mapping for knowledge-enabled service robotics(ICRA 2012), May 2012, Saint Paul, USA.

Durango Galvan S.E., Heertjes M.F. & Dunand R. (2012). Plant enhancements in motionsystems by modal control. In Proceedings of the 2012 American Control Conference(ACC 2012), 27-29 June 2012, Montréal, Canada (pp. 5348-5353).

Elfring, J., Dries, S. van den, Molengraft, M.J.G. van de & Steinbuch, M. (2012). Task-basedworld model verification. In Proceedings of the workshop semantic perception and mappingfor knowledge-enabled service robotics (ICRA 2012), May 18, 2012, Saint Paul, USA.IEEE Service Center.

Elfring, J., Dries, S. van den, Molengraft, M.J.G. van de & Steinbuch, M. (2012).World modelingin robotics. In H. Stigter & T. van den Boom (Eds.), Abstract presented at the 31th BeneluxMeeting on Systems and Control, 27-29 March 2012, Heijden, Netherlands (pp. 133).

Gommans, T.M.P., Heemels, W.P.M.H., Bauer, N.W. & Wouw, N. van de (2012).Compensation-based control for lossy communication networks. In Proceedings of theAmerican Control Conference (ACC 2012), 27-29 June 2012, Montreal, Canada (pp.2854-2859). Piscataway: IEEE Service Center.

Guerreiro Tome Antunes, D.J., Heemels, W.P.M.H., Hespanha, J.P. & Silvestre, C. J. (2012).Scheduling measurements and controls over networks, part I : Rollout strategies forprotocol design. In Proceedings of the American Control Conference (ACC 2012), 27-29June 2012, Montreal, Canada. Piscataway: IEEE Service Center.

Guerreiro Tome Antunes, D.J., Heemels, W.P.M.H., Hespanha, J.P. & Silvestre, C. J. (2012).Scheduling measurements and controls over networks, part I I: Rollout strategies forsimultaneous protocol and controller design. In Proceedings of the American ControlConference (ACC 2012), 27-29 June 2012, Montreal, Canada. Piscataway: IEEE ServiceCenter.

Heertjes M.F. & Temizer B. (2012). Data-based control tuning in master-slave systems. InProceedings of the 2012 American Control Conference (ACC 2012), 27-29 June 2012,Montréal, Canada (pp. 2461-2466).

Hoogendijk, R., Molengraft, M.J.G. van de & Steinbuch, M. (2012).Transfer-function-data-basedcomputation of closed-loop poles for lightly damped MIMO systems. In H. Stigter & T.van den Boom (Eds.), Book of abstracts of the 31th Benelux Meeting on Systems andControl, March 27-29, 2012, Heijen, The Netherlands (pp. 130-130). Wageningen:Wageningen University.



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Hoogendijk, R., Molengraft, Rene van de & Steinbuch, M. (). Data-based control design methodsfor lightweight high-precision motion systems. In Abstract presentend at the firstDSPE-Conference 2012, 4-5 September 2012, Deurne. Deurne: DSPE - Dutch Societyfor Precision Engineering.

Hunnekens B.G.B., Haring, M.A.M., Wouw N. van de & Nijmeijer H. (2012). Steady-stateperformance optimization for variable-gain motion control using extremum seeking. InProceedings of the 51st IEEE Conference on Decision and Control (CDC 2012), 10-13December 2012, Maui, Hawai (pp. 3796-3801). Piscataway: IEEE.

Hunnekens B.G.B., Wouw N. van de & Nijmeijer H. (2012). Variable gain motion control fortransient performance improvement. In Proceedings of the 2012 American ControlConference (ACC), june 27-29, Montreal, Canada (pp. 2467-2472). Montreal, Canada:IEEE.

Janssen, R.J.M., Molengraft, M.J.G. van de & Steinbuch, M. (2012). An update on the RoboEartharchitecture. In H. Stigter (Ed.), 31th Benelux Meeting on Systems and Control, 27 March- 29 March 2012, Heijden, Netherlands, book of abstracts. Wageningen, Netherlands.

Janssen, R.J.M., Molengraft, M.J.G. van de, Steinbuch, M., Di Marco, D., Zweigle, O. & Levi,P. (). A proposal for a global task planning architecture using the RoboEarth cloud basedframework. In F. Py & D. Musliner (Eds.), Proceedings of the 22nd InternationalConference on Automated Planning and Scheduling : Workshop on Planning and PlanExecution for Real-World Systems: Principles and Practices (PlanEx), June 25-29 2012,Atibaia, Brazil (pp. 51-55).

Lauret, M., Felici, F.A.A., Witvoet, G., Goodman, T.P., Vandersteen, G., Westerhof, E.,Steinbuch, M., Sauter, O. & Baar, M.R. de (2012). A new mechanism for sawtooth periodcontrol. In E. Westerhof & P.W.J.M. Nuij (Eds.), EC-17 – 17th Joint Workshop on ElectronCyclotron Emission and Electron Cyclotron Resonance Heating, 7-10 May 2012, Deurne,The Neherlands (pp. 02008-1-02008-2). EPJ.

Loon, S.J.L.M. van, Donkers, M.C.F., Wouw, N. van de & Heemels, W.P.M.H. (2012). Stabilityanalysis of networked control systems with periodic protocols and uniform quantizers. InProceedings of the 4th IFAC Conference on Analysis and Design of Hybrid Systems(ADHS 12), 6-8 June 2012, Eindhoven, The Netherlands. Oxford: Pergamon.

Lopez Martinez, C.A., Molengraft, M.J.G. van de & Steinbuch, M. (2012). High performanceand stable teleoperation under bounded operator and environment dynamics. InProceedings of the 10th International IFAC Symposium on Robot Control (SYROCO2012), 5-7 September 2012, Dubrovnik, Croatie.

Lopez Martinez, C.A., Molengraft, M.J.G. van de & Steinbuch, M. (2012). Robust performancecontrol design for bilateral teleoperation under time-varying bounded operator andenvironment dynamics. In Proceedings of the 2012 American Control Conference (ACC2012), 27-29 June 2012, Montréal, Québec, Canada (pp. 3465-3470).

Lunenburg, J.J.M., Molengraft, M.J.G. van de & Steinbuch, M. (2012). ROP: developing arobotic open platform. In H. Stigter & T. van den Boom (Eds.), Abstract presented at the31st Benelux Meeting on Systems and Control, March 27-29 2012, Heijen, TheNetherlands. Wageningen: Wageningen University - Biometris.

Oliveri, A., Barcelli, D., Bemporad, A., Genuit, B.A.G., Heemels, W.P.M.H., Poggi, T., Rubagotti,M. & Storace, M. (2012). MOBY-DIC : a Matlab toolbox for circuit-oriented design ofexplicit MPC. In Proceedings of the 4th IFAC Nonlinear Model Predictive ControlConference (NMPC'12), 23 - 27 August 2012, Noordwijkerhout, The Netherlands.

Oncu, S., Wouw, N. van de, Heemels, W.P.M.H. & Nijmeijer, H. (2012). String stability ofinterconnected vehicles under communication constraints. In Proceedings of the 51stIEEE Conference on Decision and Control (CDC 2012), 10-13 December 2012, Maui,Hawai (pp. 2459-2464). Piscataway: IEEE.


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Oomen, T.A.E., Herpen, R.M.A. van, Quist, S., Wal, Marc van de, Bosgra, O.H. & Steinbuch,Maarten (2012). Next-Generation Wafer Stage Motion Control: Connecting SystemIdentification and Robust Control. In Proceedings of the 2012 American ControlConference, 27-29 Juni 2012, Montreal, Canada (pp. 2455-2460). Montreal, Canada.

Ploeg J., Gietelink O.J. & Verburg D.J. (2006). Experimental evaluation of acommunication-based cooperative driving algorithm. In Proceedings of the 13th WorldCongress and Exhibition on Intelligent Transport Systems (ITS World 2006), 8-12 October2006, London, United Kingdom (pp. 1-8).

Postoyan, R., Wouw, N. van de, Nesic, D. & Heemels, W.P.M.H. (2012). Emulation-basedtracking solutions for nonlinear networked control systems. In Proceedings of the 51stIEEE Conference on Decision and Control (CDC 2012), 10-13 December 2012, Maui,Hawai (pp. 740-745). Piscataway: IEEE.

Reeven, V. van, Hofman, T., Huisman, R. & Steinbuch, M. (2012). Extending energymanagement in hybrid electric vehicles with explicit control of gear shifting and start-stop.In Proceedings of the American Control Conference, June 27-29, 2012, Montreal, Canada.Piscataway: IEEE.

Rijlaarsdam, D.J., Oomen, T.A.E., Nuij, P.W.J.M., Schoukens, J. & Steinbuch, Maarten (2012).New connections between frequency response functions for a class of nonlinear systems.In M. Kinnaert (Ed.), Proceedings of the 16th IFAC Symposium on System Identification,11-13 July 2012, Brussels (pp. 280-285). S.l.: IFAC.

Ronde, M.J.C., Molengraft, M.J.G. van de & Steinbuch, M. (2012). Model-based feedforwardfor inferential motion systems, with application to a prototype lightweight motion system.In Proceedings of the 2012 American Control Conference, June 27-29, Montréal, Canada(pp. 5324-5329).

Ronde, M.J.C., Schneiders, M.G.E., Molengraft, M.J.G. van de, Haas, D. de & Steinbuch, M.(2012). Spatial feedforward for over-actuated flexible motion systems. In R. Scheidl & B.Jakoby (Eds.), The 13th Mechatronics Forum International Conference, 17-19 September,Linz, Austria (pp. 254-260). Linz: Trauner Verlag.

Rüffer B.S., Wouw N. van de & Mueller M. (2012). From convergent dynamics to incrementalstability. In Proceedings of the 51st IEEE Conference on Decision and Control (CDC2012), 10-13 December 2012, Maui, Hawai (pp. 2958-2963). Piscataway: IEEE.

Sadowska A.D., Kostic D., Wouw N. van de, Huijberts H.J.C. & Nijmeijer H. (2012). Distributedformation control of unicycle robots. In Proceedings of the 2012 International Conferenceon Robotics and Automation (ICRA), May 14-18, 2012, St. Paul, Minnesota (pp.1564-1569). Piscataway: IEEE Service Center.

Sande T.P.J. van der, Besselink I.J.M. & Nijmeijer H. (2012). Steer-by-Wire: A Study into theBandwidth and Force Requirements. In Presentation at the 11th international symposiumon advanced vehicle control (AVEC '12), September 9-12 2012, Seoul, Korea.

Silvas, E., Hofman, T. & Steinbuch, M. (2012). Review of optimal design strategies for hybridelectric vehicles. In IFAC Workshop on Engine and Powertrain Control, Simulation andModeling, 23-25 October 2012 (pp. 77-84). Les Rencontres Scientifiques d'IFP Energiesnouvelles Rueil-Malmaison, Paris, France.

Silvas, E., Hofman, T. & Steinbuch, M. (2012). Towards integrated vehicle system design:electrification of components. In Fifteenth Engineering Mechanics Symposium. Lunteren,The Netherlands.

Silvas, E., Hoogendijk, R., Aangenent, W.H.T.M., Wal, M.M.J. van de & Steinbuch, M. (2012).Modal decoupling of a lightweight motion stage using algebraic constraints on thedecoupling matrices. In Proceedings of the 31st Benelux Meeting on Systems and Control,27-29 march 2012, Heijden, the Netherlands (pp. 166). Heijden, the Netherlands.



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Wouw N. van de, Haring M.A.M. & Nesic D. (2012). Extremum-seeking control for periodicsteady-state response optimization. In Proceedings of the 51st IEEE Conference onDecision and Control (CDC 2012), 10-13 December 2012, Maui, Hawai (pp. 1603-1608).Piscataway: IEEE.

Zutven P.W.M. van & Nijmeijer H. (2012). Balance of humanoid robots by proper foot placement.In Proceedings of the Dynamic Walking Conference, 21-24 May 2012, Pensacola, USA.

Zutven P.W.M. van & Nijmeijer H. (2012). Foot placement for balance in planar bipeds withpoint feet. In Hans Stigter & Ton van den Boom (Eds.), 31st Benelux Meeting on Systemsand Control, March 27-29, 2012, Heijden, the Netherlands, Book of Abstracts (pp. 40-40).Wageningen, Netherlands: Wageningen University - Biometris.

Zutven P.W.M. van, Dalen S.J., Assman T.M., Caarls J., Cilli C., Aarts M.A.P., Boshoven T.P.M.,Mironchyk P., Ilhan E. & Nijmeijer H. (2012). Tech United Eindhoven RoboCup adult sizehumanoid team description 2012. In Proceedings of RoboCup 2012, Symposium papersand Team Description papers, 18-24 June 2012, Mexico City, Mexico (pp. 1-8). MexicoCity: RoboCup.

Zutven, P.W.M. van, Kostic, D. & Nijmeijer, H. (2012). Foot placement for planar bipeds withpoint feet. In Proceedings of the IEEE International Conference on Robotics andAutomation (ICRA), 14-18 May 2012, Saint Paul, USA.

Ph.D. theses

B. Besselink PhD. Thesis, Model reduction for nonlinear control systems 2012, TU/e Advisors:H. Nijmeijer Co-advisor: I.J.M. Besselink

D. Rijlaarsdam PhD. Thesis, Frequency domain based performance optimization of systemswith static nonlinearities, 2012, TU/e Advisors: M. Steinbuch Co-advisor: P.W.J.M. Nuij

R.W. van Gils PhD.Thesis, Feedback stabilization of Pool-Boiling systems, 2012, TU/e Advisors:H. Nijmeijer Co-advisor: M.F.M. Speetjens

S. Adinandra PhD. Thesis, Hierarchical Coordination Control of Mobile Robots 2012, TU/eAdvisors: H. Nijmeijer Co-advisor:

S.K. Ravensbergen PhD. Thesis, Adaptive Optics for Extreme Ultravoilet Lithography 2012,TU/e Advisors: M. Steinbuch Co-advisor: P.C.J.N. Rosielle

V.D. Ngo PhD.Thesis, Gear shift Strategies for Automotive Transmissions 2012, TU/e Advisors:M. Steinbuch Co-advisor: T. Hofman

M.Sc. theses

Abbasi, A., Heck, D.J.F. & Nijmeijer, H. (2012). Task space manipulator control for unilateralteleoperation. (D&C 2012.061). Eindhoven: Eindhoven University of Technology.

Abbasi, A., Nijmeijer, H. & Heck, D.J.F. (2012). Haptic long distance telemanipulation. (D&C2012.011). Eindhoven: University of Technology.

Alleleijn, J., Steinbuch, M., Baar, M.R. de & Berkel, M. van (2012). Detection of small sawtoothperiods on TCV using real-time wavelet maxima analysis. (CST 2012.089). Eindhoven:Eindhoven, University of Technology.

Altgassen, D., Molengraft, M.J.G. van de, Hoogendijk, R., Pancras, W.C.M. & Steinbuch, M.(2012). Generic MIMO decoupling for industrial control : design of a tool. (CST 2012.032).Eindhoven: Eindhoven, University of Technology.

Arts, R.R.M.J.W., Willems, F.P.T. & Steinbuch, M. (2012). Effect of in-cylinder pressure sensorbehavior on Diesel engine performance for Closed-loop Combustion Control. (CST2012.045). Eindhoven: Eindhoven, University of Technology.

Assman, T.M., Zutven, P.W.M. van & Nijmeijer, H. (2012). Humanoid push recovery steppingin experiments and simulations. (D&C 2012.059). Eindhoven: University of Technology.


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Backx, E.A., Hofman, T. & Steinbuch, M. (2012). Preliminary design considerations for the"Dutch Innovator" (hybrid-) electric drivetrain. (CST 2012.109). Eindhoven: EindhovenUniversity of Technology.

Baelemans, J.A.J., Blanke, M., Galeazzi, R. & Nijmeijer, H. (2012). Ship autopilot and rudderroll damping using L1 adaptive control. (D&C 2012.019). Eindhoven: Eindhoven Universityof Technology.

Bajonero Canonico, E., Steinbuch, M. & Koekebakker, S.H. (2012). New robust delay-variablerepetitive controller. (CST 2012.017). Eindhoven: Eindhoven University of Technology.

Barradas Berglind, J.D.J., Gommans, T.M.P. & Heemels, W.P.M.H. (2012). Self-triggeredcontrol for constrained discrete-time LTI systems. (H&NS 2012.003). Eindhoven:Eindhoven, University of Technology.

Baten, J.H., Steinbuch, M., Koekebakker, S.H. & Bolder, J.J. (2012). ILC applied for intelligentwide format media handling. (CST 2012.070). Eindhoven: Eindhoven University ofTechnology.

Beek, H. van, Nijmeijer, H., Limpens, M.P.M.A. & Fey, R.H.B. (2012). Observer basedtemperature reconstruction for determining thermomechanical deformations: Simulationsand experiments. (D&C 2012.062). Eindhoven: University of Technology.

Belleter, D.J.W., Nijmeijer, H. & Fossen, T.I. (2012). Nonlinear observability and observer designfor parametric roll. (D&C 2012.022). Eindhoven: University of Technology.

Bhandary, D.P., Steinbuch, M., Hofman, T. & Aladagli, I. (2012). System identification of apushbelt CVT variator : a literature survey. (CST 2012.114). Eindhoven: EindhovenUniversity of Technology.

Biemond, J.J.B., Wouw, N. van de, Heemels, W.P.M.H., Sanfelice, R.G. & Nijmeijer, H. (2012).Tracking control of mechanical systems with a unilateral position constraint inducingdissipative impacts. (D&C 2012.039). Eindhoven: Eindhoven University of Technology.

Blanken, L., Evers, G., Naus, G.J.L., Molengraft, M.J.G. van de & Steinbuch, M. (2012). Analysisof the applicability of performance measures in the evaluation of surgical bilateralteleoperation systems. (CST 2012.059). Eindhoven: Eindhoven, University of Technology.

Boeren, F.A.J., Herpen, R.M.A. van, Oomen, T.A.E., Bosgra, O.H. & Steinbuch, M. (2012).Model-based control of lightweight motion systems : a literature survey. (CST 2012.028).Eindhoven: Eindhoven, University of Technology.

Boeren, F.A.J., Steinbuch, M., Bosgra, O.H., Heertjes, M.F., Oomen, T.A.E. & Herpen, R.M.A.van (2012). Multivariable weighting function design for performance enhancement of aflexible wafer stage. (CST 2012.029). Eindhoven: Eindhoven University of Technology.

Borgers, D.P., Lauret, M., Nuij, P.W.J.M., Baar, M.R. de & Steinbuch, M. (2012). Frequencyand phase tracking using Kalman filters. (CST 2012.036). Eindhoven: Eindhoven,University of Technology.

Bosma, G.A., Jager, A.G. de & Steinbuch, M. (2012). Seat belt control. (CST 2012.085).Eindhoven: Eindhoven, University of Technology. Bouten, J.T., Steinbuch, M., Rosielle,P.C.J.N. & Hendrix, R. (2012). Redesign of a 5-DoF haptic master device for roboticallyassisted eye surgery. (CST 2012.030). Eindhoven: Eindhoven University of Technology.

Bouwens, T., Hofman, T., Besselink, I.J.M. & Steinbuch, M. (2012). Design of a 4WD electricdrive train for a FSAE race car. (CST 2012.112). Eindhoven: Eindhoven University ofTechnology.

Bouwmans, H.C., Nijmeijer, H. & Zutven, P.W.M. van (2012). Gravity compensation for a bipedalhumanoid robot. (D&C 2012.017). Eindhoven: University of Technology.

Braat, T.M., Steinbuch, M., Hofman, T. & Reeven, V. van (2012). Analysis of the environmentinfluence on the energy estimation of a truck. (CST 2012.058). Eindhoven: EindhovenUniversity of Technology.



125

Breugel, L.C. van, Nijmeijer, H., Wouw, N. van de & Hunnekens, B.G.B. (2012). Analysis ofpiecewise linear variable gain controllers for linear motion systems. (D&C 2012.037).Eindhoven: University of Technology.

Briegel, M., Steinbuch, M., Molengraft, M.J.G. van de, Etman, L.F.P. & Janssen, R.J.M. (2012).Multi-agent Action Recognition and Prediction Using Support Vector Machines. (CST2012.068). Eindhoven: Eindhoven University of Technology.

Bulk, J.D.J.M. van den & Steinbuch, M. (2012). Active vibration control methods for disturbancerejection. (CST 2012.016). Eindhoven: Eindhoven, University of Technology.

Cerit, E., Steinbuch, M., Molengraft, M.J.G. van de & Lopez Martinez, C.A. (2012). Modelingand control of a steerable needle for minimally insasive surgery. (CST 2012.117).Eindhoven: Eindhoven University of Technology.

Clements, H.H., Steinbuch, M., Molengraft, M.J.G. van de, Pogromski, A.Y. & Naus, G.J.L.(2012). Performance evaluation and bilateral control of a dynamically coupled MIMOslave manipulator using PERR and KFF architectures. (CST 2012.037). Eindhoven:Eindhoven, University of Technology.

Coenen, S.A.M., Steinbuch, M., Molengraft, M.J.G. van de, Lunenburg, J.J.M. & Naus, G.J.L.(2012). Motion Planning for Mobile Robots - A Guide. (CST 2012.108). Eindhoven:Eindhoven, University of Technology.

Colak, S., Steinbuch, M., Jager, A.G. de & Maas, R.J.R. van der (2012). Detectability ofmechanical properties from calibration data. (CST 2012.076). Eindhoven: EindhovenUniversity of Technology.

Dalen, S.J., Zutven, P.W.M. van & Nijmeijer, H. (2012). A linear inverted pendulum walkimplemented on TUlip. (D&C 2012.015). Eindhoven: University of Technology.

Deenen, D.A., Steinbuch, M., Baar, M.R. de & Lauret, M. (2012). Bachelor eindproject : analysevan beschrijving en regelsysteem voor het niet-lineaire deurium-tritium kernfusiemodel.(CST 2012.088). Eindhoven: Eindhoven, University of Technology.

Dekkers, A.J.M. & Heemels, W.P.M.H. (2012). Model-based tracking control of a Rovio TMmobile robot. (HNS 2012.006). Eindhoven: Eindhoven University of Technology.

Denissen, J.W.C.J. & Steinbuch, M. (2012). Kinematic and dynamic modelling of a motionplatform. (CST 2011.090). Eindhoven: Eindhoven, University of Technology.

Derks, M., Nijmeijer, H. & Guay, M. (2012). Observability based model reduction and estimationfor flow systems. (D&C 2012.055). Eindhoven: University of Technology.

Derksen, T.J.J., Steinbuch, M. & Rosielle, P.C.J.N. (2012). Design an upgrade for TNO'spre-crash system. (CST 2012.087). Eindhoven: Eindhoven University of Technology.

Dierikx, S.M.F., Nijmeijer, H., Wouw, N. van de, Hof, P.M.J. Van den & Zijsling, D.H. (2012).Control of torsional vibrations in drilling systems using a model reduction strategy. (D&C2012.026). Eindhoven: University of Technology.

Dohmen, G.J.A., Steinbuch, M. & Rosielle, P.C.J.N. (2012). Mechanical design of a servicerobot torso for AMIGO V2.0. (CST 2012.031). Eindhoven: Eindhoven, Univeristy ofTechnology.

Dolk, V.S. & Steinbuch, M. (2012). Preliminary research : control of flexible launch vehicles.(CST 2012.002). Eindhoven: Eindhoven, University of Technology.

Dongen, P. van, Freeman, C., Nijmeijer, H. & Rogers, E. (2012). Optimal reference models of3D movements for stroke patients. (D&C 2012.013). Eindhoven: Eindhoven Universityof Technology.

Duisters, K.S., Steur, E. & Nijmeijer, H. (2012). Synchronization if Hindmarsh-Rose oscillatorsin time delayed networks. (D&C 2012.008). Eindhoven: Eindhoven University ofTechnology. Evers, F., Alvarez-Agguirre, A., Pieters, R.S. & Nijmeijer, H. (2012).Handwriting task for a 7-DOF robotic manipulator. (D&C 2012.041). Eindhoven: EindhovenUniversity of Technology.


126

Ebben, P.P., Steinbuch, M. & Post, W.J.A.E.M. (2012). Analysis of the swash plate movementsof a FCVP. (CST 2012.106). Eindhoven: Eindhoven University of Technology.

Eenink, B., Steinbuch, M. & Hofman, T. (2012). Objective design of a motion cueing algorithmfor a 7 DOF driving simulator. (CST 2012.093). Eindhoven: Eindhoven University ofTechnology.

Erp, G.A. van, Steinbuch, M. & Rosielle, P.C.J.N. (2012). Dynamic vacuum feedthrougt. (CST2012.050). Eindhoven: Eindhoven University of Technology.

Evers, G., Steinbuch, M., Molengraft, M.J.G. van de, Naus, G.J.L. & Weiland, S. (2012). Ahuman and task centered analysis of haptic feedback in robotic telesurgery. (CST2012.066). Eindhoven: Eindhoven University of Technology.

Fennis, F.H.G. & Steinbuch, M. (2012). Force measurement at the tip of a bevel tip needleusing FPI. (CST 2012.047). Eindhoven: Eindhoven Unversity of Technology.

Firooznia, A., Zwart, H.J., Wouw, N. van de & Ploeg, J. (2012). Controller design for stringstability of infinite vehicle strings. (D&C 2012.052). Eindhoven: Eindhoven University ofTechnology.

Geelen, M.J.A.J., Steinbuch, M., Molengraft, M.J.G. van de & Elfring, J. (2012). An extractabletask and robot specific world representation. (CST 2012.082). Eindhoven: EindhovenUniversity of Technology.

Geelen, P.J.M., Scott, S., Mumgaard, R., Bock, M.F.M. de & Steinbuch, M. (2012). Simulationof the motional stark effect on C-MOD using MSESIM and PERF. (CST 2012.097).Eindhoven: Eindhoven, University of Technology.

Geerts, E.G., Manzie, C., Kutadinata, M. & Steinbuch, M. (2012). Simulations of urban trafficwith an extremum seeking controller. (CST 2012.092). Eindhoven: Eindhoven Universityof Technology.

Gerrits, K.P., Molengraft, M.J.G. van de, Hoogendijk, R. & Steinbuch, M. (2012). Ball handlingsystem for tech united soccer robots. (CST 2012.072). Eindhoven: Eindhoven Universityof Technology.

Govindasamy Rajasekaran, C., Hofman, T., Marquenie, L. & Steinbuch, M. (2012). Analysisand modeling of a dry clutch system for a medium duty truck : internship report. (CST2012.054). Eindhoven: Eindhoven University of Technology.

Haansbergen, B., Lunenburg, J.J.M. & Steinbuch, M. (2012). Analyzing the workspace ofAMIGO. (CST 2012.018). Eindhoven: Eindhoven University of Technology.

Hanegraaf, A.K., Steinbuch, M., Molengraft, M.J.G. van de & Lopez Martinez, C.A. (2012).Reduction of conservatism in passivity-based control. (CST 2012.110). Eindhoven:Eindhoven University of Technology.

Heeren, A.M.W., Steinbuch, M. & Rosielle, P.C.J.N. (2012).The design of a suspension systemfor a surgical robot. (CST 2012.063). Eindhoven: Eindhoven University of Technology.

Heldens, G.M., Molengraft, M.J.G. van de & Steinbuch, M. (2012). Improving object positionestimation for a TechUnited Turtle. (CST 2012.044). Eindhoven: Eindhoven Universityof Technology.

Heldens, J.P., Molengraft, M.J.G. van de & Steinbuch, M. (2012). Robot disco. (CST 2012.074).Eindhoven: Eindhoven University of Technology.

Heuijerjans, M. & Steinbuch, M. (2012). Investigation of the repetitive process ILC. (CST2012.019). Eindhoven: Eindhoven University of Technology. Heuvel, J. van den &Steinbuch, M. (2012). Multitarget tracking and detection on AMIGO. (CST 2012.033).Eindhoven: Eindhoven University of Technology.

Hoedemaekers, E., Steinbuch, M., Jager, A.G. de & Marinkov, S. (2012). SRG vehicle chargingsystem. (CST 2012.055). Eindhoven: Eindhoven University of Technology.



127

Hoefsloot, A.V., Steinbuch, M. & Post, W.J.A.E.M. (2012). Reducing carbon-dioxide emissionsof the roadtransport sector in the port of Rotterdam : project (BEP) report. (CST 2012.061).Eindhoven: Eindhoven University of Technology.

Hoeks, J., Steinbuch, M. & Nijmeijer, H. (2012). Sensor and actuator selection in the control offlexible stages. (CST 2012.105). Eindhoven: Eindhoven University of Technology.

Jacobs, L., Sande, T.P.J. van der & Nijmeijer, H. (2012). Modeling of an anti-lock braking systemin Matlab-Simulink. (D&C 2012.003). Eindhoven: Eindhoven University of Technology.

Jansen, N.F., Steinbuch, M. & Molengraft, M.J.G. van de (2012). Analysis, modeling and controlof a haptic manipulator : McArm. (CST 2012.011). Eindhoven: Eindhoven University ofTechnology.

Jansen, S.E.P., Steinbuch, M., Molengraft, M.J.G. van de & Elfring, J. (2012). Appearanceprediction and active search using probabilistic relations. (CST 2012.083). Eindhoven:Eindhoven University of Technology.

Janssens, M., Steinbuch, M. & Rosielle, P.C.J.N. (2012). Design of a short stroke reluctanceactuator support structure for WS450. (CST 2012.101). Eindhoven: Eindhoven Universityof Technology.

Kiriouchine, V.I., Steinbuch, M., Baar, M.R. de & Lauret, M. (2012). Further development andvalidation of island phase observer for ASDEX Upgrade. (CST 2012.092). Eindhoven:Eindhoven University of Technology.

Klemm, W.P.A., Steinbuch, M., Hofman, T. & Berkel, K. van (2012). Optimal energy managementwith thermal effects of the engine. (CST 2012.052). Eindhoven: Eindhoven University ofTechnology.

Kremers, N.A.H., Nijmeijer, H., Aarts, J. & Wouw, N. van de (2012). Trajectory planning for ahigh-speed laser cutter. (D&C 2012.023). Eindhoven: University of Technology.

Kuijpers, B.B.M.F., Seykens, X.L.J., Willems, F.P.T. & Steinbuch, M. (2012). Development ofa parameter identification method for a control-oriented diesel engine combustion model.(CST 2012.073). Eindhoven: Eindhoven University of Technology.

Kuijpers, B.B.M.F., Steinbuch, M. & Willems, F.P.T. (2012). Development of a parameteridentification method for a control-oriented diesel engine combustion model. (CST2012.073). Eindhoven: Eindhoven University of Technology.

Kupper, F., Steinbuch, M. & Willems, F.P.T. (2012). Integrated powertrain cotrol for a Euro VIheavy duty diesel engine with waste heat recovery system. (CST 2012.090). Eindhoven:Eindhoven University of Technology.

Kupper, F., Willems, F.P.T., Cloudt, R. & Steinbuch, M. (2012). Integrated powertrain controlfor a Euro VI heavy duty diesel engine with waste heat recovery system. (CST 2012.090).Eindhoven: Eindhoven University of Technology.

Laarhoven, M. van & Steinbuch, M. (2012). Internship on wind turbine control (basics) atindustrial systems and control. (CST 2012.046). Eindhoven: Eindhoven University ofTechnology.

Lambregts, N., Steinbuch, M. & Hofman, T. (2012). Fuzzy-hybrid modelling based on a movingvariable window. (CST 2012.019). Eindhoven: Eindhoven University of Technology.

Lamers, M.H.M., Steinbuch, M. & Rosielle, P.C.J.N. (2012). Design of a continuous motioninkjet printer for full-color printing of cylindrical products. (CST 2012.024). Eindhoven:Eindhoven University of Technology.

Lepelaars, D.P.F. & Steinbuch, M. (2012). Controller re-design of planar motor system. (CST2012.091). Eindhoven: Eindhoven University of Technology.

Li (Ziyang), Z., Steinbuch, M., Molengraft, M.J.G. van de & Janssen, R.J.M. (2012). Planning,Execution and Monitoring in the RoboCup@Home General Purpose Service RobotChallenge. (CST 2012.118). Eindhoven: Eindhoven University of Technology.


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Li, Ziyang, Janssen, R.J.M., Molengraft, M.J.G. van de & Steinbuch, M. (2012). Planning,execution and monitoring in the RoboCup@Home general purpose servie robot challenge.(CST 2012.118). Eindhoven: Eindhoven University of Technology.

Lijster, G., Nijmeijer, H. & Ploeg, J. (2012). A radar-based, enhanced control algorithm forAdaptive Cruise Control. (D&C 2012.016). Eindhoven: University of Technology.

Liu, Z., Sande, T.P.J. van der, Besselink, I.J.M. & Nijmeijer, H. (2012). A study of feedbackinfluence on steering performance. (D&C 2012.064). Eindhoven: University of Technology.

Maldonado Reyes, J.E., Steinbuch, M., Hofman, T. & Aladagli, I. (2012). Analysis and modellingof a series continously variable transmission. (CST 2012.100). Eindhoven: EindhovenUniversity of Technology.

Maljaars, E., Steinbuch, M., Baar, M.R. de, Djordjevic, S. & Felici, F. (2012). Model predictivecontrol of safety factor profile in ITER hybrid mode. (CST 2012.080). Eindhoven:Eindhoven University of Technology.

Meegdes, K.J.C., Steinbuch, M. & Rosielle, P.C.J.N. (2012). Mechanical design of a device forcochlear implant procedures. (CST 2012.022). Eindhoven: Eindhoven University ofTechnology.

Meijl, E.W.P. van, Steinbuch, M., Molengraft, M.J.G. van de & Janssen, R.J.M. (2012). Anintegrated architecture for action execution and planning for domestic service robots.(CST 2012.081). Eindhoven: Eindhoven University of Technology.

Melief, T.J., Zutven, P.W.M. van & Nijmeijer, H. (2012). Leer een tweebenige robot lopen. (D&C2012.005). Eindhoven: University of Technology.

Metsemakers, P.M.G. & Steinbuch, M. (2012). Simulation design of passive dynamic bipedalwalkers. (CST 2012.041). Eindhoven: Eindhoven University of Technology.

Michielsen, T.J.T. & Steinbuch, M. (2012). Six DoF active vibration isolation. (CST 2012.001).Eindhoven: TU/e.

Moris, B. & Steinbuch, M. (2012). Modeling for control of a biped robot - AAU-BOT1 : anotherstap towards dynamic walking. (CST 2012.116). Eindhoven: Eindhoven University ofTechnology.

Nagarajan, P., Hofman, T., Vroemen, B.G. & Steinbuch, M. (2012). Experimental study onhydraulic actuation of CVT : using a small pump and buffer. (CST 2012.034). Eindhoven:Eindhoven University of Technology.

Nagarajan, P., Steinbuch, M. & Hofman, T. (2012). Realization of a realistic drive cycle simulationmethod. (CST 2012.094). Eindhoven: Eindhoven University of Technology.

Natris, R. de & Steinbuch, M. (2012). Ultra clean vacuum : building fundamental knowledge forAAE. (CST 2012.015). Eindhoven: Eindhoven University of Technology.

Nava Richardson, A.M., Steinbuch, M. & Jager, A.G. de (2012). Multiple model adaptive controlfor lighting application. (CST 2012.079). Eindhoven: Eindhoven University of Technology.Oene, E.M.P. van, Janssen, R.J.M., Molengraft, M.J.G. van de & Steinbuch, M. (2012).Simulation of a hexapodal robot. (CST 2012.012). Eindhoven: Eindhoven University ofTechnology.

Pan, L., Steinbuch, M. & Aladagli, I. (2012). Modelling of traction drive CVT's efficiency. (CST2012.075). Eindhoven: Eindhoven University of Technology.

Pérez Munoz, J.C., Baar, M.R. de, Hommen, G. & Steinbuch, M. (2012). Camera movementcompensation for real-time optical plasma boundary. (CST 2012.069). Eindhoven:Eindhoven University of Technology.

Peters, P.J., Rosielle, P.C.J.N., Poels, P. & Steinbuch, M. (2012). Syringe assembly : insertingthe hypodermic needle. (CST 2012.021). Eindhoven: Eindhoven University of Technology.

Ploegmakers, H., Ploeg, J. & Nijmeijer, H. (2012). Verbetering van versnellingsregelaar doormiddel van massaschattingsmethode : project cooperation adaptive cruis control versie4.0. (D&C 2012.045). Eindhoven: University of Technology.



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Raijmakers, P., Steinbuch, M. & Lunenburg, J.J.M. (2012). Getting AMIGO to grasp. (CST2012.042). Eindhoven: Eindhoven University of Technology.

Ritzen, P.J., Lammertse, P. & Nijmeijer, H. (2012). Improving the performance of theHapticMaster during human contact. (D&C 2012.054). Eindhoven: University ofTechnology.

Roebroek, E.J.W., Wouw, N. van de & Nijmeijer, H. (2012). Path following control of atractor-steered-trailer robot. (D&C 2012.058). Eindhoven: University of Technology.

Ruijter, L., Lee, T.H. & Steinbuch, M. (2012). Unmanned Aerial Vehicle (UAV) design. (CST2012.008). Eindhoven: Eindhoven University of Technology.

Rullens, S.C.A., Berkel, K. van, Hofman, T. & Steinbuch, M. (2012). Comparison of optimalmechanical-hybrid vehicle concepts. (CST 2012.027). Eindhoven: Eindhoven Universityof Technology.

Samplonius, R.J., Heck, D.J.F. & Nijmeijer, H. (2012). Regelen van de pizza robot. (D&C2012.042). Eindhoven: University of Technology.

Sanden, M.C.W. van de, Eichhorn, R.H.L., Boot, M.D., Willems, F.P.T., Jager, A.G. de,Steinbuch, M. & Ouwerkerk, H. (2012). Modeling an SI engine with WEDACS for controlpurposes. (CST 2012.013). Eindhoven: Eindhoven University of Technology.

Schepop, S. van de, Baar, M.R. de, Berkel, M. van & Steinbuch, M. (2012). Real time estimationof the heat diffusion coefficient X. (CST 2012.005). Eindhoven: Eindhoven University ofTechnology.

Schijndel, J. van, Heemels, W.P.M.H., Longo, S. & Genuit, B.A.G. (2012). Control ofenergy-harvesting gliders towards thermals: a nonlinear MPC approach. (H&NS 2012.005).Eindhoven: Eindhoven University of Technology.

Shukla, D.P., Box, S. & Nijmeijer, H. (2012). Investigation and implementation of controltechniques for a fluid temperature control unit. (D&C 2012.007). Eindhoven: Universityof Technology.

Shukla, D.P., Ploeg, J., Wouw, N. van de & Nijmeijer, H. (2012). Design and evaluation of amultiple vehicle look ahead platoon control system. (D&C 2012.071). Eindhoven: Universityof Technology.

Simon, A.S., Heemels, W.P.M.H., Bauer, N.W. & Loon, S.J.L.M. van (2012). Analysis of controllerimplementation on low-powered devices. (HNS 2012.002). Eindhoven: Eindhoven,University of Technology.

Spoelstra, M.P.A., Schlacher, K. & Nijmeijer, H. (2012). Position control of a rolling ball on agimbal supported plate. (D&C 2012.033). Eindhoven: University of Technology.

Teunissen van Manen, T., Molengraft, M.J.G. van de, Lunenburg, J.J.M., Hendrix, R. &Steinbuch, M. (2012). AMIGO II gripper : underactuated robot gripper. (CST 2012.074).Eindhoven: Eindhoven University of Technology.

Tienstra, T., Criens, C.H.A., Willems, F.P.T. & Steinbuch, M. (2012). Feedforward control oftransients in diesel engines. (CST 2012.025). Eindhoven: Eindhoven University ofTechnology.

Titulaer, R.H.M., Nevels, R., Hofman, T. & Steinbuch, M. (2012). Modeling thermal inertia inwaste heat recovery system. (CST 2012.053). Eindhoven: Eindhoven University ofTechnology.

Turan, O., Hofman, T., Purnot, T. & Steinbuch, M. (2012). Testing and control of actuatorsystems for twinspeed transmission. (CST 2012.020). Eindhoven: Eindhoven Universityof Technology.

Vardar, Y., Hoogendijk, R., Dijk, N. van & Steinbuch, M. (2012). Estimation of MIMO Closed-LoopPoles using Transfer Function Data. (CST2012.067). Eindhoven: Eindhoven Universityof Technology.


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Velden, B.J.C.H. van der, Alberding, M., Guzzella, L., Hofman, T. & Steinbuch, M. (2012).Steering control of semi-trailers : model-based vehicle dynamics control for rolloverprevention. (CST 2012.004). Eindhoven: Eindhoven University of Technology.

Verhaegh, J.L.C., Heemels, W.P.M.H. & Gommans, T.M.P. (2012). Extension and evaluationof model-based periodic event-triggered control. (H&NS 2012.007). Eindhoven: EindhovenUniversity of Technology.

Verstappen, R.J.L.M., Nijmeijer, H., Freeman, C.T. & Rogers, E. (2012). Tremor suppressionby FES using closed-loop control. (D&C 2012.010). Eindhoven: Eindhoven University ofTechnology.

Verstralen, G.J.T.J., Yeo, C. & Steinbuch, M. (2012). Torque ripple reduction for PMSM usingILC. (CST 2012.071). Eindhoven: Eindhoven University of Technology.

Voncken, J.M.R., Tomizuka, M. & Steinbuch, M. (2012). Intelligent power assistance for anelectrical bicycle. (CST 2012.051). Eindhoven: Eindhoven University of Technology.

Wijk, J. van, Herpen, R.M.A. van, Bosgra, O.H., Oomen, T.A.E., Fey, R.H.B., Wal, M.M.J. vande & Steinbuch, M. (2012). Increasing the performance of beyond-rigid-body systemsusing constrained H control. (CST 2012.026). Eindhoven: Eindhoven University ofTechnology.

Wijnhoven, M.L.J. & Steinbuch, M. (2012). Design of a real-time optimizing controller for theminimization of aerodynamic skin friction drag. (CST 2012.096). Eindhoven: EindhovenUniversity of Technology.

Wijnhoven, M.L.J. & Steinbuch, M. (2012). Design of an energy efficient reversal system formass-sliding motions. (CST 2012.095). Eindhoven: Eindhoven University of Technology.

Yurtseven, E., Camlibel, M.K. & Heemels, W.P.M.H. (2012). Controllability of a class of bimodaldiscrete-time piecewise linear systems. (HNS 2012.004). Eindhoven: Eindhoven Universityof Technology.

Zundert, J.C.D. van & Nijmeijer, H. (2012). Synthesis of piecewise linear variable gain controllersfor linear motion systems. (D&C 2012.021). Eindhoven: Eindhoven University ofTechnology.



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Eindhoven University of TechnologyDepartment of Electrical Engineering – Control Systems

General Information

AddressEindhoven University of Technology, Department of Electrical Engineering P.O. Box 513,5600 MB Eindhoven, Netherlands. Phone: 040–247 23 00. Fax. 040–243 45 82 @E–mail:[email protected]

Scientific staffProf.dr.ir. A.C.P.M. Backx, Prof.dr.ir. P.P.J. van den Bosch, Prof.dr.ir. P.M.J. Van den Hof,Prof.dr. S. Weiland, Prof.dr.ir. H.J. Bergveld, Prof.dr. W.M.J.M. Coene, Ing. W. Hendrix,Dr.ir. J.T.B.A. Kessels, Dr. M. Lazar, M.Sc., Dr.ir. C.M.M. van Lierop, Dr. L. Ozkan, M.Sc.,Dr. R. Toth

PhD studentsIr. J. Achterberg, Ir. C. Bikcora, H. Chen, M.Sc., C. Cochior, M.Sc., C. Ding, M.Sc., Ir. A.Doban, M. Ezzeldin, M.Sc., Ir. R. Gielen, Ir. R. Hermans, Ir. P. van der Hulst, E. InsuastyMoreno, MSc. A. Katalenic, M.Sc., Ir. M. Mutsaers, T.H. Pham, M.Sc., M.Siraj, MSc. V.Spinu, M.Sc., Ir. J. Stolte, N.Q. Tran, M.Sc., Ir. E. Tazelaar, A. Virag, M.Sc., Ir. K. Verkerk,Ir. J.A.W. Vissers

Temporary staff and postdocsDr. D. Piga Dr. N. Athanasopoulos

Cooperation withABB,APX (Amsterdam), ASML (Veldhoven), Assembleon, Bayer(Belgium/Germany), DAFTrucks, DSM, DTI, ECN (Petten), FEI (Eindhoven), Ford Research (Aachen), Ford (USA),Heliox, IPCOS Technology, ISPT, Kema (Arnhem), NXP, ORS (Italy), Océ (Venlo), PhilipsApTech, Philips Lighting, PPG Fiberglas, Proctor & Gamble

Prodrive (Eindhoven), REXAM (Dongen), Sasol (SA), Shell, SKF, SORG (Germany), TenneT(Arnhem), Thales (Hengelo), Tierl, TNO, TU Delft, Vereenigde Glasfabrieken.With partners in NoE HYCON and Hycon 2 and 7th FW EU projects E-Price and Autoprofit.

KeywordsModeling, identification, system analysis, control system synthesis, model reduction, predictivecontrol, spatial-temporal systems, distributed systems, automotive control, motion control,power systems, process control.

Brief description

PROGRAM POLICYThe domain of dynamic systems and control provides essential tools for the smart andhigh-performance operation of technical systems in a wide variety of technology domains.Model-based measurement, monitoring, control, optimization and adaptation are the keyingredients of a research field that is an essential enabling technology for the optimal dynamicoperation of high-tech/mechatronic systems, automotive systems, energy and power convertersystems and industrial process control systems.


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It is the research mission of the group to be an internationally recognized center of researchin systems and control, that has a solid foundation in the department EE and TU/e, wherecontributions to fundamental theory and method development are combined with advancinginnovative technological applications in a selected number of domains, in cooperation withrelevant industrial and academic partners.

The fundamental driven research of CS is directed towards the following topics:• Spatial-temporal systems and model reduction

Spatial effects in dynamic systems occur e.g. in non-rigid-body mechanics, particularphenomena in electromagnetic materials (Eddy currents, hysteresis), thermal phenomenain materials, and fluid flow patterns. Mastering the complexity through model reduction inboth spatial and temporal dynamics is required to arrive at feasible control and optimizationstrategies.

• Data-driven modeling (system identification) of linear and nonlinear systems

The availability of quantified and validated dynamic models is of paramount importance inmodel-based operational strategies as monitoring, control, estimation and optimization.Research focusses on experiment design, identification in open-loop, closed-loop, and indynamic networks, as well as on parameter estimation in large scale physical models.Particular attention is given to nonlinear (linear parameter-varying - LPV) models, includingthe relation with machine learning.

• Constrained and interconnected systems

Interconnected systems appear in many technological environments, like (smart) electricitygrids, sensor networks, and automotive systems, while constraints on physical variables area natural phenomenon to be considered in the design of optimal operations. Modelling,estimation and control strategies are developed with typical tools as MPC (model predictivecontrol), and flexible Lyapunov functions for studying stability properties.

• Model-based control and optimization

Dynamic models are central in the design, control and optimization of technological systems.Control-relevant modelling, and model-based control strategies as well as techniques foronline model maintenance and controller tuning are studied for processes in severaltechnology fields (high-tech mechatronic systems, chemical process control, oil reservoirengineering, automotive systems and energy systems).

These fundamental research lines are explored in combination and direct involvement withseveral fields of technology:

• High-tech mechatronic systems, including planar actuators for high-precision positioningdevices, high-accuracy power convertors, and physical imaging systems.

• Processes in (petro)chemical engineering and petroleum reservoir engineering.• Large-scale power distribution networks and systems.• Automotive systems, in particular energy and battery management systems

With the growing complexity of technological systems, pertaining to combinations of physical,mechanical, and electrical phenomena that influence dynamic properties and essentiallyinfluence performance, and the increasing performance demands that are requested, thefield of systems and control is expected to play an increasing role in future systems. On-linemeasurement and control strategies will need to be developed for interconnected systemsof high complexity and with communication links as part of the control system.

CS actively participates in the research programme of the national research school DISC,and with its research program contributes strongly to the “Smart and Sustainable Systems”


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program of the department EE. Cooperative links exist with the EE-groups EPE and EES.Opportunities for contributing to the theme,Connected World, are being explored.

FUNDAMENTAL RESEARCH

Spatial-temporal systems and model reductionResearch on infinite dimensional port-Hamiltonian systems has been continued. This modelclass proves useful for modeling large classes of physical systems in which variables evolveover time and space. We have exploited novel discretization schemes of infinite dimensionalport-Hamiltonian that consist of interconnections of finite dimensional port-Hamiltonian systems.In particular, we have developed a proof of principle in which a 1D spatially distributed diffusivesystem can be discretized while retaining the Hamiltonian property and the internal physicalenergy of the system. A key consequence of this result is that discretized systems maintaintheir physical meaning as a passive and diffusive system –a property that can usually not beguaranteed by finite element approximation schemes. An implementation of these results hasbeen used as a proof of principle of this method. To further intensify this research a researchproject has been submitted to NWO to address and solve fundamental questions in thismethodology. Galerkin projections define an important tool for a number of model approximationschemes for the general class of large-scale nonlinear systems. We have been generalizingthis method so as to become more flexible towards specific Euclidean structures of configurationspaces and to make approximation methods independent of specific meshing techniques andgranularity of meshes. These model approximation methods have been successfully appliedto a number of approximation question in the high-tech industry. Specifically in the modelingof the thermal stress and mechanical deformations of the reticle in lithographic processes, inthe thermal modeling of LED's mounted on printed circuit boards, in air flow models (describedby Navier-Stokes equations) that are used for energy generation by wind turbines and in variousmodel-based estimation processes. The cooperation with industrial partner ASML has beenintensified in this period, which has led to the start and funding of a new PhD project on ThermalControl for Projection-Optics in EUV-Lithography.

Data-driven modeling (system identification) of linear and nonlinear systemsIdentification of LPV models

Operating industrial process systems under varying operating conditions and the need to handleposition dependent and nonlinear dynamics in motion control systems have stimulated thedevelopment of modeling and control approaches capable of efficiently handle the systembehavior in terms of an intermediate: still linear, but varying dynamical representation. Specificapproaches have been developed which allow the identification of LPV polynomial models ina closed-loop setting using the extension of instrumental variable schemes. Significant advancesin the understanding of realization theory of LPV systems have been achieved in terms of directrealization schemes between input-output and state-space representations, further exploringthe relations between dynamic dependency on the scheduling variable and minimal realizationof the represented dynamics. This has lead to the introduction of a realization theory basedmodel reduction scheme for LPV models where joint reduction of representation complexity interms of system order and complexity of dependence on the scheduling variable can be achieved.Also significant improvements in terms of the discretization theory of LPV systems have beendeveloped. Model structure exploration approaches have been also introduced in terms ofsparse estimators for polynomial LTI models with rational noise models, which have been alsoextended to the LPV setting. Nonparametric identification of LPV models under general noiseconditions has been achieved by using an instrumental variables based extension of theleast-squares support vector machine approach originating form the machine learning field.


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Identification in dynamic networks

The problem of identifying dynamical models of particular modules that appear in a complexnetwork structure is a new problem that has been formulated and now is being analyzed andtreated in detail. The problem occurs in many fields of application, among which power grids,systems biology, sensor networks etc. The identification on the basis of measurement data ofa particular link in a dynamic network shows close resemblance with the classical closed-loopidentification problem. However in its structure it is richer as it also involves the selection ofsensing and actuation locations, and possibly the detection of the cause-effect relationships.We have generalized the clasical identification problem to situations of a complex interconnectionstructure where the objective is to consistently identify the dynamics of a particular module inthe network. For a known interconnection structure it has been derived that classical predictionerror methods for closed-loop identification can be generalized to provide consistent modelestimates, under specified experimental and topological conditions. Graph theoretical toolshave been derived to verify the topological conditions.

Constrained and interconnected systemsLow complexity Model Predictive Control

Techniques for the design of low-complexity MPC algorithms were developed, with the aim ofpreserving safety at all times (in terms of constraints satisfaction) and achieving a competitiveperformance (in terms of closed-loop dynamic and static response specifications).The developedtechniques make use of one the following ingredients, or a combination of them: flexibleLyapunov functions, infinity norms cost functions, hybrid polytopic partitions, constrained controlinvariant sets. Also, efficient methods for hardware implementation of the developed techniqueson dedicated circuits (ASIC) or programmable hardware (FPGA) were developed.

The long-term activities of the CS Group in the area of Model Predictive Control culminated inorganizing the 4th IFAC Conference on Nonlinear MPC, which took place in Noordwijkerhout,August 23 – August 27, 2012, with 133 participants from 33 countries.

Activities in this domain were performed in collaboration with the industrial partners FordResearch Laboratories, USA; Prodrive; ASML; On-Semiconductors; NXP.

Stability analysis of interconnected systems and time-delay systems

Non-conservative techniques for stability analysis of large-scale interconnected systems and/ortime-delay systems were developed.These techniques exploit a relaxation of Lyapunov functions,termed finite-time Lyapunov functions, to obtain, for the first time, a set of non-conservativedissipativity-type and small-gain-type conditions for stability analysis of large-scale interconnectedsystems.The equivalence of interconnected systems and systems with time-delay, establishedin collaboration with Prof. A.R. Teel from UCSB, USA, was further exploited in combinationwith finite-time Lyapunov functions to obtain the first, necessary and sufficient conditions forRazumikhin-stability analysis of time delay systems.

Distributed control and estimation

Several Lyapunov-based distributed MPC algorithms were developed and applied to control ofelectrical energy transportation networks, or shortly, power systems. These algorithms arecharacterized by solving on-line a convex optimization problem of low complexity in a repetitiveway and it is remarkable that convexity is preserved for input-affine discrete-time nonlinearsystems. A paper which shows that the developed distributed MPC algorithms can stabilize acast-study system were existing distributed MPC methods fail is in print. A novel event-basedestimator that is valid for generic event-triggered control systems was developed along with anovel method for fusing the estimates of two estimators within a network of estimators. These


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two results provide a major step forward in the areas of event-based estimation and controland distributed state estimation, respectively.

Activities in this domain were performed in collaboration with the industrial partners TenneT,KEMA, APX, TNO.

Model-based control and optimizationIn addition to the fundamental research in the area of stability and robustness in model basedcontrol, we aim to extend and improve the model based control implementations andmaintenance of such controllers in several fields of technology. Methods are being developedfor model maintenance, adaptation, diagnosis and controller tuning aiming for an higher levelof autonomy of operation of (MPC) controlled processes, under the presence of nonlineardynamic influences (change of operating conditions), and external disturbances, while theoptimal economic performance of the process is the leading objective to be maintained.

In the scope of the FP7 project Autoprofit, two different controller tuning methods (selection ofweighting matrices in the objective function ) have been developed in which frequency domaininformation is utilized in the selection of the weighting matrices. In addition asymptotic behaviourof Toeplitz matrices has been studied for SISO and MIMO processes, with the goal to serveas a basic tuning tool in model predictive control (MPC) applications.

In a related domain, two new PhD projects have been started on model-based control andoptimization problems in petroleum reservoir engineering, in cooperation with Shell and TUDelft.

TECHNOLOGY DOMAINSHigh-tech mechatronic systems and power convertors

High-performance electromagnetic actuated systems play a key role in the current developmentson high-tech systems, as driven by the major achievements in lithographic processes. Next toresearch on advanced actuator concepts and active vibration isolation, we include controlconcepts for high-performance power convertors as well as modeling, estimation and controlaspects in the thermal, mechanical and optical imaging part of lithographic processes.

As an alternative to the classical Lorentz actuators we investigate variance reluctance actuatorsand control strategies for electromagnetic effects with spatial distribution in non-rigid bodystructures. It has been shown that the closed-loop performance of Lorentz actuators can bematched and even surpassed by reluctance actuators with properly designed and calibratedcontrol schemes based on the developed tools. This way, no tradeoff in performance has tobe done when switching from Lorentz to reluctance actuators, which are able to achieve higherforce densities. By using over actuation of the many coils of a planar actuator both the 6 DOFrigid body states and a number of flexible modes can be controlled. The remaining freedom isused to reduce the losses and so the temperature variations in both the fixed coils and themoving magnets.

An important focus in the development of lithographic processes is on the use of Extreme UltraViolet light sources. The use of this light source implies a need for substantial advancementsin thermo-mechanical-optical modeling, estimation and control of the reticle, the projectionoptics and the wafer.We have been contributing to this development with simplified and accuratemodels for the thermo-mechanical behavior of the reticle and the wafer.This work has receivedconsiderable acknowledgement from ASML and will be continued in the direction in whichoptical aspects are taken into account. A PhD position has een funded by ASML on this domain.

For industrial inkjet printers a measurements-based feedforward strategy has been successfullycompleted. Based on first-principle modeling the essential physical phenomena of jetting havebeen captured. With on-line measurements with a high-speed camera the volume and speed


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of jetted ink droplets have been observed, resulting in optimal pulse shapes. In a related projecta non linear MPC controller has been designed for industrial printers maximizing throughputand respecting constraints on print quality and changing available electric power. A solutionhas been found to decompose the NL MPC into a NL static optimizer and piece-wise linearestimators and controllers.

In the scope of realizing ultra high-precision power amplifiers a novel systematic design methodwas proposed for synthesis of piecewise-affine state-feedback controllers that take into accountsystem constraints and available computation resources for the real-time implementation. Itwas shown that significant improvements in bandwidth and robustness of the power amplifierscan be achieved, and that explicit MPC controllers can be implemented in FPGAs for closed-looprates in excess of 200kHz.

Cooperation partners include ASML, Prodrive, NXP and Océ.

Process controlIn collaboration with the Chemical Engineering Department dynamic operation of heterogeneouscatalytic reactions is investigated. Very fast temperature pulses are provided to provide therequired energy for the reactions to occur, in an attempt to control chemical reactions on amicroscale. A proof of concept was already demonstrated and the promising results are publishedin a journal paper. Currently, different catalysts are explored under this kind of operation.

In view of integrating process design and process control, research efforts were directed towardscontrollability analysis of intensified reactors. This study resulted in the controllability analysisof a Helix reactor for the production of an surfactant and showed that the importance of inclusionof feedback control considerations in the design of reactors.

In the EU-FP7 project Autoprofit, important steps have been made towards on-line monitoring,detection and tuning methods for on-line process control and economic optimal operations. Anexperimental campaign at Sasol (South-Africa) has been part of the activities. Besides methodsfor controller tuning, focus has been on the handling of nonlinear dynamics. The developedapproaches for LPV identification have been tested on a benchmark model of a high-puritydistillation column in detailed comparative study with a large selection of available approachesin LPV identification. The study has shown that the non-parametric estimation approachesprovide highly accurate models with a relatively low complexity due to their capability ofaccurately reconstructing the dependency of the linear dynamics on the operating conditionsfrom data.

Cooperation partners include ISPT, ABB, Sasol, Proctor&Gamble, TNO, DSM, Shell

Power networksWithin the EU-KP7 E-Price project the design of a new market structure for trading reservecapacity in energy markets is studied along with the possibility to use prosumers (small producersand/or consumers) actively in the real time imbalance mechanism, for instance with real timeprice-based control algorithms, and the use of locational pricing to alleviate transmissioncongestion related to imbalance power. A simulation environment has been built and extendedby the market layers in which generators and loads are grouped into market parties.The biddingand market clearing mechanism have been developed, resolving the inherent trade-off betweenefficiency and reliability. Contributions were made to adaptive control of the Area Control Errorin power systems to cope with changing electrical characteristics of the production andconsumption units and the grid parameters. It allows better tuning of the secondary controllertaking also the actual cross-border connection into account.


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Automotive systemsIn the automotive domain we have been successful in acquiring substantial research budgetthrough a EU-KP7 project CONVENIENT (Complete vehicle energy-saving technologies forheavy trucks) in close cooperation with DAF Trucks NV, and 20 other national and internationalpartners. The CONVENIENT project targets a 30% reduction of fuel consumption in vehiclesfor long-distance freight transport by developing an innovative heavy-truck archetype featuringa suite of innovative energy-saving technologies and solutions. Responding to this challengeof improving fuel efficiency, the objective of CONVENIENT is to achieve complete vehicleenergy management by proposing highly innovative solutions for improved efficiency andenhanced integration of components (currently designed independently) which will be developed,integrated and evaluated directly on validator vehicles.

In a research project on hybrid innovations for trucks (HIT), we focus on investigating anddemonstrating the potential of advanced energy management strategies, exploiting integratedpower train control to benefit from synergy between individual power train components as wellas model transformations. The target is to realize a fuel saving up to 7% compared to thebaseline heavy-duty long-haul XF truck.

In the domain of battery management optimal charging schemes for lead-acid batteries in hybridcars have been developed based on a battery model to estimate the charge acceptance. In asimulation using New European Driving Cycle (NEDC) data, the new charging strategy hasshown an advantage over the existing regenerative charging strategy in terms of fuel economy.In the HTAS Power Train project a battery model for the selected LiFePO4 battery astate-of-charge/state-of-health estimation scheme has been developed.This scheme was testedon an experimental set-up at Philips Innovation Services on the High-tech Campus in Eindhoven.

Partners in this domain are DAF, TNO, Tier1, SKF, DTI, Heliox, Ford, Philips and manyinternational partners in CONVENIENT

DISC projects

Stability and stabilization in the space of compact sets

First promotor: Prof. Paul Van den Hof, Second promotor: Prof. Jan vanSchuppen, Co-promotor: Dr. Mircea Lazar

Projectleader:

Alina DobanPhD students:NWO and Dutch Institute of Systems and ControlSponsored by:

DescriptionThe aim of this project is to study a generalization of classical set-theoretical tools andLyapunov’s stability theory for dynamical systems to dynamics which evolve in the spaceof (compact) set-points. A novel approach to several relevant problems in systems theory(e.g., stabilization with a set of assigned initial conditions, constrained and robust stabilization,obstacle avoidance) as well as in emerging problems in systems biology (e.g., modeling ofdisease dynamics, gene regulatory networks) is proposed. First, motivated by biomedicalapplications, in particular biochemical networks, a characterization of set-equilibria isinvestigated. This will enable the employment of the Hausdorff set-distance as a tool for thegeneralization of concepts such as Lyapunov functions and invariant and contractive setsfor systems evolving in the space of set-points. Finally, the theoretical results are expectedto provide a set of tools for solving constrained and robust control synthesis problems andto handle problems from systems biology, in particular control of biochemical reactionnetworks.


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Modelling of a hysteretic relay in self-oscillating loops

Prof.dr.ir. P.P.J. van den Bosch, Prof.dr. S. WeilandProjectleader:Paul van der HulstPhD students:

DescriptionSelf-oscillating relay systems are not well understood. This is a problem for class-D audioamplifier designs built around such control loops, since these require performance beyondwhat is found in most relay control loops. The interesting aspect of the relay is that theinput-output behaviour is very simple, but this description is useless for control loop design.Current linearised models for the non-linear relay are usually based on a quasi dc assumptionand do not accurately describe the dynamic relay behaviour. Additionally the relay is typicallymodeled with a real gain, where a complex transfer would be more accurate.

This project aims to find a more accurate complex model for dynamic signals, which is ableto predict linearity as function of signal level as function of system parameters such as thehysteresis which determines the oscillation frequency.

Partner: Piak electronic design bv

Ongoing workResults: Improved numerical simulation engine for systems with discontinuous signals

DISC projects

Rapid Variation of Catalyst Temperature in Heterogeneous Catalysis

Prof.dr.ir. A.C.P.M. Backx, Dr. L. OzkanProjectleader:Jasper StoltePhD students:

AUTOPROFIT: Advanced Autonomous Model-based Operation of IndustrialProcess Systems

Prof.dr.ir. A.C.P.M. Backx, Dr. L. OzkanProjectleader:Nhat Quang TRANPhD students:

Advanced Autonomous Model-Based Operation of Industrial ProcessSystems (Autoprofit)

Dr. L. Ozkan, Promoter: A.C.P.M. Backx.Projectleader:N.Q. Tran,PhD students:

DescriptionThe AUTOPROFIT project (Advanced Autonomous Model-Based Operation of IndustrialProcess Systems) is a medium-scaled focused research project funded by FP7, theFramework Programmes (http://www.fp7-autoprofit.eu/). In this project we aim to optimizethe operational efficiency of current model-based systems (Model Predictive Control, RealTime Optimization) which are commonly used in process industry. One of the problems inthese systems is the high cost related to the industrial implementation. Moreover, the


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performance of these model based systems degrades over time due to changes in operationalconditions.Therefore, the target of project is to maintain the performance and automate justin time maintenance of these model based systems at a reasonable cost.

The interest of control group of Eindhoven University of Technology is to investigate theeffect of model uncertainties on the performance of the model based systems and developand automate robustly performing tuning methods in case of performance degradation.

External partners:

Academic partners: Delft University of Technology, RWTH Aachen University Germany ,KTH Royal Institute of Technology Sweden

Industrial partners: ABB Sweden, Boliden Sweden, SASOL South Africa

Identification of structured models for life-cycle optimization with varyingwell configurations

Prof.Dr.Ir. Paul van den Hof (TU Eindhoven) – Prof.Dr.Ir. Jan Dirk JansenProjectleader:Edwin G.Insuasty Moreno,PhD students:

DescriptionAim of the project:

Projects within the ISAPP program on model-based optimization of oil production over thelife of an oil reservoir have demonstrated that economic performance can be increased upto 15%. Generally, a nonlinear PDE reservoir model is used to determine the optimalproduction strategy. However, in order to realize the potential gain of such a dynamicproduction strategy, several issues need to be addressed. These include:

• The high level of uncertainty that is present in the large-scale nonlinear models, andas a result of the high level of uncertainty in any model-based optimization strategy.

• The limited information content in production and other data to validate the large scalemodels.

The required translation of a high level production strategy to an operational level thatincludes production constraints and production targets that are specified on a short termhorizon. In previous works, long-term performance is introduced into a short term productionenvironment by way of a secondary control problem that it is executed in an operationallevel. This latter control problem uses low order (linear) data-driven reservoir models incombination with a short-term tracking control objective to realize essential elements of thehigh level optimal production strategy in practice. The developments so far have focusedon:

• Fixed configuration of wells.• Identification of non-structured black-box data driven models• Optimization based on one particular long-term reservoir model.

The objective of this project is to extend the hierarchical control approach by two optionalelements:

• The development of data-driven structured models that are capable of effectivelycharacterizing the actual injector-producer dynamics in a large scale production setting, thereby identifying the injectors that most effectively influence production, and

• The inclusion of well configuration changes/investments in the long term model-basedoptimization strategy.

Starting date: 1st September 2012


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Partners: Shell – TU Eindhoven – TU Delft (The Recovery Factory Program)

A robust hierarchical approach to life cycle optimization

Mohsin Mohammed SirajPhD students:

DescriptionModel-based optimization of oil production over the life of an oil reservoir has demonstratedthat economic performance can be increased up to 15%. Generally, a physics-basedlarge-scale nonlinear reservoir model is used to determine the optimal production strategy.However, in order to realize the potential gain of such a dynamic production strategy, severalcritical issues such as high level of uncertainty present in the large-scale nonlinear models,the limited information contents in the production and other data to falsify/validate thelarge-scale models and the translation of high-level (long-term) production strategy to anoperational level that includes production constraints and production targets that are specifiedon a short-term horizon, need to be addressed.

A two-level (hierarchical) optimization strategy is recently introduced, where long-termeconomic performance is introduced into a short-term production environment by way of asecondary control problem that is executed on an operational level. The objective of thisproject is to investigate whether the multilevel control approach is suited to successfullyintroduce long-term economics into short-term operational decision-making, under theconditions of large (geological) modeling uncertainties and of operational constraints. Asecondary objective is to investigate which type of data-driven modeling would be mostsuited to field applications of such a multi-level approach.

Starting date: 1st September 2012

Finishing date: 1st September 2016

Partners in industry and/or other institutes:• TU Delft• Shell

Supervisors:• Prof. Dr. Ir. Paul van den Hof (TU/e)• Prof. Dr. Ir. Jan Dirk Jansen (TU-Delft)

Shell Mentor:• Ir. Gijs van Essen


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ASPA: Advanced Single-stage Planar Actuator

Prof.dr.ir. P.P.J. van den Bosch, Dr.ir. C.M.M. v. LieropProjectleader:Jaron AchterbergPhD students:

Control of reluctance actuators for high-precision positioning

Prof.dr.ir. P.P.J. van den BoschProjectleader:Andelko KatalenicPhD students:

Ultra High-Precision Power Amplifier

Prof.dr.ir. P.P.J. van den Bosch, Dr. M. LazarProjectleader:Veaceslav SpinuPhD students:

DescriptionThe UHPA project deals with the design methods for next generation precision poweramplifiers.The work is split among two groups, i.e., EPE and CS.The research on the powerstage topology design and analysis of electrical components is performed at the EPE group.The research on the advanced control techniques for power converters is performed at CSgroup.

The opposed current converter (OCC) is acknowledged by EPE to be the most suitableamplifier topology for next generation of precision servo-drives. In contrast with the actualstate-of the art H-bridge converters, OCC does not suffer from dead-time effects and doesnot present series connected switches, therefore is highly linear in open loop and is protectedagainst single effect burnout. It was shown through experiments that the OCC topologynoticeably outperforms the H-bridge.

Good open-loop behavior is not sufficient for a next generation power amplifier. Therefore,the CS group works to advance the state of the art in the converter feedback control. Incontrast to generally employed single-input single-output controllers and decoupling, wefocus on state-feedback control design methods. Within this class, model predictive control(MPC) and set-theoretic methods (STM) are of specific interest. Main objectives in the controldesign are constraints handling, fast dynamic response and good disturbance rejection.

Partners: Philips lighting, Prodrive, ASML. Limited cooperation with the MOBY-DIC onimplementation of explicit MPC in FPGAs.

Results at CS group:

Theory innovations:

- A novel systematic design method was proposed for synthesis of piecewise-affinestate-feedback controllers that take into account system constraints and available computationresources for the real-time implementation.

Proof of concept:

- It was shown that with state-feedback significant improvements in bandwidth and robustnessof the power amplifiers can be achieved in comparison to standard SISO control strategies(tested on both H-bridge and OCC stack).


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- It was shown on the experimental setup (buck-boost converter) at the CS group that explicitMPC controllers can be implemented in FPGAs for at closed-loop rates in excess of 200kHzand potentially up to several MHz through pipelining and/or with further approximation.

Vibration Isolation Control of a Contactless Electromagnetic SuspensionSystem

Prof.dr.ir. P.P.J. van den Bosch, Dr.ir. A.A.H. DamenProjectleader:Chenyang DingPhD students:

DescriptionThis thesis systematically explores the opportunities to improve the performance(transmissibility and compliance) of a 6-DoF contactless electromagnetic suspension systemby system-level design, choices of sensors, identification of the static and dynamic behaviors,and development of advanced control strategies. Such a system, also referred to as theSingle Electro-Magnetic Isolator System (SEMIS), combines the advantage of passive gravityforce (7.2 kN) compensation and low power consumption (0.3 6W). It is a typical

multi-DoF active suspension system. For vibration isolation control of a general multi-DoFactive suspension system, this thesis proposes a design strategy of vibration isolation controlwhich combines the optimal static decoupling and the sliding surface control. The opticalstatic decoupling reduces a multi-DoF vibration isolation control problemto multiple 1-DoFvibration isolation control problems. Each 1-DoF vibration isolation control is to be solvedby the sliding surface control. Optimal static decoupling is studied for an LTI mechanicalsystem with and without the assumption of proportional damping. If proportional dampingmay be assumed for an LTI mechanical system, two methods, modal decomposition andOwens method, are both applicable and perfect decoupling can be achieved. It is proved inthis thesis that the two different pairs of input- and output- decoupling matrices derived bythese two methods

can be normalized to the same pair of decoupling matrices. If proportional damping may notbe assumed for an LTI mechanical system, Vaes-procedure can be applied to derive a pairof optimal static decoupling matrices. This thesis develops two modifications to theVaes-procedure to improve its numerical stability and reduce its computational complexity.

A measurement scheme, which combinesmetrology frame absolute acceleration and itsdisplacement relative to its supporting base frame, is chosen for vibration isolation controlof SEMIS. As such, the controller for each DoF motion has two inputs and a single output(force or torque). The sliding surface control is developed based on the frequency-shaped

sliding surface approach [?], to design a DISO vibration isolation controller for a 1-DoF activesuspension system.The advantage of the sliding surface control with respect to conventionalmethods is that the transmissibility and the compliance are designed in two

independent steps. As such, the design process is simplified. The cross-coupling of amulti-DoF system can be reduced as much as possible by static decoupling such that thedecoupled system may be treated as multiple 1-DoF systems in control design.

The proposed control strategy is compared with H¥ optimization based on an identifiedmodel of the 3-DoF experimental demonstrator. It shows that the developed strategy hascomparable transmissibility, better compliance, simpler design process, lower controllerorder, less requirement on identification, but lower robustness than the H¥ controller. Theperformance comparison is validated in experiments on the 3-DoF demonstrator. For the


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system-level design of a general 6-DoF active suspension system, thesinglegravity-compensator concept is developed. Its advantages with respect to theconventional multi-gravity-compensator concepts are lower stiffness, lower passive damping,lower cross-coupling, and lower cost. The SEMIS concerned in this thesis is realized basedon this single-gravity-compensator concept. Static and dynamic behaviors of SEMIS areidentified in experiments.The high vertical passive force produced by the gravity compensatoris measured as 7.2 kN. The temperature dependency of this vertical passive force ismeasured as -12.1 N/K, which is 1.7h/K of the total 7.2 kN.The dynamic properties of SEMIS,low cross-coupling, low stiffness, low

passive damping, and suitability of high-bandwidth control are experimentally validated.

These dynamic behaviors are inherited from the gravity compensator. This proves thesuccess of the system-level design.

Analysis of the dynamic measurement results shows that further decoupling SEMIS usingstatic matrices in addition to the geometric transformationmatrices is neither possible nornecessary. This also proves the success of the system-level design. As a result, the

sliding surface control is applied to design a vibration isolation controller for each of the6-DoF motions. Closed-loop performance is pushed to the limit of SEMIS hardware.Closedloop transmissibility and compliance are experimentally validated.

Stochastic Modelling for Lens Heating and Beyond

Prof.dr.S. Weiland, Prof.Dr. W. Coene, Prof.dr.ir. P.P.J. van den Bosch,Supervisors: Prof. dr. Wim Coene, Prof. dr. Siep Weiland Partners inindustry: ASML

Projectleader:

Can BikcoraPhD students:

DescriptionThe project is divided into two parts:

1. Prediction of lens heating induced aberrations in deep ultraviolet lithography:

The projection lens in a deep ultraviolet wafer scanner contributes significantly to imagingerrors due to its localized heating during exposures. Via the use of available models thatdescribe the resultant wavefront aberrations in terms of system inputs (e.g., the exposuredose), recursive estimation and prediction strategies are developed. In particular, modelparameters are recursively updated with respect to the aberration measurements taken atthe end of a wafer and are subsequently utilized in aberration predictions for the dies of thenext wafer. Dependent on the model type in use, the focus is given either to nonlinear Kalmanfilters or to linear estimation approaches with regularization.The predictions are then utilizedin finding the setpoints for the manipulators that the projection lens is equipped with, in orderto minimize the aberrations to occur.

2. Modeling and prediction of thermally-induced deformations on reticles for extreme ultravioletlithography:

Deformation of reticles due to their inevitable heating is among the dominant causes ofimaging errors in photolithography. In extreme ultraviolet (EUV) lithography, this problem isbecoming progressively crucial as the source power continually increases, leading to higherlevels of absorption of the EUV light by reticles. In order to mitigate its impact on exposedlayers, accurate predictions to be the inputs of a control scheme are essential. To serve thispurpose, a large-scale thermo-mechanical model is derived by using the finite element


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method. Since only low-order models are feasible for real-time use, this model is undergoneseveral model reduction techniques to arrive at the best compact model with respect to itsprediction performance, compaction rate, and easiness of computation. Afterwards, the bestperforming reduced-order model is utilized in several stochastic estimation methods to selectboth an update mechanism for the model and a prediction mechanism of the deformations.

OCTOPUS: Smart system adaptability

Prof.dr.ir. P.P.J. van den Bosch, Dr. S. Weiland, Dr.ir. J.T.B.A. KesselsProjectleader:Carmen CochiorPhD students:

DescriptionA general aim in industry is to improve system evolvability, i.e. the ability to easily adaptsystems in response to evolution of technology, competition, and/or customer expectations.The research challenge is to design a runtime adaptive system that maintains a high levelof economic performance under nonlinear dynamic behavior and changing operatingconditions and requirements. To deliver high performance, the system should adapt itselfin runtime, based on the operating conditions and constraints.

OCE develops an adaptable printer to maximize the productivity under different workingconditions and print queues. The (known) print queue consists of a number of print jobs,each job with a finite number of the same media characteristics (paper weight, paper size,thermal properties, mode- simplex/duplex). To maximize the productivity and to satisfy theprint quality constraints, paper properties need to be taken into account. An accurate controllercan be obtained if it is possible to predict the influence of all the components interacting withthe system, to obtain the required paper temperature.

The proposed solution, based on model predictive control, utilizes a centralized formulation,which allows finding a better optimum, support scalability and adaptability, can betterguarantee constraints satisfaction. Power-constrained printing needs to achieve maximumthroughput [sheets/sec] and still satisfies the print quality constraints.

Partners in industry and/or other institutes: Embedded Systems Institute (ESI), OCEOcé-Technologies B.V. and academic partners - Delft University of Technology, RadboudUniversity Nijmegen and University of Twente

Task dependent control of a flexible motion system

Prof. Dr. Ir. P.P.J. v.d. Bosch, Prof. Dr. Ir. H. Butler, Dr. Ir. R. TothProjectleader:Koen VerkerkPhD students:

DescriptionHigh performance planar actuators are becoming more and more flexible due to the reductionin weight of the moving stage. To reach the required tracking performance, new controltechniques are required that take the flexible behavior into account.These techniques requiremeasurements of the flexible behavior and as these cannot be measured directly observerare needed. The complicating factor in the observer design is the fact that sensor positionsare not fixed but vary over time.

A secondary goal is related to system identification, because the system is subject toproduction imperfections and thermal dynamics online closed loop system identificationtechniques can be used to ensure that the model used in the control loop is up to date. The


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main task here is the design of experiments such that identification is possible withoutdegrading performance.

A final research direction is the use of multiple controllers and switch between them dependingon the task the system is currently performing. These tasks have different performancecharacteristics and the use of a single controller for all tasks is not always optimal.

Start: 01-04-2012

Finish: 31-03-2016

Partners from industry: ASML

Thermal Control for Projection-Optics in EUV-Lithography

prof.dr. W.M.J.M. (Wim) Coene, prof.dr. S. (Siep) WeilandProjectleader:Michel HabetsPhD students:

DescriptionIn EUV-lithography, light with a wavelength of 13.5 nm is used. This light is easily absorbedin air and any other materials. EUV-light is primarily being absorbed by: (1) the reticle and(2) the so-called projection-optics box. Both operate in a reflective mode. Coupled to theroadmap for EUV-lithography, the EUV source power will increase in order to reach higherwafer throughputs for smaller feature sizes.

The PhD-project focuses on thermal control of the projection-optics box.The projection-opticsbox for EUV-lithography consists of a couple of mirrors, by which the light is reflected andfocused. The mirrors are made of a low-expansion material (low coefficient of thermalexpansion).The mirrors are heated up by the absorption of the EUV-light during normal useof the scanner, and they will suffer from thermal-induced deformations. The latter will leadto a severely aberrated imaging performance of the scanner, which needs to be mitigated.The elements for thermal control of the projection optics comprise:

- Fast Predictive Model (via Reduced-Order Modeling)

- Estimation-and-Filtering

- Sensors and Metrology

- Actuation

Partners in industry: ASML, ZEISS

Starting data: 01.01.2013

Finishing data: 01.01.2017

Hybrid Innovations for Trucks(HIT)

Prof.dr.ir. P.P.J. van den Bosch, Dr.ir. J.T.B.A. KesselsProjectleader:Thinh Hong PHAMPhD students:

DescriptionThis project is aiming to deliver a significant contribution in realizing up to 7% CO2 emissionreduction and up to 7% fuel saving for long haul vehicles by research and development ofa number of technologies. The objective of this project is to develop a proof of concept fora hybrid long haul truck leading to a realistic fuel saving up to 7%, and CO2 reduction up to7% in 2013 for heavy-duty long-haul trucks while maintaining EURO-V/VI emission limits


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and comparable driveability, production 2016.The baseline is a EURO-V heavy-duty long-haulXF truck with ±350 kW.

In this project, the PhD, from Control Systems group of Electrical Engineering departmentof Technische Universiteit Eindhoven (TU/e), focuses on investigating and demonstratingthe potential of advanced energy management strategies, exploiting integrated power traincontrol to benefit from synergy between individual power train components as well as modeltransformations. The target is to realize a fuel saving up to 7% compared to the baselineheavy-duty long-haul XF truck.

Starting date: Quarter3, 2010

Finishing date: Quarter2, 2014

Partners in industry and/or other institutes: The project consortium represents aninterdependent automotive ecosystem. Headed by OEM DAF, Tier1 SKF, SME’s DTI, Heliox,and TU/e as knowledge institute contributing towards a balanced multi-disciplinary approachand fundamental/strategic technological research.

Complete Vehicle Energy-saving Technologies for Heavy-Trucks

J. Kessels and S. WeilandProjectleader:Handian ChenPhD students:

DescriptionThe CONVENIENT project targets a 30% reduction of fuel consumption in vehicles forlong-distance freight transport by developing an innovative heavy-truck archetype featuringa suite of innovative energy-saving technologies and solutions.

From the customer viewpoint, fuel efficiency is top priority because of its significant impactin terms of cost (in the EU, fuel represents about 30% of the Total Operating Costs for a40-ton tractor-semitrailer combination). Responding to this challenge, the objective ofCONVENIENT is to achieve complete vehicle energy management by proposing highlyinnovative solutions for improved efficiency and enhanced integration of components (currentlydesigned independently) which will be developed, integrated and evaluated directly onvalidator vehicles.

Project partners:

CENTRO RICERCHIE FIAT SCPA CRF

IVECO S.p.A.

VOLVO TECHNOLOGY AB

DAF Trucks NV

Continental Automotive GmbH

AVL LIST GMBH

RHEINISCH-WESTFAELISCHE TECHNISCHE HOCHSCHULE AACHEN IKA

NEDERLANDSE ORGANISATIE VOOR TOEGEPAST NATUURWETENSCHAPPELIJK

ONDERZOEK-TNO

Engineering Center Steyr G.m.b.H. & Co KG ECS

IDIADA AUTOMOTIVE TECHNOLOGY SA IDIADA


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TECHNISCHE UNIVERSITEIT EINDHOVEN

TECHNISCHE UNIVERSITEIT DELFT

SKF GMBH

MERITOR HEAVY VEHICLE SYSTEMS CAMERI SPA MERIT

HUTCHINSON SA HUTCH

ING ENEA MATTEI SPA MATTEI

UNIVERSITA DEGLI STUDI DELL ‘ AQUILA UNAQUILA

INNOVAZIONE AUTOMOTIVE E METALMECCANICA SCRL IAM

Webasto Spa WEBASTO

ZF FRIEDRICHSCHAFEN AG ZF

FRAUNHOFER-GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTENFORSCHUNG E.V

FRAUN

KUNGLIGA TEKNISKA HOEGSKOLAN KTH

Starting date: 1-11-2012

Finishing date: 1-11-2015

E-PRICE:Price-based Control of Electrical Power Systems

Prof.dr.ir. P.P.J. van den Bosch, Dr. A. JokicProjectleader:Ana ViragPhD students:

DescriptionThe project proposes the price-based control approach as a coherent methodologicalframework to ensure the feasibility, the reliability and the efficiency of the future Europeanpower system, anticipate and support market based operation and decentralized decisionmaking. It is enabled by state-of-the-art ICT technologies and by utilizing (beyond-)state-of-the-art decentralized and distributed control systems theory and modern optimizationtechniques. In our approach, ICT interfaces, control laws and behavioural protocols will beholistically analyzed and systematically designed as distributed solutions to time-varyingglobal optimization problems.

In the E-PRICE project we propose a systematic scientific approach to formulate ICT andcontrol requirements and solutions for price-based control of future power systems. In theheart of our approach are modelling, analysis and synthesis of the interplays between:

1. the interconnected physical power system, with time varying power requirements asprominent signals; and the economical layer with time varying price signals as the prominentinformation carriers.

2. local objectives of producers/consumers (prosumers) and global balance, transmissionnetwork limits and reliability constraints.

Project partners in industry and academy:

KEMA, APX, TenneT (the Netherlands)Institute for Advanced Studies Lucca, ORS(Italy)Eidgenössische Technische Hochschule Zürich (ETHZ), ABB (Switzerland)


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Publications

Ph.D. theses

Stability analysis and control of dicrete-time systems with delay. Dissertation Rob Gielen:February 2013

Publications

Book chapters/parts

Gielen, R.H., Lazar, M. & Olaru, S. (2012). Set-induced stability results for delay differenceequations. In R. Sipahi, T. Vyhlidal, S.-I. Niculescu & P. Pepe (Eds.), Time delay systems: methods, applications and new trends (Lecture Notes in Control and InformationSciences, 423) (pp. 73-84). Springer.

Sijs, J. & Papp, Z. (2012). Self organizing distributed state estimators. In F. Hu & Q. Hao (Eds.),Intelligent sensor networks : the integration of sensor networks, signal processing andmachine learning. CRC Press.

Tejada, A., Dekker, A.J. & Hof, P.M.J.Van den (2012). A Matlab-based dynamic TEM stimulator.In R. Doornbos & S. van Loo (Eds.), From Scientific Instrument to Industrial Machine(Springer Briefs in Electrical and Computer Engineering) (pp. 38-42). Springer.

Toth, R., Heuberger, P.S.C. & Hof, P.M.J. Van den (2012). Prediction-error identification ofLPV systems : present and beyond. In J. Mohammadpour & C..W. Scherer (Eds.), Controlof linear parameter varying systems with applications (pp. 27-60). Heidelberg: Springer.

Villar Pique, G. & Bergveld, H.J. (2012). State-of-the-art of integrated switching power converters.In M. Steyaert, A. van Roermund & A. Baschirotto (Eds.), Analog circuit design : lowvoltage low power, short range wireless front-ends, power management and DC-DC (pp.259-281). Dordrecht: Springer.


Bikcora, C., Veelen, M. van, Weiland, S. & Coene, W.M.J. (2012). Lens heating inducedaberration prediction via nonlinear Kalman filters. IEEE Transactions on SemiconductorManufacturing, 25(3), 384-393.

Bohm, C., Lazar, M. & Allgower, F. (2012). Stability of periodically time-varying systems: periodicLyapunov functions. Automatica, 48(10), 2663-2669.

Butler, H. (2012). Acceleration feedback in a lithographic tool. Control Engineering Practice,20(4), 453-464.

Butler, H. (2012). Feedforward signal prediction for accurate motion systems using digital filters.Mechatronics, 22(6), 827-835.

Gielen, R.H. & Lazar, M. (2012). On the construction of D-invariant sets for linear polytopicdelay difference inclusions. Journal Europeén des Systèmes Automatisés, 46(2-3),183-195.

Gielen, R.H. & Lazar, M. (2012). Stabilisation of linear delay difference inclusions via time-varyingcontrol Lyapunov functions. IET Control Theory & Applications, 6(12), 1-7.

Gielen, R.H., Lazar, M. & Kolmanovsky, I.V. (2012). Lyapunov methods for time-invariant delaydifference inclusions. SIAM Journal on Control and Optimization, 50(1), 110-132.

Gielen, R.H., Lazar, M. & Teel, A.R. (2012). Input-to-state stability analysis for interconnecteddifference equations with delay. Mathematics of Control, Signals, and Systems, 24(1-2),33-54.


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Hermans, R.M., Jokic, A., Lazar, M., Alessio, A., Bosch, P.P.J. van den, Hiskens, I.A. &Bemporad, A. (2012). Assessment of non-centralised model predictive control techniquesfor electrical power networks. International Journal of Control, 85(8), 1162-1177.

Hulzen, J.R., Schitter, G., Hof, P.M.J. Van den & Eijk, J. van (2012). Dynamics, load balancingand modal control of piezoelectric tube actuators. Mechatronics, 22(3), 282-294.

Lazar, M. & Gielen, R.H. (2012). On parameterized dissipation inequalities and receding horizonrobust control. International Journal of Robust and Nonlinear Control, 22(12), 1314-1329.

Mesbah, A., Nagy, Z.K., Huesman, A.E.M., Kramer, H.J.M. & Hof, P.M.J. Van den (2012).Nonlinear model-based control of a semi-industrial batch crystallizer using a populationbalance modeling framework. IEEE Transactions on Control Systems Technology, 20(5),1188-1201.

Mutsaers, M.E.C. & Weiland, S. (2012). Rational representations and controller synthesis ofL2 behaviors. Automatica, 48(1), 1-14.

Nikacevic, N.M., Huesman, A.E.M., Hof, P.M.J.Van den & Stankiewicz, A. (2012). Opportunitiesand challenges for process control in process intensification. Chemical Engineering andProcessing : Process Intensification, 52, 1-15.

Pisarenco, M., Maubach, J.M.L., Setija, I.D. & Mattheij, R.M.M. (2012). Efficient solution ofMaxwell’s equations for geometries with repeating patterns by an exchange ofdiscretization directions in the aperiodic Fourier modal method. Journal of ComputationalPhysics, 231(24), 8209-8228.

Rakovic, S.V. & Lazar, M. (2012). Minkowski terminal cost functions for MPC. Automatica,48(10), 2721-2725.

Sijs, J. & Lazar, M. (2012). Event based state estimation with time synchronous updates. IEEETransactions on Automatic Control, 57(10), 2650-2655.

Sijs, J. & Lazar, M. (2012). State fusion with unknown correlation : ellipsoidal intersection.Automatica, 48(8), 1874-1878.

Spinu, V., Athanasopoulos, N., Lazar, M. & Bitsoris, G. (2012). Stabilization of bilinear powerconverters by affine state-feedback under input and state constraints. IEEE Transactionson Circuits and Systems. Part II: Express Briefs, 59(8), 520-524.

Tazelaar, E., Shen, Y., Veenhuizen, P.A., Hofman, T. & Bosch, P.P.J. van den (2012). Sizingstack and battery of a fuel cell hybrid distribution truck. Oil and Gas Science andTechnology, 67(4), 563-573.

Toth, R., Abbas, H. & Werner, H. (2012). On the state-space realization of LPV input-outputmodels : practical approaches. IEEE Transactions on Control Systems Technology, 20(1),139-153.

Toth, R., Laurain, V., Gilson, M. & Garnier, H. (2012). Instrumental variable scheme forclosed-loop LPV model identification. Automatica, 48(9), 2314-2320.

Toth, R., Lovera, M., Heuberger, P.S.C., Corno, M. & Hof, P.M.J. Van den (2012). On thediscretization of linear fractional representations of LPV systems. IEEE Transactions onControl Systems Technology, 20(6), 1473-1489.


Bikcora, C. (2012). Expected MSE minimization in linear regression over ellipsoidal uncertaintysets. In Abstract presented at the 31th Benelux Meeting on Systems and Control, 27-29March 2012, Heijden, The Netherlands (pp. 1-2).

Booij, P., Sijs, J. & Fransman, J. (2012). Localized climate control in greenhouses. InProceedings of the IFAC conference on Nonlinear Model Predictive Control 2012(NMPC'12), August 23-27, 2012, Noordwijkerhout, The Netherlands (pp. 454-459). Oxford:Pergamon.


150

Cerone, V., Piga, D., Regruto, D. & Toth, R. (2012). Fixed order LPV controllers design for LPVmodels in input-output form. In Proceedings of the 51st IEEE Conference on Decisionand Control (CDC 2012), 10-13 December 2012, Maui, Hawai (pp. 6297-6302).Piscataway: IEEE Service Center.

Cerone, V., Piga, D., Regruto, D. & Toth, R. (2012). Input-output LPV model identification withguaranteed quadratic stability. In M. Kinnaert (Ed.), Proceedings of the 16th IFACSymposium on System Identification (SYSID 2012), july 11-13 2012, Brussels, Belgium(pp. 1767-1772). Brussels, Belgium.

Cerone, V., Piga, D., Regruto, D. & Toth, R. (2012). Minimal LPV state-space realization drivenset-membership identification. In Proceedings of the American Control Conference (ACC2012), 27-29 June 2012, Montreal, Canada (pp. 3421-3426). Piscataway: IEEE ServiceCenter.

Cochior, C., Bosch, P.P.J. van den, Waarsing, R. & Verriet, J. (2012). Cold start control ofindustrial printers. In Proceedings of the 2012 IEEE/ASME International Conference onAdvanced Intelligent Mechatronics (AIM), July 11-14, 2012, Kaohsiung, Taiwan (pp.123-128). Piscataway: IEEE Service Center.

Cochior, C., Bosch, P.P.J. van den, Waarsing, R. & Verriet, J. (2012). Control strategy for printquality control. In Proceedings of the 31st Benelux Meeting on Systems and Control,March 27-29, 2012, Heijen, The Netherlands (pp. 142).

Cochior, C., Bosch, P.P.J. van den, Waarsing, R. & Verriet, J. (2012). Control strategy forsystems with input-induced nonlinearities: a printing system case study. In Proceedingsof the 2012 American Control Conference (ACC), June 27-29 2012, Montréal, Canada(pp. 1949-1954). Piscataway: IEEE Service Center.

Dankers, A.G., Hof, P.M.J. Van den, Heuberger, P.S.C. & Bombois, X. (2012). Dynamic networkidentification using the direct prediction-error method. In Proceedings of the 51st IEEEConference on Decision and Control (CDC 2012), 10-13 December 2012, Maui, Hawai(pp. 901-906). Piscataway: IEEE.

Dankers, A.G., Hof, P.M.J. Van den, Heuberger, P.S.C. & Bombois, X. (2012). Dynamic networkstructure identification with prediction error methods - basic examples. In J. Schoukens& R. Bitmead (Eds.), Proceedings of the 16th IFAC Symposium on System Identification(SYSID 2012), July 11-13 2012, Brussels, Belgium (pp. 876-881).

Doorn, T.S., Bergveld, H.J., Buthker, D., Castello, C., Jong, A. de, Otten, R. van, Waal, K. de,Ansem, T. van, Dijkstra, M., Keekstra, I. & Sneep, J. (2012). A driver IC for photovotaicmodule-integrated DC/Dc converters. In Proceedings of the 24th International Symposiumon Power Semiconductor Devices and IC's, (ISPD), 3-7 June 2012, Bruges, Belgium (pp.57-60). Bruges, Belgium: ISPD.

Driessen, P.A.A., Hermans, R.M. & Bosch, P.P.J. van den (2012). Distributed economic modelpredictive control of networks in competitive environments. In Proceedings of the 51stIEEE Conference on Decision and Control (CDC), 10-13 December 2012, Maui, Hawaii(pp. 266-271). Piscataway: IEEE Service Center.

Essen, G.M. van, Hof, P.M.J. Van den & Jansen, J.D. (2012). A two-level strategy to realizelife-cycle production optimization in an operational setting. In Proceedings of the SPEIntelligent Energy International Conference, 27-29 March 2012, Utrecht, The Netherlands.Utrecht: SPE.

Feru, E., Lazar, M., Gielen, R.H., Kolmanovsky, I.V. & Di Cairano, S. (2012). Lyapunov-basedconstrained engine torque control using electronic throttle and variable cam timing. InProceedings of the American Control Conference (ACC 2012), 27-29 June 2012, Montreal,Canada (pp. 2866-2871). Piscataway: IEEE Service Center.


151

Forgione, M., Mesbah, A., Bombois, X. & Hof, P.M.J. Van den (2012). Batch-to-batch strategiesfor cooling crystallization. In Proceedings of the 51st IEEE Conference on Decision andControl (CDC 2012), 10-13 December 2012, Maui, Hawai (pp. 6364-6369). Piscataway:IEEE.

Forgione, M., Mesbah, A., Bombois, X. & Hof, P.M.J. Van den (2012). Iterative learning controlof supersaturation in batch cooling crystallization. In Proceedings of the 2012 AmericanControl Conference (ACC), June 27-29 2012, Montréal, Canada (pp. 6455-6460).Piscataway: IEEE Service Center.

Gielen, R.H. & Lazar, M. (2012). Non-conservative dissipativity and small-gain conditions forstability analysis of interconnected systems. In Proceedings of the 51st IEEE Conferenceon Decision and Control (CDC 2012), 10-13 December 2012, Maui, Hawai (pp.4187-4192). Piscataway: IEEE Service Center.

Gielen, R.H., Hermans, R.M., Lazar, M. & Teel, A.R. (2012). On the application of the small-gaintheorem to the stability analysis of large-scale power systems with delay. In Proceedingsof the American Control Conference (ACC 2012), 27-29 June 2012, Montreal, Canada(pp. 1476-1481). Piscataway: IEEE Service Center.

Gielen, R.H., Rakovic, S.V. & Lazar, M. (2012). Further results on the construction of invariantfamilies of sets for linear systems with delay. In Proceedings of the 10th IFAC Workshopon Time Delay Systems, 22-24 June 2012, Boston, USA (pp. 254-259).

Hermans, R.M., Almassalkhi, M.R. & Hiskens, I.A. (2012). Incentive-based coordinated chargingcontrol of plug-in electric vehicles at the distribution-transformer level. In Proceedings ofthe American Control Conference (ACC 2012), 27-29 June 2012, Montreal, Canada (pp.264-269). Piscataway: IEEE Service Center.

Hof, P.M.J. Van den (2012). Challenges in system identification : from closed-loop to dynamicnetwork identification. In Proceedings of the 24th Chinese Control and DecisionConference (CCDC), 24 May 2012, Taiyuan, China (pp. 1-49). Piscataway: IEEE.

Hof, P.M.J. Van den, Dankers, A.G., Heuberger, P.S.C. & Bombois, X. (2012). Identification indynamic networks with known interconnection topology. In Proceedings of the 51st IEEEConference on Decision and Control (CDC 2012), 10-13 December 2012, Maui, Hawai(pp. 895-900). Piscataway: IEEE.

Hof, P.M.J. Van den, Jansen, J.D. & Heemink, A.W. (2012). Recent developments inmodel-based optimization and control of subsurface flow in oil reservoirs. In Proceedingsof the 1st IFAc Workshop on Automatic Control in Offshore Oil and Gas Production, 31May - 1 June 2012, (pp. 189-200). IFAC.

Huang, J., Guoli, J., Zhu, Y. & Bosch, P.P.J. van den (2012). Some study on the identificationof multi-model LPV models with two scheduling variables. In Preprints of the 16th IFACSymposium on System Identification, 11-13 July 2012, Brussels, belgium (pp. 1269-1274).Brussels, Belgium: IFAC.

Katalenic, A., Lierop, A.M van & Bosch, P.P.J. van den (2012). Identification and inversion ofsmooth hysteretic maps. In Proceedings of the 20th International Symposium onMathematical Theory of Networks and Systems (MTNS2012), July 9-13 2012, Melbourne,Australia.

Kessels, J.T.B.A., Martens, J.H.M., Bosch, P.P.J. van den & Hendrix, W.H.A. (2012). Smartvehicle powernet enabling complete vehicle energy management. In Proceedings of theIEEE Vehicle Power and Propulsion Conference(VPPC), October 9-12, 2012, Seoul,Korea (pp. 938-943). Piscataway: IEEE.

Kuiper, S., Hof, P.M.J. Van den & Schitter, G. (2012). Trade-off between the control bandwidthand the measurement accuracy in Atomic Force Microscopy. In Proceedings of the 2012IEEE International Instrumentation and Measurement Technology Conference (I2MTC),13-16 May 2012, Graz, Austria (pp. 888-893). Piscataway: IEEE.


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Laan, E. van der, Cochior, C. & Driessen, D. (2012). A predictive control strategy for productiveprinters. In DSPE-Conference on Precision Mechatronics, September 4-5, 2012, Deurne,The Netherlands.

Laurain, V., Toth, R., Zheng, W-X. & Gilson, M. (2012). Nonparametric identification of LPVmodels under general noise conditions : an LS-SVM based approach. In M. Kinnaert(Ed.), Proceedings of the 16th IFAC Symposium on System Identification, 11-13 July2012, Brussels, Belgium (pp. 1761-1766). Brussels, Belgium.

Mesbah, A., Bombois, X., Forgione, M., Ludlage, J.H.A., Moden, P.E., Hjalmarsson, H. & Hof,P.M.J. Van den (2012). A unified experiment design framework for detection andidentification in closed-loop performance diagnosis. In Proceedings of the 51st IEEEConference on Decision and Control (CDC 2012), 10-13 December 2012, Maui, Hawai(pp. 2152-2157). Piscataway: IEEE.

Mesbah, A., Bombois, X., Ludlage, J.H.A. & Hof, P.M.J. Van den (2012). Experiment designfor closed-loop performance diagnosis. In J. Schoukens & R. Bitmead (Eds.), Proceedingsof the 16th IFAC Symposium on System Identification (SYSID 2012), 11-13 July 2012,Brussels, Belgium (pp. 1341-1346). Brussels, Belgium: IFAC.

Mutsaers, M.E.C. & Weiland, S. (2012). A model reduction strategy preserving disturbancedecoupling properties. In Proceedings of the 20th International Symposium onMathematical Theory of Networks and Systems (MTNS 2012), 9-13 July 2012, Melbourne,Australia. Melbourne, Australia.

Mutsaers, M.E.C., Ozkan, L. & Backx, A.C.P.M. (2012). Energy flow scheduling for parallelrunning batch processes. In Proceedings of the 31th Benelux Meeting on Systems andControl, 27-29 March 2012, Heijen/Nijmegen, The Netherlands (pp. 32-32).

Mutsaers, M.E.C., Ozkan, L. & Backx, A.C.P.M. (2012). Scheduling of energy flows for parallelbatch processes using max-plus systems. In Proceedings of the International Symposiumon Advanced Control of Chemical Processes, (ADCHEM 2012), 10-13 July 2012,Singapore (pp. 614-619).

Mutsaers, M.E.C., Weiland, S., Rooij, L. van & Op den Camp, O.M.G.C. (2012). Pre-crashpassenger safety in cars: a model based control approach. In Proceedings of the 31thBenelux Meeting on Systems and Control, 27-29 March 2012, Heijen/Nijmegen, TheNetherlands (pp. 168-168).

Pham, H.T., Bosch, P.P.J. van den, Kessels, J.T.B.A. & Huisman, R.G.M. (2012). Integratedenergy and thermal management for hybrid electric heavy duty trucks. In Proceedingsof the IEEE Vehicle Power and Propulsion Conference(VPPC), October 9-12, 2012,Seoul, Korea (pp. 932-937). Piscataway: IEEE.

Rakovic, S.V., Gielen, R.H. & Lazar, M. (2012). Construction of invariant families of sets forlinear systems with delay. In Proceedings of the American Control Conference (ACC2012), 27-29 June 2012, Montreal, Canada (pp. 6246-6251). Piscataway: IEEE ServiceCenter.

Rosca, B., Kessels, J.T.B.A., Bergveld, H.J. & Bosch, P.P.J. van den (2012). On-line parameter,state-of-charge and aging estimation of Li-ion batteries. In Proceedings of the IEEEVehicle Power and Propulsion Conference(VPPC), October. 9-12, 2012, Seoul, Korea(pp. 1122-1127). Piscataway: IEEE.

Sijs, J. & Papp, Z. (2012). Towards self-organizing Kalman filters. In Proceedings of the 15thInternational Conference on Information Fusion (Fusion ’12), 9-12 July 2012, Singapore(pp. 1-8).

Siraj, M.M. & Toth, R. (2012). On the problem of model reduction of LPV systems. In 31stBenelux Meeting on Systems and Control, 27-29 March 2012, Heijden, The Netherlands.


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Siraj, M.M. & Weiland, S. (2012). On H-inf optimal model reduction and invariance of robuststability margin for descriptor systems. In 2nd International Workshop on Model Reductionfor Parameterized Systems (MoRePaS II) , 2-5 October 2012, Günzburg, Germany.

Siraj, M.M., Toth, R. & Weiland, S. (2012). Joint order and dependency reduction for LPVstate-space models. In Proceedings of the 51st IEEE Conference on Decision and Control(CDC 2012), 10-13 December 2012, Maui, Hawai (pp. 6291-6296). Piscataway: IEEEService Center.

Spinu, V. & Lazar, M. (2012). A hybrid polytopic partition approach to constrained stabilizationof bilinear systems. In Proceedings of the 4th IFAC Nonlinear Model Predictive ControlConference, 23-27 August 2012, Noordwijkerhout, The Netherlands (pp. 430-435).Amsterdam: Elsevier.

Spinu, V. & Lazar, M. (2012). Integration of real-time and stability constraints via hybrid polytopicpartitions. In Proceedings of the 2012 IEEE International Conference on ControlApplications (CCA), 3-5 October 2012, Dubrovnik, Croatia (pp. 226-233). Piscataway:IEEE Service Center.

Spinu, V., Dam, M. & Lazar, M. (2012). Observer design for DC/DC power converters withbilinear averaged model. In Proceedings of the 4th IFAC Conference on Analysis andDesign of Hybrid Systems (ADHS 12), 6-8 June 2012, Eindhoven, The Netherlands (pp.204-209). Oxford: Pergamon.

Spinu, V., Oliveri, A., Lazar, M. & Storace, M. (2012). FPGA implementation of optimal andapproximate model predictive control for a buck-boost DC-DC converter. In Proceedingsof the 2012 IEEE International Conference on Control Applications (CCA), 3-5 October2012, Dubrovnik, Croatia (pp. 1417-1423). Piscataway: IEEE Service Center.

Taamallah, S., Bombois, X. & Hof, P.M.J. Van den (2012). Optimal control for power-off landingof a small-scale helicopter : a pseudospectral approach. In Proceedings of the 2012American Control Conference (ACC 2012), 27-29 June 2012, Montréal, Canada (pp.914-919). Piscataway: IEEE.

Toth, R., Hjalmarsson, H. & Rojas, C.R. (2012). Order and structural dependence selection ofLPV-ARX models revisited. In Proceedings of the 51st IEEE Conference on decision andcontrol (CDC 2012), 10-13 December 2012, Maui, Hawai (pp. 6271-6276).

Toth, R., Hjalmarsson, H. & Rojas, C.R. (2012). Sparse estimation of polynomial dynamicalmodels. In M. Kinnaert (Ed.), Proceeding of the 16th IFAC Symposium on SystemIdentification, 11-13 July 2012, Brussels, Belgium (pp. 983-988). Brussels, Belgium.

Verkerk, K.W., Achterberg, J., Lierop, C.M.M. van & Weiland, S. (2012). Modal observer designfor a flexible motion system with state dependent sensor positions. In Proceedings of the51st IEEE Conference on Decision and Control (CDC), 10-13 December 2012, Maui,Hawaii (pp. 4498-4504). Piscataway: IEEE Service Center.

Virag, A., Jokic, A. & Bosch, P.P.J. van den (2012). General framework for real-timeimplementation of balancing services market outcome. In Proceedings of the 8th PP&PSC(Power Plant and Power System Control) Symposium, 2-9 September 2012, Toulouse,France.

Virag, A., Jokic, A., Lampropoulos, I., Hermans, R.M. & Bosch, P.P.J. van den (2012). Analternative approach for real-time balancing of electrical power systems. In Proceedingsof the 2012 9th International Conference on the European Energy Market (EEM), 10-12May 2012, Florence, Italy (pp. 1-7). Piscataway: IEEE Service Center.

Zaman, M.S., Poshtkouhi, S., Palaniappan, V., Li, K.W., Bergveld, H.J., Myrskog, S. & Trescases,O. (2012). Distributed power-management architecture for a low-profile concentrating-PVsystem. In Proceedings of the 2012 15th International Power Electronics and MotionControl Conference (EPE/PEMC), 4-6 September 2012, Novi Sad, Serbia (pp. LS2d.4-1/8).Piscataway: IEEE.


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Ph.D. theses

Distributed Control of Deregulated Electrical Power Networks. Thesis Ralph Hermans 20November 2012.

Ezzeldin Mahdy Abdelmonem, M. (2012, april 25). Performance improvement of professionalprinting systems : from theory to practice. TUE : Technische Universiteit Eindhoven (161pag.) (Eindhoven: Technische Universiteit Eindhoven). Prom./coprom.: prof.dr.ir. P.P.J.van den Bosch & prof.dr. S. Weiland.

Hermans, R.M. (2012, november 20). Distributed control of deregulated electrical powernetworks. TUE : Technische Universiteit Eindhoven (182 pag.) (Eindhoven: TechnischeUniversiteit Eindhoven). Prom./coprom.: prof.dr.ir. P.P.J. van den Bosch, dr. M. Lazar &dr. A. Jokic.

Mutsaers, M.E.C. (2012, september 06). Control relevant model reduction and controllersynthesis for complex dynamical systems.TUE : Technische Universiteit Eindhoven (195pag.) (Eindhoven:Technische Universiteit Eindhoven). Prom./coprom.: prof.dr. S.Weiland& prof.dr.ir. A.C.P.M. Backx.

Sijs, J. (2012, april 26). State estimation in networked systems. TUE : Technische UniversiteitEindhoven (173 pag.) (Eindhoven: Technische Universiteit Eindhoven). Prom./coprom.:prof.dr.ir. P.P.J. van den Bosch & dr. M. Lazar.

Vissers, J.A.W. (2012, oktober 16). Model-based estimation and control methods for batchcooling crystallizers. TUE : Technische Universiteit Eindhoven (235 pag.) (Eindhoven:Technische Universiteit Eindhoven). Prom./coprom.: prof.dr.ir. A.C.P.M. Backx & prof.dr.S. Weiland.

M.Sc. theses

Chen, Handian (2012). Battery charging control based on charge acceptance estimation.Doban, A.I. (2012). Finite-time contractive sets for discrete-time homogeneous systems with

an application in control of power electronics.Driessen, P.A.A. (2012). Non-centralized economic model predictive control applied to frequency

control.Heijerman, J. (2012). Transformer modeling in the Port-Hamilton framework.Imangaliyev, S. (2012). Applications of multivariable data analysis for food process monitoring

: hierarchical multiblock models and process chemometrics.Insuasty Moreno, E.G. (2012). Advanced thermo-mechanical modeling for reticle stages in EUV

lithography.Qureshi, F. (2012). Real-time control of high precision industrial current amplifiers.Siraj, M.M. (2012). On invariance of robust stability margin and H-infinity optimal model reduction

for descriptor systems.Slaats, N.J.H. (2012). Flyback converter efficiency optimization by non-linear mode selection.Sonin, S. (2012). Design of a model for the prediction of aberration sensitivities in

nanolithography process.Stuijvenberg, M.M. (2012). Optimal experiment design for linear multi-variable closed-loop

process identification.Verkerk, K.W. (2012). Model observer design for a flexible motion system with state dependent

sensor positions.Wang, Haixu (2012). Distributed lighting control of locally intelligent luminaire systems.Wortel, K.I. (2012). A smart optimization strategy for charging a network of electric vehicles.


155

Other publications

Bergveld, H.J., Myrskog, S. & Trescases, O. (2012, februari 05). Power electronics forphotovoltaic systems : devices, circuits and trends. Orlando, Florida, USA, Applied PowerElectronics Conference and Exposition, APEC 2012, 5 February 2012, Orlando, Florida.

Bresser, B.W.J. de (2012). Control of a 3-phase interleaved converter operating in continuousand discontinuous conduction mode. (Master graduation paper, Electrical Engineering242). Eindhoven: Technische Universiteit Eindhoven.

Habets, M.B.I. (2012).Thermal modeling of LED platforms. (Technische Universiteit Eindhoven(TUE). Capaciteitsgroep Meet- en Besturingssystemen (MBS). Sectie Control Systems.247). Eindhoven: Technische Universiteit Eindhoven.

Pisarenco, M., Maubach, J.M.L., Setija, I.D. & Mattheij, R.M.M. (2012). Efficient solution ofMaxwell's equations for geometries with repeating patterns by an exchange ofdiscretization directions in the aperiodic Fourier modal method. (CASA Report 12-34).Eindhoven: Technische Universiteit Eindhoven.

Rakovic, S.V., Gielen, R.H. & Lazar, M. (2012). Construction of invariant families of sets forlinear systems with delay. Eindhoven University of Technology: Technical report.


156

University of TwenteRobotics and Mechatronics(RaM)(Formerly ControlEngineering (CE))

General Information

AddressUniversity of Twente, Faculty of Electrical Engineering, Mathematics and Computer Science,Department of Electrical Engineering, Control Engineering group, P.O. Box 217, 7500 AEEnschede, The Netherlands. Phone (secretariat): 053 – 489 2606. Fax (secretariat): 053 –489 2223. E–mail (secretary): [email protected], web: http://www.ce.utwente.nl

Scientific staffDr.ir. Peter Breedveld, dr.ir. Jan Broenink, Dr. Raffaella Carloni, dr. Angelika Mader, dr.Sarthak Misra, Prof.dr.ir. Stefano Stramigioli, Dr.ir. Theo de Vries

Technical and administrative staffJolanda Boelema-Kaufmann, Carla Gouw-Banse (till July 2012), ing. Gerben te Riet o/gScholten, ing. Marcel Schwirtz, Alfred de Vries (till March 2012)

PhD studentsGeert Folkertsma MSc (since Oktober 2012), Drs.Ing. Ton Boode (since September 2012),Dian Borgerink MSc (since April 2012), Stefan Groothuis MSc (since Jan 2012), MomenAbayazid MSc, Roy Roesthuis MSc, Israel Nunez Hernandez MSc, ir. Edwin Dertien,Ramazan Unal MSc, Ludo Visser MSc, ir. Maarten Bezemer, Yury Brodskiy MSc, O uzcanO uz MSc, Bart Peerdeman MSc, Xiaochen Zhang MSc, Yunyun Ni MSc, Abeje YenehunMersha MSc, Tadele Shiferaw Tadele MSc, Alex Jahya MSc, Bayan Babakhani MSc (tillOktober 2012), Rob Reilink MSc (till November 2012),

Temporary staff and postdocsHao Sun PhD (till September 2012), Matteo Fumagalli PhD, Wissam Assaad PhD (till August2012), Islam Khalil PhD, ir. Dirske Kranenburg-de Lange, ing. Matthijs Roorda (till March2012), drs. Jarno de Vries, Robbert Wilterdink MSc, Jos Vos MSc, em. prof.dr.ir. Job vanAmerongen,

Cooperation withDLR (DE), ETHZ (CH), University of Bologna (IT), University of Napels (IT), University ofBergamo (IT), University of Pisa (IT), Superlec (FR), DEMCON (NL), PHILIPS (NL),MEDTRONIC (USA), OSSUR (IS), RDD (NL), Fraunhover IPA (DE), KU Leuven (BE), Kuka(DE), Kiwa Gastech (NL), Van der Lande (NL), ANU (AU), UMCU (NL), UMCR (NL), UMCG(NL), RUNMC (NL), University of Utrecht (NL), TUD (NL), Xivent (NL), Siemens BV (NL)ItalianInstitute of Technology (IT, Imperial College (UK), Alstom Inspection Robotics (CH), RadboudUniversity Nijmegen (NL), TU/e (NL), Oce research (NL), ASML (NL), University of Newcastleupon Tyne (UK), Aarhus University (DK), Chess eT International B.V. (NL), Chess iTInternational B.V. (NL), Controllab Products BV (NL), Neopost Technologies BV (NL),Verheart New Products and Services NV (B), GPS (DE), Bluebotics (DE), HAN (NL), TCNN(NL), FH Munster (DE), FH Gelsenkirchen (DE), University of Duisburg-Essen (DE),Leadpartner en NL adviseurs: Euregio (DE/NL), Syntens (NL), STODT (NL), IMOTEC (NL),

University of TwenteRobotics and Mechatronics(RaM)(Formerly Control Engineering (CE))

157

Hankamp Gears (NL), KMG Neede (NL), BAM Techniek B.V. (NL), Vrije Universiteit Brussel(BL),Witteveen en Bos (NL), TASS Technology Solutions (NL),

Locomotec (DE), Exact Dynamics (NL)

Keywordscontrol, modeling, simulation, intelligent control, embedded control systems, robotics,measurements, instrumentation, walking robots, haptics, tele manipulation, mechatronics,mechatronic design, micro mechatronics, design tools, port-based modeling, bond graphs,controller agents, distributed control

Brief descriptionThe research of the group has always focused on mechatronics and has currently beenextended to focus on robotic systems. The Research Area of the group is novel technologyand scientific methodologies for the design and development of complete robotic systemsand similar intelligent devices, i.e. cyber-physical systems. The binding paradigm is the useof port-based methodologies for modeling, control, embedded software and design ofmechatronics and robotics systems for real applications.

The group focuses on understanding the fundamental properties governing the dynamicand interacting behavior of mechatronic and robotic systems (modeling) and creates completesystems achieving the desired behaviors (control, embedded and design).This is done usingport-based concepts (bond-graphs, port-Hamiltonian systems and process-oriented softwarestructures). This paradigm is a common factor in the group. The port-based paradigm hasproven successful in finding effective solutions for problems like telemanipulation with timedelays, novel passive non-linear control strategies, power distribution, etc. Once a problemhas been modeled, extensive simulations are run, mostly with the 20sim package of ControllabProducts, one of the spin-off enterprises of the group.This software is growing in recognitionand is now, among others, also used for multi-physics simulations by the European SpaceAgency. These results are followed by creative sessions to make choices on directions tobe followed to solve the problem at hand. The solutions are then evaluated again, both viasimulation and real realization of mechatronic systems and their embedded control software.The special mechanical parts are 3D-printed, or made by the group’s local contacts (SMEor Saxion University of Applied Sciences). A specific part of the group is responsible for thecomputational and architectural part of the systems to be developed and performs researchin Embedded Systems for this goal.

The chair is part of the 3TU Center of Excellence on Intelligent Mechatronic Systems for itsactivities and expertise in the Robotics field. The research of Control Engineering is carriedout in the IMPACT, MIRA and CTIT Institutes.

Strong collaborations with the Mechatronic Valley Twente and national industries like Philips,TNO, ESA, OCE, Thales are taking place. The Chair has a leading role in the LEO initiative.LEO Center of Service Robotics is at this stage a cluster of regional enterprises and groupsworking in robotics and will have a physical space to display what robotics is and what canbe used for in our society. The ambition is to become a reference point for robotics in theNetherlands.

Results of research by PhD and MSc students also find their way into tools for mechatronicdesign. Due to the cooperation with our spin-off company Controllab Products these resultsbecome globally available after some time, mostly in the form of extensions of the mechatronicdesign program 20-sim.


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General Information

Temporary staff and postdocsRobert Wilterdink MSc.

General Information

Temporary staff and postdocsMatteo Fumagalli PhD

General Information

Temporary staff and postdocsJos Vos MSc

General Information

Temporary staff and postdocsdr. Shodhan Rao

General Information

Temporary staff and postdocsHao Sun PhD

General Information

Temporary staff and postdocsIslam Khalil PhD

Medical Robotics

In this program developments are taking place which have directly or indirectly to do with thehuman body. The program is composed of two parts.

• Robotic Surgery in which new robotic instruments and methodologies are studied withprojects like Teleflex and Miriam.

• Prosthetics is related to the development or artificial limbs like transradial hand prosthesis(MyoPro) and transfemoral leg prosthesis.

Inspection Robotics

In this program the use of robotics technologies is investigated for tasks in which inspection ofnot easily reachable structures is necessary. This can be the case for underground gas mainslike in the project Pirate, high structures or plans like in the flying robot Airobots, continuousmonitoring of the dutch dikes like in the project Rose or even modeling for inspection of spacerovers in collaboration with ESA for the Exomars. For the latter the modeling of altitude mapsand their use in the prediction of the navigation of the ExoMars rover is considered. Problemswhich arise in this study relate a combination of sparse altitude data with precise terramechanics


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simulations. This is tackled using a hybrid use of differential geometric techniques andcomputational geometric methods.

Home & Care robotics

This program deals with development of methods and techniques to design service robots.These robots have to act in an unstructured environment, and have regularly and deliberatelyphysical contact with its environment. Contexts in which these robots have to act are normal(household) situation and care taking situations. Topics of study are robot architectures thatfacilitate resilient, robust and fault-tolerant behavior of the autonomous service robot.

Modeling

The central theme of this research line is an inter-disciplinary, integrated, port-based approachto the modeling of physical system behavior in various engineering domains, in particular thoserelated to robotics and mechatronics. It follows an energy-based approach, making extensiveuse of the (multi-)bond graph notation, and is subdivided in several classes of projects.

Where applicable, the modeling activities of the laboratory are used as a basis to generatere-usable, generic (sub-) model structures of various engineering systems.

Control

Work in this research line deals with application and further investigation of control schemesnecessary for robotic systems. The focus is on intrinsic stability through passivity; smoothoperation of contact behavior; resilient robotic behavior via robustness of the control schemesand robot architectures. Model-driven controller design techniques and a holistic, systemsengineering view are preferred approaches. The resulting controller schemes are inspired byand applied to the robotic applications developed in our application domains. Proofs of principleare validated using small setups, exhibiting the relevant essential behavior.

Embedded

This research line deals with the realization of control schemes on digital computers. Theultimate goal is to support the mechatronic / robotic design engineer such that implementingcontrollers according to “do it the first time right” becomes business as usual.

Simulation and formal methods are used as a means for verification at all stages of the designprocess. This facilitates concurrent engineering. Robot Software Architectures are tuned to fitin our design approach, to obtain an effective realization trajectory.

Furthermore, the use of parallel hardware and parallel software is investigated, to exploit theinherent parallel nature of embedded systems and their control.

Design

This research line deals with developing and applying methods for design of robots. Model-drivenand a system's (i.e. mechatronic) approaches are used, to take best advantage of possibilitiesoffered by all domains involved.

Focus is of course on robotic systems. The design methods being developed are tried out onour robotic setups, which serve as initial test. Via design projects in which industry is involved,further development and testing of the design methods are conducted.


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DISC projects

Smartbot - Roboship (since April 2012)

Prof.dr.ir. Stefano StramigioliProjectleader:Dian Borgerink MScPhD students:INCASSponsored by:

DescriptionRobots that are equipped with several sensors (multi-sensor robots) are called SmartBots.Sensor system technology and ICT enable robots to operate autonomously and on morecomplex tasks. Robots become smarter and therefor can be applied in more areas thanever before. Robots will become a key success factor when it comes to applications inindustrial, agricultural or other economic sectors.

SmartBot is a cross-border collaboration between 24 different partners from Germany andthe Netherlands.The aim is to develop multi sensor robot platforms for maritime, agriculturaland industry applications. The SmartBot project strengthens the collaboration betweendifferent parties in both economical and technological ways. The project also helps createa global knowledge hotspot on sensor robotics in the border-region of Germany and theNetherlands.

The SmartBot project consists of three sub projects:• Roboship (shipping industry): an autonomous intelligent robot for the inspection and

repair of ballast water tanks of ships.• Sinbot (industry): a pilot environment for intelligent use of industrial robotics in a

production environment. The first application will be focused on the production ofcomposite material for the transport sector.

• AgroBot (agriculture): (semi) autonomous robot systems operating in dynamicalenvironments.These systems will be able to work on complex tasks without damagingthe environment (for example a robot that recognizes and pulls out the weeds).

Our group is participating in the Roboship project:

Shipping industry is extremely competitive. European warfs stay ahead of the internationalcompetition by specialization in building for instance cruise ships, offshore equipment and–ships and ship with high added value.These warfs will have to lower their production costs.They can standardize components, processes an d design and automize a great share oftheir production process. The Meyer Werft in Papenburg is an example of a warf with aleading position in the world market for cruise ships, because they have been able to dothis.

Despite of all the innovations in the shipping industry there are still many processes thatneed to be carried out by hand, such as welding, welding inspection, cleaning, coating andinspection of the ballast watertanks. These tanks are used to stabilize a ship. They areconstructed in a way that it is hard for people to access them. It is even very difficult to haverobots work in them.

So far we have been unable to automize the maintenance of ballast-water tanks.The purposeof RoboShip is to develop an intelligent multi-sensor robot system for inspection andmaintenance of the water ballast tanks in ships such as the ones being built at the MeyerWerft.


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IVIA (since January 2012)

Dr. Raffaella CarloniProjectleader:Prof.dr.ir. Stefano StramigioliParticipants:Stefan Groothuis MScPhD students:Exact DynamicsSponsored by:

DescriptionPeople with moderate or severe upper extremity disabilities, caused by various diseases orinjuries, find themselves in need of continuous personal care, since even the simplest taskcannot be performed independently.This complete dependence on others has a tremendousimpact on the impaired person’s quality of life and on societal healthcare expense.Therefore,robotic aids to assist impaired people is becoming increasingly popular. Unlike task-restricteddevices like feeding-aids and pageturners, multi-purpose robotic arms can assist the impairedin a variety of tasks and are often mounted on a wheelchair for increased mobility. However,since these arms are traditionally powered by stiff actuators, interaction safety is not easilyguaranteed, because interaction control is not robust due to control bandwidth limitations.The novel variable impedance actuation technology enables the adaptation of physicalactuator output impedance (e.g. stiffness) independently from the actuator output position.This means that the physical impedance can be tuned to instantaneous safety requirements,thereby providing intrinsic safety by means of physical elasticity.

The goal of this project is to research and develop an intelligent variable impedance arm,aimed at assisting physically impaired people. Intelligence that can be embedded is, forinstance, the autonomous tuning of impedance based on specific task intentions and exploitingthe internal actuator elasticity for more energy efficient motion control.

Ongoing workThe optimization of a robotic manipulator configuration (the distribution of different types ofactuators) has being researched. Since the number of possible configurations rapidly growsfor an increasing number of degrees of freedom, an optimization framework is necessary.Graph theory is currently being used, on a 2-dof planar manipulator, to allow thestraightforward extension to higher dimensional problems. Ongoing work is to investigatewhether consensus theory (described on graphs) can be used to approach the problem. Inconsensus theory, a network of leader and follower agents is considered, where all agentshave to reach the same state, i.e., consensus on the state, after some time. However, anappropriate control input on the leader agents allows to steer them in a certain direction,such that the follower agents, who receive (state) information through the network, follow adesired trajectory, which may be equivalent to a required task for the manipulator end-effector.A criterion for an optimal manipulator configuration is minimizing the required control effort,which may be accomplished by changing the network topology or agent properties.


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FREEQ (since October 2012)

Prof.dr.ir. Stefano StramigioliProjectleader:Geert Folkertsma MScPhD students:DISCSponsored by:

DescriptionFast-Running, Energy-Efficient Quadruped: bringing together morphological computation,biomimetics and Port-Hamiltonian Systems to design a high-performance quadrupedal robotwith inherent locomotion behavior.

Ongoing work• Validation / proof-of-principle geometric bond graph modelling of spine• Extracting motions from video material of cheetahs

–- Extracting motions from simple models

–- Calculating power-continuous storage functions that duplicate simple model behaviour

–- Extending both methods to the real cheetah footage

AuPertProc (since October 2012)

Jan BroeninkProjectleader:Ton BoodePhD students:DISCSponsored by:

BRICS

Prof.dr.ir. Stefano StramigioliProjectleader:dr.ir. Jan Broenink, dr. Angelica MaderParticipants:Yury Brodskiy MSc, Israel Nunez Hermandez MScPhD students:

DISC projects

EU-FP7Sponsored by:

DescriptionEven after 50 years of robotics development and research the process of developing a newrobot and its applications has more similarities with ingenious engineering or designing apiece of artwork than with a structured and well-defined process.This holds particularly truefor advanced service robot systems. The prime objective of BRICS is to structure andformalize the robot development process itself and to provide development tools,computational models, and functional libraries, which allow engineers and developers ofcomplex robotic systems to reduce the development time and effort by an order of magnitude.

BRICS will work together with academic and industrial providers of robotic components –both hardware and software – to identify and document best practices in the developmentof complex robotics systems, to refactor existing components in order to achieve a much


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higher level of reusability and robustness, and to support the robot development processwith a well-structured tool chain and a repository of reusable, configurable code.

BRICS is a joint research project funded by the European Commission ICT Challenge 2under grant number 231940.

VIACTORS (till Jan 2012)

dr. Raffaella CarloniProjectleader:prof.dr.ir. Stefano StramigioliParticipants:Ludo Visser MSc, ir. Gijs van OortPhD students:EU-FP7Sponsored by:

DescriptionThe European Project VIACTORS has been financed in the Seventh Framework ProgrammeFP7-ICT-2007-3 in the call ICT-3-8.5 on Embodied Intelligence. The consortium is formedby: Deutsches Zenstrum für Luft und Raumfahrt (Coordinator), University of Pisa, Universityof Twente (Scientific Co-Coordinator), Imperial College London, Italian Institute ofTechnology), Vrije Universiteit Brussel.

The project focuses on the development and exploitation of actuation technologies for anew generation of robots that can co-exist and co-operate with people and get much closerto the human manipulation and locomotion performance than today’s robots do.This meansthat the aim is to design systems that embody the physical principles, which shape thedesired robot behavior as much as possible and thus reducing the required control effort. Itis expected that in this way the system will be intrinsically energy efficient, safe, and robustagainst external perturbations.The idea is to achieve this embodiment of behavior by meansof variable impedance actuation, i.e. changing the apparent interface impedance of anactuator and thus change the system behavior.

The work of the project is approached on three levels:

Analysis of the physical and biological principles, which will constitute the bases of designand control of variable impedance actuators.

Design of new robot actuators in which much of the motion intelligence is embodied in themorphology of the structure. This will also result in conceptual new paradigms for control totune compliance, enforce safety and strongly improve energy efficiency.

Evaluation in three distinct application aspects, namely robotic manipulation, bipedallocomotion, and rehabilitation robots.

The focus for the UT is in the application of these kinds of actuator systems in the field of(bipedal) locomotion.The goal is to design locomotion systems that come closer to biologicalsystems in terms of energy efficiency, robustness and adaptability.

The main objectives are to analyze, simulate and develop legged locomotion systems basedon the principles of variable impedance actuation. These systems should be robust undersubstantial disturbances and at the same time efficient in terms of energy consumption.Thework will be based on biologically inspired mechanisms, as nature provides ample examplesof robust, energy efficient walking mechanisms.

The work is organized into the following phases:


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Morphological analysis of walking systems: given any morphology, which walking patternscan be realized. Given a feasible walking pattern, what are the requirements for the actuatorsand what can be said about the influence of disturbances on this particular pattern?

Implementation on humanoid robots: how can we apply the newly developed actuationtechniques to existing robots to improve their performance?

Modelling and simulation of walking: learn more about the physical coupling and energyexchange between the various components of locomotion systems.

New prototype: design new walking systems that optimally incorporate the new actuationtechniques.

Several students are, or have been, involved in VIACTORS: two PhD students (Gijs vanOort and Ludo C.Visser), two MSc students (Luciana Cicchitti and Matin Jafarian), two BScstudents (Feite Klijnstra and Bart Reefman).

This project aims at developing and exploiting actuation technologies for a new generationof robots that can co-exist and co-operate with people and get much closer to the humanmanipulation and locomotion performance than today’s robots do. At the same time theserobots are expected to be safe, in the sense that interacting with them should not constitutea higher injury risk to humans than the interaction with another cautious human.This requiresthat robots with similar size and mass as the humans also have comparable power, strength,velocity and interaction compliance.

This ambitious goal can, however, not be achieved with the existing robot technology, inwhich the robots are designed primarily as rigid position or torque sources and mostinteraction skills are imposed by virtue of control software. Also, conventional robots in whichinteraction is controlled by software only, could not avoid an impact to damage the robotand possibly the human neighbor, as the controller will react with some delay. This projectwill develop both a solid theoretical understanding and the enabling technologies for thedesign of a new generation of robot actuator systems, capable of embodying the physicalprinciples which shape the robot behavior.

The focus of the work will be on achieving different abilities, in particular:

Efficiency (e.g. natural gait generation and adaptation in legged locomotion applications);

Robustness to external perturbations and unpredictable model errors (changes) of theenvironment, of the robot kinematics and dynamics, or of the dynamics of a human interactingwith;

Adaptability and force accuracy in the interaction with the operator, in applications in whichcontinuous contact and accurate force exchange is necessary, such as in “hands-on” assistivedevices, rehabilitation, exoskeletons and haptics;

Safety to humans (and resilience to self-damage) in operations where the robot is requiredpositional accuracy and swiftness of motion, while cooperating, physically interacting oreven possibly colliding with the humans and their environment, such as e.g. in collaborativerobotics.

To tackle this goal, this project uses the concept of Variable Impedance Actuation. The keyinnovation of the project is the development, exploitation and integration of VariableImpedance Actuator Systems both in manipulation, locomotion and rehabilitation.

For developing these new kinds of actuator systems, it is critical to understand in depth themechanisms by which the efficiency, motion performance, and safety are obtained in biologicalsystems and in particular by humans.


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Taking the state of the art in artificial muscles into account, our major goal is not bio-mimesisper se, but rather to develop actuation systems with similar functional properties as theneuro-mechanical system in humans. In other terms, a part of the necessary intelligencehas to be embedded (embodied) in the systems themselves, which should be able to passively(or almost passively) be safe, efficient, compliant, etc.

This idea will be approached on three levels within the project:

The first objective is to work out the physical and biological principles which will constitutethe bases of the mentioned shift of paradigm in embodiment, design and control.

The gained knowledge will be then used to design new robot actuators following theseprinciples. The approach should result in a very innovative kind of robots, in which much ofthe motion intelligence is embodied in the morphology of the structure. This will also resultin conceptual new paradigms for control to tune compliance, enforce safety and stronglyimprove energy efficiency.

The fundamentals elaborated as described above, will be applied and evaluated to three

distinct application aspects, namely robotic manipulation, bipedal locomotion, andrehabilitation robots.

Several partner labs already have first prototypes of variable impedance actuated systemsavailable or under development within predecessor projects which will be used as earlyevaluation platforms for the

mentioned application areas. Of particular relevance here is the FP6 PHRIENDS project(www.phriends.eu), which is widely recognized as a worldwide pioneer of the variable stiffnessactuation approach to safe and dependable robotics, and whose legacy of highly innovativeresults will be inherited and capitalized upon by VIACTOR

A constructive method for modeling and controlling a bipedal walker using variable stiffnessactuation principles has been presented. Starting from a conceptual bipedal spring-loadedinverted pendulum with controllable stiffness, the model is iteratively refined, adding swingdynamics and knees, to more closely resemble a robotic walker. In parallel, a control strategyis derived that is sufficiently robust to handle the more complicated dynamics of subsequentmodels. Furthermore, it has been shown that the control strategies are energy-efficient byexploiting the compliance of the legs.The result is a template model and an energy-efficientcontroller that can serve as the basis for bipedal robot control. Finally, the proposed controllerhas been validated by both numeric simulations and experimental tests.


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AIROBOTS

Dr. Raffaella CarloniProjectleader:prof.dr.ir. Stefano StramigioliParticipants:Abeje Yenehun Mersha MScPhD students:

DISC projects

EU-FP7Sponsored by:

DescriptionThe goal of the AIRobots project is to develop a new generation of aerial service robotscapable to support human beings in all those activities, which require the ability to interactactively and safely with environments not constrained on ground but, indeed, freely in air.The step forward with respect to the classical field of aerial robotics is to realize aerial vehiclesable to accomplish a large variety of applications, such as inspection of buildings and largeinfrastructures, sample picking, aerial remote manipulation, etc.

The starting point is an aerial platform whose aero-mechanical configuration allows thevehicle to interact with the environment in a non-destructive way and to hover close tooperating points. Rotary-wing aerial vehicles with shrouded propellers represent the basicairframes, which will be then equipped with appropriate robotic end-effectors and sensorsin order to transform the aerial platform into an aerial service robot, a system able to fly andto achieve robotic tasks.

Advanced automatic control algorithms will be conceived to govern the aerial platform, whichwill be remotely supervised by the operator with the use of haptic devices. Particular emphasiswill be given to develop advanced human-in-the-loop and autonomous navigation controlstrategies relying upon a cooperative and adaptive interaction between the on-board automaticcontrol and the remote operator. Force and visual feedback strategies will be investigatedin order to transform the aerial platform in a “flying hand” suitable for aerial manipulation.

The consortium is composed by four academic groups (University of Bologna-Italy, ETHZurich-Switzerland, University of Naples Federico II-Italy, and University of Twente- TheNetherlands) and an industry, ALSTOM Inspection Robotics, which ha the role of end-userand evaluator of the project outcomes for the specific application of robotic inspection ofpower plants.

Prototypes of aerial service robots will be developed within AIRobots and tested onexperimental setups, which will be constructed in order to reproduce typical industrialscenarios, envisaged by ALSTOM Inspection Robotics, in which aerial inspection roboticcan be beneficial. The prototypes will be specifically tested on tasks such as docking andundocking from structures, cleaning, inspection and repairing of infrastructures, payloadlifting, and others operations requiring safe interaction between the aerial platform and theenvironment.

Advanced automatic control algorithms will be conceived to govern the aerial platform whichwill be remotely supervised by the operator with the use of haptic devices. Particular emphasiswill be given to develop advanced human-in-the-loop and autonomous navigation controlstrategies relying upon a cooperative and adaptive interaction between the on-board automatic


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control and the remote operator. Force and visual feedback strategies will be investigatedin order to transform the aerial platform in a "flying hand" suitable for aerial manipulation.

Ongoing workA theoretical formulation and practical realization of a generic passive controller for hapticteleoperation of aerial robots, which comprehensively addresses both peculiar and classicalchallenges in the field, have been proposed. More specifically, the control scheme consistsof a user-defined variable scale mapping, a variable impedance master controller and avirtual slave system. The controller is characterized by its clear distinction between thehigh-level bilateral teleoperation and low-level dynamic regulation control loops.The presenceof the variable impedance master controller and the virtual slave system in the teleoperationloop makes it applicable to a wide range of tasks and operating conditions. Furthermore,the multidimensional treatment of the control scheme adds to its generic nature. Simulationand experimental results have been performed, validating the applicability and effectivenessof the proposed control architecture.

Moreover, a robotic arm for flying inspection and manipulation, that is meant to be mountedon an unmanned aerial vehicle with medium payload capabilities, has been designed andrealized. The combination of the flying vehicle and the robotic arm realizes the flying handof a remote operator. The result of the design consists of a lightweight robotic arm thatfeatures properties such as modularity, versatility and compliance. The kinematics and thedynamics of the overall flying robot have been derived and exploited to perform trajectorytracking and interaction control. Simulations and experiments show the effectiveness of theproposed design and an overview of the basic capabilities of the flying hand.

DESTECS

dr.ir. Jan BroeninkProjectleader:dr. Angelika MaderParticipants:Xiaochen Zhang MSc, Yunyun Ni MScPhD students:EU-FP7Sponsored by:

DescriptionThis EU-FP7 funded project (8 partners, UT is coordinator), deals with researching anddeveloping methods and open tools that support collaborative design of dependable real-timeembedded control systems using a model-base approach. Models here are co-modelsconsisting of a discrete event part modeled in VDM, and a continuous time part modeled in20sim. These models are co-simulated. The UT contribution is mostly on design methods,design space exploration and organization and management for models.

TELEFLEX (till June 2012)

prof.dr.ir. Stefano StramigioliProjectleader:dr. Sarthak Misra, dr.ir. Jan BroeninkParticipants:Rob Reilink MSc, ir. Maarten BezemerPhD students:PIDONSponsored by:

DescriptionThe project focusses on the development of a surgical telemanipulation robotic systemsuitable for intuitive control of the next generation surgical instruments for minimal invasivesurgery. The high-tech SME DEMCON is the coordinator.


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BOBBIE

dr.ir. Theo de vriesProjectleader:prof.dr.ir. Stefano StramigioliParticipants:Tadele Tadele Shiferaw MScPhD students:Point OneSponsored by:

DescriptionRecent advances in robotics, mechatronics, computer vision, artificial intelligence, robustautonomy and software allowed the development of personal robots that can be used in ahome environment. These personal robots can typically be applied to assist elderlypopulations in order to relief the pressure on health care systems. With this application areain mind, this project aims to come up with new methods to design a complete robot systemusing standardized architectures which can safely work in a care situation.

This collaboration project consortium consists of the University of Twente, the TechnicalUniversity of Eindhoven, Delft University of Technology, Fontys University of Applied Sciencesand a number of industrial partners in the Netherlands. The core technological focus areasof the project are safe adaptive mobile manipulation and modularity and interoperability inboth hardware and software components. These include:

• Safe navigation in dynamic environments;• Safe manipulator motion in human environments;• Grasping of unknown objects;• Seamless exchangeability of components.

PIRATE

prof.dr.ir. Stefano StramigioliProjectleader:ir. Edwin DertienPhD students:Kiva GastechSponsored by:

DescriptionIn 2007 a mobile inspection system for live gas mains has been developed. This project isa joint effort of Continuon Netbeheer, Kiwa Gastec Technology B.V. and the University ofTwente. The prototype hardware has been developed at DEMCON. The robot is developedfor autonomous internal inspection of the low pressure gas mains, with minimal interventionof human operators. The robot will be used to detect leaks or possible weak points in thegas mains.

In the first stage of this project, the development of a moving mobile robot base has beenemphasized. The low pressure net in the Netherlands uses pipes with an inner diameter assmall as 50 mm, thus putting a severe limitation on the robot's size. A mechanical prototypehas been developed which is capable of moving through pipes ranging in diameter from 50to 120 mm. It can move through mitered bends and T-joints and take inclinations of 30degrees. The robot has the form of a 'snake', consisting of seven wheeled modules whichall have a designated function. Two modules are used for propulsion, two for bending therobot's shape (for navigation trough bends), one module in the center for rotation the robotaround its axis, one module for power storage and one module for control and sensorelectronics. The mechanical setup has been tested in a structured lab environment. Thenext step will be to test the functionality in a more realistic environment.


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On a different level work has been done on the design of a camera setup with structuredlight bundle (laser projecting circles) which can be used as sensor to measure pipedeformation, and which also can be used to detect obstacles and bends which is necessaryfor navigation. In following projects we hope to miniaturize this setup in order to integrate itinto the robot's design.

Ongoing workA new prototype for the PIRATE robot has been realized, completely manufactured using3D printing (Additive Manufacturing) techniques. The realized prototype is lightweight andmore powerful than its predecessor. Besides the movements it completed before it is possiblenow to take a vertical climb as well. Progress has been made on the design of an integratedcamera system.

ROSE

prof.dr.ir. Stefano StramigioliProjectleader:Douwe Dresscher MScPhD students:STWSponsored by:

DescriptionSensor networks are one of the most important technologies in the 21st century; in particular,with recent advances in sensor-equipped autonomous mobile robots, mobile robotic sensornetworks are becoming one of the most strategically important technologies worldwide andhave great potential to be applied to infrastructure security, environment and habitatmonitoring, industrial sensing, traffic control and so on. One of the greatest challenges inthe application of mobile robotic sensor networks is that the performance of such a networkis constrained by the limited available energy supply usually provided by the batteries carriedby each robotic sensor. It is therefore important to consider energy scavenging techniquesin the design of the systems. The aim of ROSE is to develop new energy-efficient designmethodologies and novel control strategies for robotic sensor networks. The key is to takea multidisciplinary and integrative approach by jointly considering the hardware level ofmobile sensor-equipped robotic devices and the system level of wireless coordination ofgroups of mobile robotic sensors. For the design of mobile sensor-integrated robotic devices,research will focus on taking full advantage of newly developed sensors, methodology toharvest and optimize energy sources and integrate such sensors with mobile robotic platforms.With optimal energy consumption and a proper system design, the platforms to be developedwill be able to operate in complex, time-varying, unknown, harsh and hazardous environmentand acquire data reliably via ground penetration radars (GPR), ultrasound imagers, magneticfield detectors and other sensors. Parallel to the development of each individualenergy-conscious robotic sensor, a system level assault on the energy efficient control ofsensor networks will also be carried out. To be more precise, wireless communicationprotocols and distributed coordination algorithms will be developed specifically for swarmsof robotic sensors using ideas from passive systems and port-Hamiltonian systems theory.The proposed research work will make direct contribution to the IJkdijk project for which therobotic sensors and the envisioned network protocols and algorithms can be used to monitorthe dikes. Dike monitoring is an example of a broad range of potential applications of roboticsensor networks for which our proposed research will have fundamental and practicalimplications to energy-efficiency and robustness, under limitations imposed by theinformational structures, physical embodiment, the external world, and their interactions.


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Within this project one of the Ph.D. students will be employed at the Control Laboratory.This Ph.D. student will be responsible for the mechatronic development of the robot includingenergy harvesting, local control and mechatronic design. The other Ph.D. student who willbe employed at the RuG will be mostly involved in the distributed control issues. The teamwill closely work together and have regular meetings.

Ongoing work• Development of technical requirements• Development of preliminary design document• Conceptual design of a novel actuation principle• Feasibility study on energy autonomy• First step toward a generic SLAM implementation

ReflexLeg (till September 2012)

dr. Raffaella CarloniProjectleader:prof.dr.ir. Stefano StramigioliParticipants:Ramazan Unal MScPhD students:STWSponsored by:

DescriptionIn this project a novel conceptual design for a transfemoral prosthesis has been proposedand a prototype (scale 1:2) have been realized.

The design is inspired by the power flow in human gait in order to have an energy efficientdevice. The working principle of the conceptual mechanism is based on three storageelements, which are responsible of the energetic coupling between the knee and the anklejoints. Design parameters of the prosthesis have been determined according to the energyabsorption intervals of the human gait.

This project is carried out in collaboration with the group of Prof. Velting and the RoessingR&D center.

MyoPro

dr. Sarthak MisraProjectleader:prof.dr.ir. Stefano StramigioliParticipants:Bart Peerdeman MScPhD students:PIDONSponsored by:

DescriptionMyoelectric prostheses often stay unused by their owners. Currently available hands canonly open and close and as a result patients perform most activities with their intact hand.Furthermore, the control is not intuitive and the user only perceives visual feedback. Themain goals of the project are threefold:

• Improve the control of a myoelectric arm-prosthesis by increasing the number ofdegrees of freedom using multichannel surface electromyography.

• Develop a natural and intuitive feedback mechanism.• Develop a virtual reality training program to enable aimed early-phase rehabilitation.


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Mechatronics for SME

dr.ir. Jan BroeninkProjectleader:prof.dr.ir. Job van AmerongenParticipants:

DISC projects

EU-InterregSponsored by:

DescriptionTo let SMEs in the Euregio better use mechatronics in their activities. Together withconsultancy and technology transfer firms (Syntens and STODT in our area), results of ourmechatronics work is brought to the SMEs in the region. The Coordinator is the Euregiooffice. Four German-Dutch euregios between the Dollard and the Ruhr are participating.The UT project members contribute with mechatronics expertise and researches methods.

Energy Efficient Actuations

dr. Raffaella CarloniProjectleader:Prof.dr.ir. Stefano StramigioliParticipants:

DISC projects

DescriptionThis project aims at developing actuation technologies for a new generation of robots thatcan co-exist and co-operate with people and get much closer to the human manipulationand locomotion performance than today’s robots do. At the same time these robots areexpected to be safe, in the sense that interacting with them should not constitute a higherinjury risk to humans than the interaction with another cautious human. This requires thatrobots with similar size and mass as the humans also have comparable power, strength,velocity and interaction compliance.

This project has main goal on the design of a new generation of robot actuator systems,capable of embodying the physical principles, which shape the robot behavior. The focusof the work will be on achieving different abilities, in particular:

• Energy efficiency • Robustness to external perturbations and unpredictable modelerrors (changes) of the environment, of

the robot kinematics and dynamics, or of the dynamics of a human interacting with; • Safetyto humans in operations where the robot is required positional accuracy and swiftness of

motion, while cooperating, physically interacting or even possibly colliding with the humansand their environment, such as e.g. in collaborative robotics.


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SmartPie

dr.ir. Theo de VriesProjectleader:Prof.dr.ir. Job van Amerongen dr.ir. Peter BreedveldParticipants:Bayan Babakhani MScPhD students:

DISC projects

SmartmixSponsored by:

DescriptionSmartPIE is a scientific research program on piezo technology. SmartPie is an acronym for"SMART systems based on integrated PIEzo". The aim of the SmartPIE research is tostrengthen the innovative position and perception of the Dutch high tech industry by providingit with new piezo-based technology.

Within the framework of SmartPIE, the application oriented research in our group addressesthe following subjects:

1. Active damping in precision equipment.

Specifically, we research the so-called rocking mode, which is a vibration mode that presentsitself in machines having linear actuation, due to finite rotational stiffnesses of linearguidances. Goal of the research is to overcome the limitation that this vibration mode imposeson the machine precision and closed-loop bandwidth by means of active damping units. Anactive damping unit (ADU) is a device that can be built into the machine at appropriatelocations and that incorporates a piezo force sensor, a piezo position actuator and a controllerthat realizes damping.

2. Touch-operated, battery-less Man-Machine-Interfaces.

In both professional and consumer products, switches are the main element by which theoperator of a technical apparatus can influence its operational functionality. Hence, switchingis the essential element of any Man Machine Interface (MMI). Contemporary MMIs areincreasingly often realized by means of touch buttons, touch panels or touch screens.Thesebuttons, panels or screens operate in such a way that hardly any mechanical work is neededfrom the operator in order to realize a switching action, implying that there is a minimizationof motions and of the number of moving parts, which results in many advantages.Furthermore, touch panels and screens are one of the most flexible input devices, due tothe fact that the interface is designed in software.


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MIRIAM

dr. Sarthak MisraProjectleader:Alex Jahya MScPhD students:Dutch Ministry of Ecconomic Affairs (Agentschap NL - PIDON) Sponsored by:

DescriptionProstate cancer is one of the most diagnosed types of tumor. According to the ProstateCancer Foundation, one out of every six men will develop prostate cancer at some point inhis lifetime. Nevertheless, prostate cancer is curable if the cancer is diagnosed and treatedin the early stages. The most reliable method for detecting and treating prostate cancer isbiopsy and brachytherapy, respectively. In the two above-mentioned surgical procedures,physicians insert a long thin needle into the prostate. For biopsy, it is to extract a tissuesample while for brachytherapy, it is to deliver radioactive seeds. In both procedures, Anaccurate placement of the needle tip is important for an accurate diagnosis and effectivetreatment.

In order to estimate correctly the needle tip location, physicians currently rely on theirknowledge of anatomical landmarks, and on two-dimensional (2D) ultrasound or magneticresonance images. Nevertheless, human errors, organ deformation, and physiologicalprocesses (e.g. respiration, fluid flow, etc.) may result in misplacement of the needle tip.One solution for this problem is to use a robotic device to insert the needle and place theneedle tip in a region of interest. Nevertheless, such a device requires an accurateneedle-tissue interaction model for planning and controlling needle path during insertion.

Hence, the goal of this research is to develop a patient-specific needle-tissue interactionmodel that is able to predict organ deformation and needle trajectory during the needleinsertion. This model will be implemented in the robotic surgical device that is developedunder Minimally Invasive Robotics in Magnetic Resonance Imaging (MRI) environmentproject (MIRIAM). The proposed technology will enable robot-assisted interventions,specifically in the diagnosis and the treatment of prostate cancer. Further, the robot can bedeployed in an MRI environment

Several topics will be covered in this research. A study on needle-tissue interactions duringneedle insertion (e.g. needle bending, and tissue rupture/crack) will be conducted. Moreover,tissue deformation due to the use of the needle guide during an MRI-guided biopsy procedurewill also be investigated.The results of these studies will be used to develop a biomechanicalmodel of needle-tissue interactions and tissue deformation that can predict the needlebending and tissue deformation during needle insertion. This anatomically correct model ofthe prostate and its surrounding connective tissue will be generated using MRI images.

With regards to the application of such a model in an MRI environment, the model will beused to generate optimal insertion strategies for an accurate placement of the needle tipduring the procedure. Moreover, the model will be used for both pre-planning andintra-operative procedure. Validation of the model and the optimized insertion strategy willbe done using an anatomically realistic phantom of the prostate and its surrounding connectivetissue, and later, with a non-human biological tissue.


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Model-driven design of dependable software-intensive embedded systems

dr. Angelika MaderProjectleader:dr.ir. Jan BroeninkParticipants:Oguzcan Oguz MScPhD students:CTITSponsored by:

DescriptionThe CTIT funded project is on integration of models for the design of dependable,software-intensive embedded systems, trying to bring together existing modeling methodsfrom the formal methods domain and the mechatronics / robotics domain.Work done togetherwith the CS-groups FMT and SE.

Needle steering

dr. Sarthak MisraProjectleader:Momen Abayazid MScPhD students:NWOSponsored by:

DescriptionManual percutaneous insertion of rigid needles is commonly performed during minimallyinvasive surgery (MIS). These needles often deviate from their intended paths due to organdeformation, tissue inhomogeneity, anatomical obstructions, and physiological processes.Inaccurate needle placement may result in ineffective treatment, misdiagnosis, or traumaticeffects due to medical complications.

To mitigate such targeting errors, the goal is to design a robotic system for accurately steeringflexible needles through tissue. There are several challenges inherent to this research:

• Three-dimensional (3D) models describing the evolving shape of a needle surroundedby tissue are not available.

• The real-time tracking and control of flexible needles using 3D ultrasound images hasnot been attempted.

• A system for accurately steering needles that integrates pre-operative plans withimage-guided intra-operative feedback control does not exist.

These research challenges will be overcome by developing 3D needle deflection modelsfor pre-operative planning. Intra-operative control of the flexible needle will be accomplishedunder 3D ultrasound guidance. A prototype robotic system that combines hardware andsoftware components will be built, and tested on non-human biological tissues and anatomicalmodels.

This project is conducted at the University of Twente and involve clinical and industrialcollaborations with the Radboud University Nijmegen Medical Center and Demcon BV,respectively.

The knowledge gained from this research will be applicable to a range of flexible medicalinstruments (e.g., catheters, biopsy). This research is strongly motivated by the medicalfield’s existing need to further reduce the invasiveness of MIS, improve clinical outcomes,minimize patient trauma, and enable treatment of “inoperable” patients.


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Medical Microrobotics

dr. Sarthak MisraProjectleader:

DISC projects

MIRASponsored by:

DescriptionMiniaturization of robotic systems will revolutionize medicine by enabling localization ofchemotherapies at cancer tumors within the human body, thereby decreasing the negativeside-effects such as anemia, bleeding problems, constipation, hair loss, infection, anddiarrhea. Localization of chemotherapy can be accomplished using magnetic microroboticsystems that can be controlled under the influence of the controlled magnetic fields. Thesemicrorobotic systems include but not limited to nano- and micro-particles, self-propelledmicrojets, and magnetotactic bacteria. We control these microrobotic systems using amagnetic-based manipulation system under microscopic and ultrasound guidance in two-and three-dimensional spaces.The magnetic-based control is based on the characterizationof the morphological, fluidic, and magnetic properties of each of the mentioned microroboticsystems. Our experimental work shows our ability to achieve closed-loop control along withnon-trivial tasks such as micro-manipulation, micro-assembly, micro-actuation, and sensing.

H-Haptics

dr. Sarthak MisraProjectleader:Roy Roesthuis MScPhD students:STWSponsored by:

DescriptionCurrently there is a trend towards performing surgery in a minimally invasive way. As opposedto (traditional) open surgery, Minimally Invasive Surgery (MIS) uses small diameter surgicaltools which are introduced into the body through small incisions.This has several advantagesover open surgery, among which one of the most important is less trauma for the patient,resulting in shorter recovery times. However, it is less intuitive to perform surgery using suchinstruments. This is a reason why robots were introduced in Minimally Invasive Surgery,

Some locations in the human body can be hard to reach by standard surgical tools due toanatomical obstacles. Using flexible miniaturized instruments (e.g. needles) allows one toreach these locations by navigating around these obstacles. Typical applications are liverbiopsy, or tumor ablation at the brain by navigation through the nasal cavities. The goal ofmy PhD study is to robotically steer such flexible miniaturized instruments (i.e. needles)towards a certain location in the human body.

Currently in surgeries where robotic instruments are used there is little or no feedback ofthe forces with which the tools interact with the surrounding tissue, and surgeons only relyon visual information. The surgeon is unaware of the forces he or she is exerting on thetissue, and this may result in undesired damage of the tissue. Therefore the goal is to steerthese instruments using haptic shared control. This means that the human, in this case a


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surgeon, shares control of the instrument with an automatic controller. The surgeon will beprovided by haptic sensory information through the control interface, allowing the surgeonto exert control and extract information at the same time.

Within this project we will collaborate with people from the Delft University of Technology.They will focus on the design of a miniaturized manipulator and the actuation system fordriving such a manipulator. In Twente we will focus on the modeling and control of themanipulator.

Publications

Books

Bonnema, G.M. and Veenvliet, K.T. and Broenink, J.F. (2012) System Design and Engineering,lubricating multidisciplinary development projects. Lecture Notes EngineeringTechnology Number UNSPECIFIED, University of Twente, Enschede.


Babakhani, B. and de Vries, T.J.A. and van Amerongen, J. (2012) A Comparison of thePerformance Improvement by Collocated and Noncollocated Active Damping in MotionSystems. IEEE/ASME transactions on mechatronics, 18 (3). pp. 905-913.ISSN 1083-4435 *** ISI Impact 2,865 ***

Bezemer, M.M. and Wilterdink, R.J.W. and Broenink, J.F. (2012) Design and Use of CSPMeta-Model for Embedded Control Software Development. In:Communicating ProcessArchitectures 2012, 26-29 Aug 2012, Dundee, United Kingdom. pp. 185-199. ConcurrentSystem Engineering Series 69 (WoTUG-34).Open Channel Publishing Ltd..ISBN 978-0-9565409-5-9

Carloni, R. and Visser, L.C. and Stramigioli, S. (2012) Variable Stiffness Actuators: A Port-BasedPower-Flow Analysis. IEEE transactions on robotics, 28 (1).pp. 1-11. ISSN 1552-3098 ***ISI Impact 2,536 ***

Franken, M.C.J. and Misra, S. and Stramigioli, S. (2012) Improved transparency in energy-basedbilateral telemanipulation. Mechatronics, 22 (1). pp. 45-54. ISSN 0957-4158 *** ISIImpact 1,255 ***

Holterman, J. and de Vries, T.J.A. and Babakhani, B. and Brouwer, D.M. (2012) Design of apiezoelectric rotation actuator. In: Electroceramics XIII, 24-27 June 2012, Enschede, TheNetherlands. pp. 92-92. University of Twente. ISBN not assigned

Jahya, A. and Schouten, M.G. and Futterer, J.J. and Misra, S. (2012) On the importance ofmodelling organ geometry and boundary conditions for predicting three-dimensionalprostate deformation. Computer methods in biomechanics and biomedicalengineering, online pre-publication. pp. 1-10. ISSN 1025-5842 *** ISI Impact 0,849 ***

Mahony, R. and Stramigioli, S. (2012) A port-Hamiltonian approach to image-based visual servocontrol for dynamic systems. The International Journal of RoboticsResearch, 31 (11). pp. 1303-1319. ISSN 1741-3176

Pal, J. and Duindam, V. and Stramigioli, S. (2012) Corrections to “Singularity-Free DynamicEquations of Open-Chain Mechanisms With General Holonomic and NonholonomicJoints”. IEEE transactions on robotics, 28 (6). pp. 1431-1432. ISSN 1552-3098 *** ISIImpact 2,536 ***


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Schouten, M.G. and Bomers, J.G.R and Yakar, D. and Huisman, H. and Rothgang,E. and Bosboom, D. and Scheenen, T.W.J. and Misra, S. and Futterer,J.J.(2012) Evaluation of a robotic technique for transrectal MRI-guided prostatebiopsies. European Radiology, 22 (2). pp. 476-483. ISSN 0938-7994 *** ISIImpact3,222 ***

Sun, Hao and de Vries, T.J.A. and de Vries, R. and van Dalen, H. (2012) Energetic optimizationof a piezo-based touch-operated button for man–machine interfaces. Smart materialsand structures, 21 (3). 035026. ISSN 0964-1726 *** ISI Impact 2,089 ***


Abayazid, M. and op den Buijs, J. and De Korte, C. L. and Misra, S. (2012) Effect of skinthickness on target motion during needle insertion into soft-tissuephantoms. In: Proceedings of the fourth IEEE RAS & EMBS International Conferenceon Biomedical Robotics and Biomechatronics (BioRob), 2012, 24-27 June 2012, Rome,Italy. pp. 755-760. Proceedings of the IEEE RAS & EMBS International Conference onBiomedical Robotics and Biomechatronics (BioRob). IEEE Engineering in Medicine &Biology Society. ISSN 2155-1774 ISBN 978-1-4577-1199-2

Babakhani, B. and de Vries, T.J.A. and van Amerongen, J. (2012) Design Guidelines concerningthe Destabilizing High-frequency Mode of an Integral Force Feedback-based ActiveDamping Unit. In: Proceedings of 2012 IEEE/ASME International Conference on AdvancedIntelligent Mechatronics (AIM), 11-14 July 2012, Kaohsiung, Taiwan. pp. 520-525. IEEE .ISSN 2159-6247 ISBN 978-1-4673-2575-2

Babakhani, B. and de Vries, T.J.A. and van Amerongen, J. (2012) Off-axis Modal Active VibrationControl Of Rotational Vibrations. In: Proceedings of 2012 IEEE/ASME InternationalConference on Advanced Intelligent Mechatronics (AIM), 11-14 July2012, Taiwan. pp. 326-331. IEEE Robotics and Automation Society.ISSN 2159-6247 ISBN 978-1-4673-2575-2

Broenink, J.F. and Ni, Yunyun (2012) Model-Driven Robot-Software Design using integratedModels and Co-Simulation. (Invited) In: International Conference on Embedded ComputerSystems, SAMOS 2012, 16-19 July 2012, Samos, Greece. pp. 339-344. IEEE ComputerSociety. ISBN 978-1-4673-2296-6

Carloni, R. and Marconi, L. (2012) Limit cycles and stiffness control with variable stiffnessactuators. In: Proceedings of the IEEE International Conference on Intelligent Robotsand Systems, 7-12 Oct 2012, Vilamoura, Portugal. pp. 5083-5088. IEEE Robotics andAutomation Society. ISSN 2153-0858 ISBN 978-1-4673-1737-5

Dertien, E.C. and Dijkstra, J. and Mader, A.H. and Reidsma, D. (2012) Making a Toy EducativeUsing Electronics. In: 9th International Conference on Advances in ComputerEntertainment, ACE 2012, 03-05 Nov 2012, Kathmandu, Nepal. pp. 477-480. LectureNotes in Computer Science 7624. Springer Verlag. ISBN 978-3-642-34291-2

Du, Jingjing and Indri, M. and Dresscher, D. and Stramigioli, S. (2012) Autonomous ExplorationUsing Kinect and Laser Range Finder. In: Advances in Autonomous Robotics (JointProceedings of the 13th Annual TAROS Conference and the 15th Annual FIRARobotWorld Congress), 20-25 Aug 2012, Bristol.pp. 420-421. Lecture Notes in ArtificialIntelligence 7429. Springer Verlag. ISSN 0302-9743 ISBN 978-3-642-32526-7

Folkertsma, G.A. and Stramigioli, S. and Kim, Sangbae (2012) Parallel stiffness in a boundingquadruped robot with flexible spine. In: Proceedings of the 2012 IEEE/RSJ InternationalConference on Intelligent Robots and Systems (IROS), 7-12 Oct 2012, Vilamoura,Portugal. pp. 2210-2215. IEEE Robotics and Automation Society.ISSN 2153-0858 ISBN 978-1-4673-1737-5


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Franken, M.C.J. and Misra, S. and Stramigioli, S. (2012) Stability of position-based bilateraltelemanipulation systems by damping injection. In: Robotics and Automation (ICRA),2012 IEEE International Conference on, 14-18 May 2012, St Paul, MN,USA. pp. 4300-4306. IEEE Robotics and Automation Society.ISSN1050-4729 ISBN 978-1-4673-1404-6

Fumagalli, M. and barrett, E. and Stramigioli, S. and Carloni, R. (2012) The mVSA-UT: aminiaturized differential mechanism for a continuous rotational variable stiffnessactuator. In: Proceedings of the IEEE RAS/EMBS International Conference on BiomedicalRobotics and Biomechatronics, 24-27 June 2012, Rome, Italy. pp. 1943-1948. IEEERobotics and Automation Society. ISBN 978-1-4577-1200-5

Fumagalli, M. and Naldi, R. and Macchelli, A. and Carloni, R. and Stramigioli, S. and Marconi,L. (2012) Modeling and control of a flying robot for contact inspection. In: Proceedingsof the IEEE/RSJ International Conference Intelligent Robots and Systems, 7-12 Oct2012, Vilamoura, Portugal. pp. 3532-3537. IEEE Robotics and Automation Society.ISSN 2153-0858 ISBN 978-1-4673-1737-5

Groothuis, S.S. and Rusticelli, G. and Zucchelli, A. and Stramigioli, S. and Carloni, R. (2012) ThevsaUT-II: A novel rotational variable stiffness actuator. In:Proceedings of the InternationalConference on Robotics and Automation, 14-18 May 2012, St. Paul,USA. pp. 3355-3360. IEEE Robotics and Automation Society. ISSN 1050-4729

Jahya, A. and van der Heijden, F. and Misra, S. (2012) Observations of three-dimensionalneedle deflection during insertion into soft tissue. In: Proceedings of the Fourth IEEERAS/EMBS International Conference on Biomedical Robotics and Biomechatronics, 24-27June 2012, Roma, Italy. pp. 1205-1210. IEEE Robotics and Automation Society.ISSN 2155-1774 ISBN 978-1-4577-1199-2

Keemink, A. Q. L. and Fumagalli, M. and Stramigioli, S. and Carloni, R. (2012) MechanicalDesign of a Manipulation System for Unmanned Aerial Vehicles. In:Proceedings of theInternational Conference on Robotics and Automation, 14-18 May 2012, St. Paul,USA. pp. 3147-3152. IEEE Robotics and Automation Society. ISSN 1050-4729

Khalil, I.S.M. and Keuning, J.D. and Abelmann, L. and Misra, S. (2012) Wireless magnetic-basedcontrol of paramagnetic microparticles. In: Proceedings of The Fourth IEEE RAS/EMBSInternational Conference on Biomedical Robotics and Biomechatronics, 24-27 June2012, Rome, Italy . pp. 460-466. Proceedings of the IEEE RAS & EMBS InternationalConference on Biomedical Robotics and Biomechatronics (BioRob). IEEE Robotics andAutomation Society. ISSN 2155-1774ISBN 978-1-4577-1198-5

Khalil, I.S.M. and Metz, R.M.P. and Abelmann, L. and Misra, S. (2012) Interaction ForceEstimation During Manipulation of Microparticles. In: Proceedings of the IEEE/RSJInternational Conference on Intelligent Robots and Systems, 7-10 Oct 2012, Vilamoura,Algarve, Portugal. pp. 950-956. IEEE Xplore. IEEE Robotics and Automation Society.ISSN 2153-0858 ISBN 978-1-4673-1737-5

Khalil, I.S.M. and Sabanovic, A. and Misra, S. (2012) An Energy-Based State Observer forDynamical Subsystems with Inaccessible State Variables. In:Proceedings of the IEEE/RSJInternational Conference on Intelligent Robots and Systems, 7-10 Oct 2012, Vilamoura,Algarve, Portugal. pp. 3734-3740. IEEE Xplore. IEEE Robotics and Automation Society.ISSN 2153-0858 ISBN 978-1-4673-1737-5

Mader, A.H. and Dertien, E.C. and Reidsma, D. (2012) Single Value Devices. In: Proceedingsof the 4th International ICST Conference on Intelligent Technologies for InteractiveEntertainment (INTETAIN 2011), Revised Selected Papers, 25-27 May 2011, Genova.Italy. pp. 38-47. Lecture Notes of the Institute for Computer Sciences, Social Informaticsand Telecommunications Engineering 78. Springer Verlag.ISSN 1867-8211 ISBN 978-3-642-30213-8


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Marincic, J. and Mader, A.H. and Wieringa, R.J. (2012) Explaining Embedded Software ModellingDecisions. In: IEEE CS International Conference on Software Science, Technology, andEngineering, SWSTE 2012, 12-13 June 2012, Herzlia, Israel. pp. 80-89. IEEE ComputerSociety. ISBN 978-0-7695-4716-9

Mersha, A.Y. and Ruesch, A. and Stramigioli, S. and Carloni, R. (2012) A contribution to hapticteleoperation of aerial vehicles. In: Proceedings of the IEEE/RSJ International Conferenceon Intelligent Robots and Systems , 7-12 Oct 2012, Vilamoura, Algarve,Portugal. pp. 3041-3042. IEEE Robotics and Automation Society.ISSN 2153-0858 ISBN 978-1-4673-1737-5

Mersha, A.Y. and Stramigioli, S. and Carloni, R. (2012) Bilateral teleoperation of underactuatedunmanned aerial vehicles: The virtual slave concept. In:Proceedings of the InternationalConference on Robotics and Automation, 14-18 May 2012, St. Paul,USA. pp. 4614-4620. IEEE Robotics and Automation Society. ISSN 1050-4729

Mersha, A.Y. and Stramigioli, S. and Carloni, R. (2012) Switching-based Mapping and Controlfor Haptic Teleoperation of Aerial Robots. In: Proceedings of the IEEE/RSJ InternationalConference on Intelligent Robots and Systems, 7-12 Oct 2012, Vilamoura, Algarve,Portugal. pp. 2629-2634. IEEE Robotics and Automation Society.ISSN 2153-0858 ISBN 978-1-4673-1737-5

Ni, Yunyun and Broenink, J.F. (2012) Hybrid systems modelling and simulation in DESTECS:a co-simulation approach. In: 26th European Simulation and Modelling Conference, ESM2012, 22-24 Oct 2012, Essen, Germany. pp. 32-36. EUROSIS-ETI.ISBN 978-90-77381-73-1

Oguz, O. and Broenink, J.F. and Mader, A.H. (2012) Schedulability analysis of timed CSPmodels using the PAT model checker. In: Communicating Process Architectures2012, 26-29 Aug 2012, Dundee, Scotland. pp. 65-88. Open Channel Publishing Ltd.ISBN 978-0-9565409-5-9

Peerdeman, B. and Fabrizi, U. and Palli, G. and Melchiorri, C. and Stramigioli, S. and Misra,S. (2012) Development of prosthesis grasp control systems on a robotictestbed. In: Proceedings of the 4th IEEE RAS & EMBS International Conference onBiomedical Robotics and Biomechatronics (BioRob), 24-27 June 2012, Rome,Italy. pp. 1110-1115. IEEE Robotics and Automation Society.ISSN 2155-1774 ISBN 978-1-4577-1199-2

Peerdeman, B. and Pieterse, G.J. and Stramigioli, S. and Rietman, J.S. and Hekman,E.E.G. and Brouwer, D.M. and Misra, S. (2012) Design of Joint Locks for UnderactuatedFingers. In: Proceedings of the 4th IEEE RAS & EMBS International Conference onBiomedical Robotics and Biomechatronics (BioRob), 24-27 Jun 2012, Rome,Italy. pp. 488-493. IEEE Robotics and Automation Society.ISSN 2155-1774 ISBN 978-1-4577-1199-2

Peerdeman, B. and Smit, G. and Stramigioli, S. and Plettenburg, D.H. and Misra,S. (2012) Evaluation of pneumatic cylinder actuators for hand prostheses. In:Proceedingsof the 4th IEEE RAS & EMBS International Conference on Biomedical Robotics andBiomechatronics (BioRob), 24-27 June 2012, Rome, Italy.pp. 1104-1109. IEEE Roboticsand Automation Society. ISSN 2155-1774 ISBN 978-1-4577-1199-2

Reilink, R. and Stramigioli, S. and Misra, S. (2012) Pose Reconstruction of Flexible Instrumentsfrom Endoscopic Images using Markers. In: Proceedings of International Conference onRobotics and Automation (ICRA), 14-18 May, 2012, St. Paul, USA. 2938-2943 . IEEERobotics and Automation Society. ISBN 978-1-4673-1404-6


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Roesthuis, R.J. and Abayazid, M. and Misra, S. (2012) Mechanics-Based Model for PredictingIn-Plane Needle Deflection with Multiple Bends. In: Proceedings of the Fourth IEEERAS/EMBS International Conference on Biomedical Robotics and Biomechatronics, 24-27Jun 2012, Rome, Italy. pp. 69-74. 4th IEEE RAS & EMBS International Conference onBiomedical Robotics and Biomechatronics (BioRob), 2012. IEEE Robotics and AutomationSociety. ISSN 2155-1774 ISBN978-1-4577-1199-2

Ruesch, A. and Mersha, A.Y. and Stramigioli, S. and Carloni, R. (2012) Kinetic scrolling-basedposition mapping for haptic teleoperation of unmanned aerial vehicles. In: PRoceedingsof the International Conference on Robotics and Automation, 14-18 May 2012, St. Paul,USA. pp. 3116-3121. IEEE Robotics and Automation Society. ISSN 1050-4729

Ünal, R. and Carloni, R. and Behrens, S.M. and Hekman, E.E.G. and Stramigioli,S. and Koopman, H.F.J.M. (2012) Towards a fully passive transfemoral prosthesis fornormal walking. In: Proceedings of the IEEE RAS/EMBS International Conference onBiomedical Robotics and Biomechatronics, 24-27 June 2012,Rome,Italy. pp. 1949-1954. IEEE Robotics and Automation Society. ISBN 978-1-4577-1200-5

van der Stap, N. and Reilink, R. and Misra, S. and Broeders, I.A.M.J. and van der Heijden,F. (2012) A feasibility study of optical flow-based navigation during colonoscopy. In: 26thInternational Congress and Exhibition on Computer Assisted Radiology and Surgery,CARS 2012, 27-30 Jun 2012, Pisa, Italy. S235.International Journal of Computer-AssistedRadiology and Surgery 7 (Suppl 1). Springer Verlag. ISSN 1861-6410

van der Stap, N. and Reilink, R. and Misra, S. and Broeders, I.A.M.J. and van der Heijden,F. (2012) The Use of the Focus of Expansion for Automated Steering of FlexibleEndoscopes. In: 4th IEEE RAS & EMBS International Conference on Biomedical Roboticsand Biomechatronics (BioRob), 24-27 June, 2012, Rome, Italy. pp. 13-18. IEEEConference Publications. IEEE Robotics and Automation Society.ISSN 2155-1774 ISBN 978-1-4577-1199-2

van Veen, Y.R.J. and Jahya, A. and Misra, S. (2012) Macroscopic and microscopic observationsof needle insertion into gels. Proceedings of the Institution of Mechanical Engineers. partH, Journal of engineering in medicine, 226 (6). pp. 441-449. ISSN 0954-4119 *** ISIImpact 1,208 ***

Vanderborght, B. and Albu-Schaeffer, A. and Bicchi, A. and Burdet, E. and Caldwell,D.G. and Carloni, R. and Catalano, M.G. and Ganesh, G. and Garabini, M.and Grioli,G. and Haddadin, S. and Jafari, A. and Laffranchi, M. and Lefeber, D. and Petit,F. and Stramigioli, S. and Tsagarakis, N. and van Damme, M. andvan Ham, R. and Visser,L.C. and Wolf, S. (2012) Variable impedance actuators: moving the robots oftomorrow. In: Proceedings of the IEEE/RSJ International Conference Intelligent Robotsand Systems, 7-12 Oct 2012, Vilamoura, Portugal. pp. 5454-5455. IEEE Robotics andAutomation Society. ISSN 2153-0858 ISBN978-1-4673-1737-5

Visser, L.C. and Stramigioli, S. and Carloni, R. (2012) Robust Bipedal Walking with VariableLeg Stiffness. In: 4th IEEE RAS/EMBS International Conference on Biomedical Roboticsand Biomechatronics, BioRob 2012, 24-27 June 2012, Rome, Italy. pp. 1626-1631. IEEERobotics and Automation Society. ISSN 2155-1774 ISBN 978-1-4577-1198-5

Zhang, Xiaochen and Broenink, J.F. (2012) A structuring mechanism for embedded controlsystems using co-modelling and co-simulation. In: Proceedings of the 2nd InternationalConference on Simulation and Modeling Methodologies, Technologies and Applications,SIMULTECH 2012, 28-31 Jul 2012, Rome, Italy.pp. 131-136. SciTePress.ISBN 978-989-8565-20-4


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Ph.D. theses

Babakhani, B. (2012) Active Damping of Vibrations in High-Precision Motion Systems. PhDthesis, Univ. of Twente. ISBN 978-90-365-3464-2

Other publications

Koopman, H.F.J.M. and Behrens, S.M. and Carloni, R. and Hekman, E.E.G. and Stramigioli,S. and Ünal, R. and Veltink, P.H. (2012) A prosthetic or orthoticdevice. Patent WO2012NL50421 (Application).

Pierce, K. and Gamble, G. and Ni, Yunyun and Broenink, J.F. (2012) Collaborative Modellingand Co-Simulation with DESTECS: A Pilot Study. In: 21st International Workshop EnablingTechnologies: Infrastructure for Collaborative Enterprises, WETICE 2012, 25-27 June2012, Toulouse, France. pp. 280-285.IEEE Computer Society.ISSN 1524-4547 ISBN 978-1-4673-1888-4


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University of Twente – Faculty of Electrical Engineering,Mathematics and Computer ScienceDepartment of Applied MathematicsHS Group

General Information

AddressUniversity of Twente, Department of Applied Mathematics, HS Group, P.O. Box 217, 7500AE Enschede, The Netherlands. Phone (secretary): +31–53–4893370. Fax (secretary):+31–53–4893800. E-mail (secretary): [email protected]

Scientific staffprof.dr. A. Bagchi, dr. P.K. Mandal, dr. G. Meinsma, dr. J.W. Polderman, prof.dr. A.A.Stoorvogel, dr. M. Vajta, prof.dr. H.J. Zwart

Technical and administrative staffmrs. M. Langkamp (secretary group HS).

PhD studentsE. Aoki MSc., M. Bocquel MSc, O.E. Göttsche MSc, F. Katsilieris MSc, W.A. Pradana MSc,R. Prihatin MSc, F.L. Schwenninger Msc, Dr. H.S. Shekhawat (until 01-12-2012).

Keywordssystems theory, robust control, nonlinear control, hybrid systems, infinite dimensional systems,behavioral systems theory, filtering, stochastic systems, modelling, signal processing,decentralized control.

Brief descriptionThe research in the group is primarily devoted to the fundamental and mathematical aspectsof systems, signals and control.

The scientific discipline of systems and control deals with the study of the dynamical behaviorof systems in interaction with their environment (open dynamical systems), as they arise inengineering and natural sciences, computer science, finance and economics. It is aninherently interdisciplinary research area with roots in electrical and mechanical engineering,as well as in applied mathematics.

Distinguishing feature of systems and control theory is that apart from describing opendynamical systems, it is also concerned with prescribing dynamical behavior, by the(feedback) coupling of the system with additional system components (analog or digital).Thus systems and control theory deals with the mathematical modeling and analysis ofcomplex dynamical systems composed of interacting subsystems, as well as with theircontrol and synthesis.

Various mathematical formalisms are employed, suited to the particular class of systems athand. Geometric, coordinate free formulations are emphasised. Stochastic modeling andparameter identification, often based on data, plays an indispensable role in many applicationareas of engineering and finance. The design of control strategies is related to optimisationand decision theory.

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The mission of the group is to perform fundamental mathematical research stimulatedby multidisciplinary collaboration with colleagues from engineering, computer science, andmanagement studies.This is pursued within a context of local and international collaborationin writing articles, setting up European networks, organising conferences, and initiatingmultidisciplinary research projects and seminars. Also, there is a longstanding collaborationwith Thales and the national research institute NLR.

The research of the group covers a large spectrum of mathematical systems and controltheory, leading to a wide mathematical scope with strong conceptual cohesion and a broadplatform for initiating multidisciplinary collaboration.

Special focus in research is on nonlinear control, robust control, geometric modeling ofphysical systems, adaptive and behavioral systems, hybrid systems, infinite-dimensionalsystems, modeling and identification of stochastic systems, stochastic filtering and control,and financial engineering. Emphasis is on intrinsic mathematical formulations, making closecontact with various branches of mathematics.

From an applications point of view the research on nonlinear and robust control, modelingof physical systems, adaptive and behavioral systems, hybrid systems, infinite-dimensionalsystems theory is motivated by collaboration with engineering departments. At the local levelthis collaboration takes place within the local institute CTIT, while on the European level thereis involvement within corresponding EU networks. Applications are mainly found in the largearea of mechatronics, both in the analysis of design, as in simulation and control ofengineering systems. The research on hybrid systems is moving towards collaborationwith computer science in the area of embedded systems.The research on stochastic modelingand identification and stochastic filtering and control finds its applications within variouscollaborations, and nationally e.g. with Thales.

DISC projects

Sampled-data systems and robust control

G. MeinsmaProjectleader:

DescriptionThe research on Sampled-data systems is directed towards applications

of ideas from systems theory to problems in signal processing. Joint work with Mirkin fromTechnion IIT in Haifa has led to a number of re-interpretations of known results in signalprocessing and to several new design methodologies for optimal samplers and holdingdevices.We have shown that the signal processing community benefits from such a systemsapproach. For example it is now possible to design optimal holds (for fixed sampler) andoptimal samplers (for fixed hold) with user-assigned degree of causality, while hitherto onlynoncausal or 0-causal samplers and holds could be delt with. Along the way quite a fewnew mathematical notions have been introduced. One is the frequency power response fortime-varying systems which we believe is the natural generalization of the frequency response/ spectral density for time-invariant systems. We also believe that our state spacerepresentation over intersample time of transfer function operators holds promise for thedesign and also helps to get a handle on the infinite dimensionality of the problem. It worksvery much like classic state space representations in that design can be transformed intoconstant matrix manipulations (which makes our methods numerically tractable). The new

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state space representations however works not only for classic time-invariant systems butalso for the type of time-varying systems that one encounters in sampled-data systems,including samplers and holds. Methods and ideas of robust control are incorporated in ourwork.

Hybrid systems

J.W. PoldermanProjectleader:

DescriptionHybrid systems are any kind of systems (or processes) with interacting continuous anddiscrete dynamics. It is an emerging area of research, with contributions from computerscience, physical systems modeling and simulation, and systems and control theory.

Collaboration was continued with computer science. Joint research with the chair of formalmethods and tools (Computer Science) concerns robustness of timed automata and stabilityand control of switched linear systems.

Control of linear systems subject to constraints

A.A. StoorvogelProjectleader:

DescriptionTime-domain constraints often yield a serious limitation on achievable performance in thecontrol of industrial processes. On the other hand the requirement for high performancemeans that we cannot simply guarantee that we stay far away from the constraint boundary.

In this project the special structure of a linear system is used where constraints are theonly nonlinearity occurring in the system.

In this setting a more or less complete controller design methodology needs to be developed.We have studied the problems of stabilization and tracking/regulation of linear systemssubject to input saturation and/or subject to rate limits. Extensions to linear systems subjectto state and input constraints are actively being developed.

Regarding our future objectives, first of all we want to get a better understanding of theeffects of rate-limits and state constraints in stability and regulation problems. Secondly, theproblem of reducing the effect of disturbances will be studied. Currently this is only understoodin the case of "matched" disturbances. In particular, we will investigate the effect of stochasticdisturbances. We will also look into the question how disturbance rejection can be achievedin a Model Predictive Control framework.

Decentralized control

A.A. StoorvogelProjectleader:

DescriptionMany systems that need to be controlled currently have structural constraints on the controller.A prime example is a controller, which consist of different components with limited orunreliable communications between channels.The research focuses initially on stabilizationissues and linear systems. The ideal is to have a design methodology, which enables us todesign a stabilizing controller, which is maximally robust against failure of one or moreconnections between the different components of the controller.


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Infinite-dimensional systems

H.J. ZwartProjectleader:

DescriptionIn 2012 the main themes within this research topic were: infinite-dimensional port-Hamiltoniansystems, stability analysis of discrete- and continuous evolution equations, and systemsproperties of infinite-dimensional systems. The theory of (linear) port-Hamiltonian systemson a one-dimensional spatial domain is by now well understood.This enabled us to documentit in a text book (together with B. Jacob, University of Wuppertal, Germany), which appearedthe summer of 2012. Together with the post-doc M. Kurula the analytic results for thesesystems are extended to systems described on a higher dimensional spatial domain.Furthermore, it is investigated how from simple port-Hamiltonian systems more complicatedsystems can be build by adding a closure relation to the systems equations.

Exponential stability for infinite-dimensional systems on a Hilbert space is well understood.An unsolved question is to give bounds on its overshoot. In the Ph.D. project “Bounds onStable Semigroups” (funded by NWO) it is shown that it is possible to identify classes ofdiscrete- and continuous-time systems with similar overshoot behavior.The thesis containingthis and more results is defended in January 2012. A new Ph.D. student started on a relatedtopic at the end of 2011. In this project we look more closely at long time behavior of numericalschemes, such as the Crank-Nicolson scheme.

Together with the Ph.D. student R van Gils (Tu/e) the stabilizability of a pool boiling processis investigated. This system is modeled by a non-linear partial differential equation. For thismodel it is shown that a P-controller will exponentially stabilize the system. In November2012 R. van Gils successfully defended his thesis.

Stochastic systems

P.K. MandalProjectleader:

DescriptionThe main focus of our research is on particle filtering with application to sensor networks.We have worked on MAP estimation algorithms and effective methods for parameterestimation.We are currently working on joint estimation of parameter and states in large-scalecomplex systems.The standard (particle filtering) techniques face the “curse of dimensionality”when applied to very high-dimensional problems.We are working on new methods/algorithmsto handle high-dimensional models.

Another area involves the ongoing research on detection and labeling of multiple objects insensor networks. When the number of targets is unknown one needs to model the systemdifferently, for example, by using the so-called Random Finance Set models.

Publications

Books

Jacob, B. And Zwart, H.J. (2012) Linear Port-Hamiltonian Systems on Infinite-dimensionalSpaces. Operator Theory: Advances and Applications 223. Springer Verlag, Basel. ISBN978-3-0348-0398-4


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Saberi, A. And Stoorvogel, A.A. and Sannuti, P. (2012) Interna land external stabilisation oflinear systems with constraints. Systems & Control: Foundations & Applications.Birkhäuser, New York. ISBN 978-0-8176-4786-5


Aihara, S.I. and Bagchi, A. (2012) Adaptive filtering for stochastic risk premia in bond market.International journal of innovative computing, information and control, 8 (3(B)).pp. 2203-2214. ISSN 1349-4198

Grip, H.F and Yang, Tao and Saberi, A. and Stoorvogel, A.A. (2012) Output synchronizationfor heterogeneous networks of non-introspective agents. Automatica, 48 (10).pp. 2444-2453. ISSN 0005-1098 *** ISI Impact 2,829 ***

Meinsma, G. and Mirkin, L. (2012) L2 sampled signal reconstruction with causality constraints- Part I: Setup and solutions. IEEE transactions on signal processing, 60 (5).pp. 2260-2272. ISSN 1053-587X *** ISI Impact 2,628 ***

Meinsma, G. and Mirkin, L. (2012) L2 sampled signal reconstruction with causality constraints- Part II: Theory. IEEE transactions on signal processing, 60 (5). pp. 2273-2285. ISSN1053-587X *** ISI Impact 2,628 ***

Polderman, J.W. (2012) Time-domain description of behaviors over finite fields. Linear algebraand its applications, 436 (5). pp. 1258-1266. ISSN 0024-3795 *** ISI Impact 0,974 ***

Polderman, J.W. and Langerak, R. (2012) Stability and robustness of planar switching linearsystems. Systems and control letters, 61 (9). pp. 904-910. ISSN 0167-6911 *** ISI Impact1,222 ***

Schwenninger, F.L. and Zwart, H.J. (2012) Weakly admissible -calculus on reflexive Banachspaces. Indagationes mathematicae, 23 (4). pp. 796-815. ISSN 0019-3577 *** ISI Impact0,195 ***

van Gils, R.W. and Speetjens, M.F.M. and Zwart, H.J. and Nijmeijer, H. (2012) Feedbackstabilisation of a two-dimensional pool-boiling system by modal control. InternationalJournal of Thermal Sciences, 61. pp. 38-49. ISSN 1290-0729 *** ISI Impact 2,142 ***

van Mourik, S. and Vries, D. and Ploegaert, J.P.M. and Zwart, H.J. and Keesman, K.J. (2012)Physical parameter estimation in spatial heat transport models with an application to foodstorage. Biosystems Engineering, 112 (1). pp. 14-21. ISSN 1537-5110 *** ISI Impact1,354 ***

Wang, Xu and Saberi, A. and Grip, H.F. and Stoorvogel, A.A. (2012) Simultaneous externaland internal stabilization of linear systems with input saturation and non-input-additivesustained disturbances. Automatica, 48 (10). pp. 2633-2639. ISSN 0005-1098 *** ISIImpact 2,829 ***

Wang, Xu and Saberi, A. and Stoorvogel, A.A. and Grip, H.F. (2012) Control of a chain ofintegrators subject to input saturation and disturbances. International journal of robustand nonlinear control, 22 (14). pp. 1562-1570. ISSN 1049-8923 *** ISI Impact 1,554 ***

Wang, Xu and Saberi, A. and Stoorvogel, A.A. and Grip, H.F. (2012) Further results on thedisturbance response of a double integrator controlled by a saturating linear static statefeedback. Automatica, 48 (2). pp. 430-435. ISSN 0005-1098 *** ISI Impact 2,829 ***

Wang, Xu and Saberi, A. and Stoorvogel, A.A. and Sannuti, P. (2012) Simultaneous globalexternal and internal stabilization of linear time-invariant discrete-time systems subjectto actuator saturation. Automatica, 48 (5). pp. 699-711. ISSN 0005-1098 *** ISI Impact2,829 ***

Wang, Xu and Stoorvogel, A.A. and Saberi, A. and Sannuti, P. (2012) Discrete-time and low-gaintheory. International journal of robust and nonlinear control, 22 (7). pp. 743-762. ISSN1049-8923 *** ISI Impact 1,554 ***


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Wyss, C. and Jacob, B. and Zwart, H.J. (2012) Hamiltonians and Riccati equations for linearsystems with unbounded control and observation operators. SIAM Journal on Controland Optimization, 50 (3). pp. 1518-1547. ISSN 0363-0129 *** ISI Impact 1,518 ***

Zwart, H.J. (2012) Toeplitz operators and calculus. Journal of Functional Analysis, 263 (1).pp. 167-182. ISSN 0022-1236 *** ISI Impact 1,082 ***


Aihara, S.I. and Bagchi, A. and Saha, S. (2012) Identification of Bates stochastic volatility modelby using non-central chi-square random generation method. In: Proceedings of the 2012IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP),25-30 Mar 2012, Kyoto, Japan. pp. 3905-3908. IEEE Computer Society. ISSN 1520-6149ISBN 978-1-4673-0045-2

Aoki, E.H. and Boers, Y. and Mandal, P.K. and Bagchi, A. (2012) SMC methods to avoidself-resolving for online Bayesian parameter estimation. In: Proceedings of the 15thInternational Conference on Information Fusion (FUSION 2012), 9-12 July 2012,Singapore. pp. 98-105. IEEE. ISBN 978-1-4673-0417-7

Aoki, E.H. and Boers, Y. and Svensson, L. and Mandal, P.K. and Bagchi, A. (2012) A Bayesianlook at the optimal track labelling problem. In: Proceedings of the 9th IET Data Fusion &Target Tracking Conference (DF&TT'12), 16-17 May 2012, London, UK. pp. 60-65.Institution of Engineering and Technology. ISBN 978-1-62276-195-1

Aoki, E.H. and Boers, Y. and Svensson, L. and Mandal, P.K. and Bagchi, A. (2012) TheRao-Blackwellized marginal M-SMC filter for Bayesian multi-target tracking and labelling.In: Proceedings of the 15th International Conference on Information Fusion (FUSION2012), 9-12 Jul 2012, Singapore. pp. 90-97. IEEE. ISBN 978-1-4673-0417-7

Bocquel, M. and Driessen, H. and Bagchi, A. (2012) Multitarget particle filter addressingambiguous radar data in TBD. In: Proceedings of the 2012 IEEE National RadarConference, 7-11 May 2012, Atlanta, GA. pp. 0575-0580. IEEE. ISSN 1097-5659 ISBN978-1-4673-0656-0

Bocquel, M. and Driessen, H. and Bagchi, A. (2012) Multitarget tracking with interactingpopulation-based MCMC-PF. In: Proceedings of the 15th International Conference onInformation Fusion (FUSION 2012), 9-12 July 2012, Singapore. pp. 74-81. IEEE. ISBN978-1-4673-0417-7

Grip, H.F. and Yang, Tao and Saberi, A. and Stoorvogel, A.A. (2012) Decentralized control foroutput synchronization in heterogeneous networks of non-introspective agents. In:American Control Conference, ACC 2012, 27-29 Jun 2012, Montréal. pp. 812-819. IEEEControl Systems Society. ISBN 978-1-4577-1094-0

Meinsma, G. and Mirkin, L. (2012) Sampled-data L-infinity smoothing: fixed-size ARE solutionwith free hold function. In: Proceedings of the 20th International Symposium onMathematical Theory of Networks and Systems, MTNS 2012, 9-13 July 2012, Melbourne,Australia. 180. Think Business Events. ISBN 978-0-646-58062-3

Meinsma, G. and Mirkin, L. (2012) Yet another discrete-time H-infinity smoothing solution. In:Proceedings of the 20th International Symposium on Mathematical Theory of Networksand Systems, MTNS 2012, 9-13 July, 2012, Melbourne, Australia. 179. Think BusinessEvents. ISBN 978-0-646-58062-3

Polenkova, S.V. and Polderman, J.W. and Langerak, R. (2012) Stability of reset systems. In:Proceedings of the 20th International Symposium on Mathematical Theory of Networksand Systems, 9-13 Jul 2012, Melbourne, Australia. 0074. Think Business Events. ISBN978-0-646-58062-3


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Shekhawat, H.S. and Meinsma, G. (2012) L2 and L optimal downsampling from system theoreticviewpoint. In: Proceedings of the 20th International Symposium on Mathematical Theoryof Networks and Systems, 9-13 July, 2012, Melbourne, Australia. 215. Think BusinessEvents. ISBN 978-0-646-58062-3

Shekhawat, H.S. and Meinsma, G. (2012) Optimal relaxed causal sampler using sampled-datesystem theory. In: Proceedings of the 20th International Symposium on MathematicalTheory of Networks and Systems, MTNS 2012, 9-13 July, Melbourne, Australia. 220.Think Business Events. ISBN 978-0-646-58062-3

Wang, X. and Saberi, A. and Stoorvogel, A.A. and Grip, H.F. and Yang, T. (2012) Consensusin the network with uniform constant communication delay. In: Proceedings of the 51stIEEE Conference on Decision and Control (CDC 2012), 10-13 Dec 2012, Maui, Hawaii.pp. 5318-5323. IEEE Control Systems Society. ISBN 978-1-4673-2064-1

Wang, Xu and Saberi, A. and Grip, H.F. and Stoorvogel, A.A. (2012) Control of linear systemswith input saturation and non-input-additive sustained disturbances - continuous-timesystems. In: American Control Conference, ACC 2012, 27-29 Jun 2012, Montréal.pp. 2313-2318. IEEE Control Systems Society. ISBN 978-1-4577-1094-0

Wang, Xu and Saberi, A. and Grip, H.F. and Stoorvogel, A.A. (2012) Control of linear systemswith input saturation and non-input-additive sustained disturbances - discrete-time systems.In: American Control Conference, ACC 2012, 27-29 Jun 2012, Montréal. pp. 2319-2324.IEEE Control Systems Society. ISBN 978-1-4577-1094-0

Yang, T. and Stoorvogel, A.A. and Grip, H.F. and Saberi, A.A. (2012) Semi-global regulationof output synchronization for heterogeneous networks of non-introspective, invertibleagents subject to actuator saturation. In: Proceedings of the 51st IEEE Conference onDecision and Control (CDC 2012), 10-13 Dec 2012, Maui, Hawaii. pp. 5298-5303. IEEEControl Systems Society. ISBN 978-1-4673-2064-1

Ph.D. theses

Besseling, N.C. (2012) Strability analysis in continuous and discrete time. (2012, January 20)107 pp. Univ. of Twente. Thesis advisor(s): prof. dr. H.J. Zwart & prof. dr. A.A. Stoorvogel.ISBN 978-90-365-3307-2

Shekhawat, H.S. (2012) Optimal Sampling and Interpolation (2012, November 29) 217 pp.Univ. of Twente. Thesis advisor(s): prof. dr. A.A. Stoorvogel & dr. G. Meinsma, Ass.promotor. ISBN 978-90-365-3473-4

M.Sc. theses

Boersma, Jochem. Controller Design of LTI systems subject to hysteresis. Universiteit Twente,Faculteit EWI, Afdeling Toegepaste Wiskunde, Enschede, 23-10-2012.

Bootsveld, Menno. Dealing with imperfect knowledge in sensor processing. Universiteit Twente,Faculteit EWI, Afdeling Toegepaste Wiskunde, Enschede, 19-12-2012.

Geerts, Astrid. Detection of Interictal Epileptiform Discharges in EEG. Universiteit Twente,Faculteit EWI, Afdeling Toegepaste Wiskunde, Enschede, 18-09-2012.

Huurnink, Norbert. Skew calibration using local volatility methods. Universiteit Twente, FaculteitEWI, Afdeling Toegepaste Wiskunde, Enschede, 17-04-2012.

Lagerweij, Giske. Methodiek en analyse voor de herkenning van tumor weefsel op basis vanFDG-PET. Universiteit Twente, Faculteit EWI, Afdeling Toegepaste Wiskunde, Enschede,18-04-2012.

Lai Jiang. Bermudan option pricing with the Longstaff-Schwartz Monte Carlo – from theregressor’s perspective. Universiteit Twente, Faculteit EWI, Afdeling ToegepasteWiskunde, Enschede, 31-10-2012.


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Stoep van der, Anton. Sovereign credit ratings – analyzing overrides and migration behavior.Universiteit Twente, Faculteit EWI, Afdeling Toegepaste Wiskunde, Enschede, 25-1-2012.

Veenstra, Marko. Valuing options in natural gas contracts. Universiteit Twente, Faculteit EWI,Afdeling Toegepaste Wiskunde, Enschede, 29-06-2012.

Other publications

Aoki, E.H. and Boers, Y. and Svensson, L. and Mandal, P.K. and Bagchi, A. (2012) A Bayesiananalysis of the mixed labeling phenomenon in two-target tracking. Memorandum 1986,Department of Applied Mathematics, University of Twente, Enschede. ISSN 1874-4850.

Aoki, E.H. and Boers, Y. and Svensson, L. and Mandal, P.K. and Bagchi, A. (2012) An analysisof the Bayesian track labeling problem. Memorandum 1980, Department of AppliedMathematics, University of Twente, Enschede. ISSN 1874-4850.

Bagchi, A. (2012) In search of engineering mathematics. (2012, September 28) University ofTwente, Enschede. ISBN not assigned

Katsilieris, F. and Boers, Y. (2012) Optimal search: a p[ractical interpretation of information-drivensensor management. Memorandum 1979, Department of Applied Mathematics, Universityof Twente, Enschede. ISSN 1874-4850.

Kurula, M. and Zwart, H.J. (2012) The duality between the gradient and divergence operatorson bounded Lipschitz domains. Memorandum 1994, Department of Applied Mathematics,University of Twente, Enschede. ISSN 1874-4850.


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University of GroningenIndustrial Technology and Management (ITM)

General Information

AddressITM, Nijenborgh 4, 9747 AG Groningen, The Netherlands. Phone (secretary):+31–50-3638493.

Scientific staffprof.dr.ir. J.M.A. Scherpen, dr. B. Jayawardhana, dr. M. Cao prof.dr. C. de Persis

Technical and administrative staffing. H. W. van den Dool, lab coordinator S. Achterop, lab technician F.G. Fokkens, secretaryDTPA/SMS (E-mail: [email protected]/[email protected])

PhD studentsdivision DTPA(Alphabetic order) D. Alkano, R. Tri Cahyono M.Sc., from 10 December 2012,H. Garcia de Marina Peinado M.Sc., from 15 February 2012, Drs. R. Huisman, M.Sc., G.K.H.Larsen, M.Sc., H. Liu, M.Sc., M. Muñoz Arias M.Sc., Ir. R. Ouyang,M.Sc., M.Z. Romdlony,M.Sc., from 1 October 2012, M. Seslija M.Sc. (jointly with JBI), Ir. E. Vos (jointly with JBI),C. Wang, M.Sc. W. Xia M.Sc., F. Zhang, M.Sc., from 1 March 2012, J. Zhang, M.Sc., from1 June 2012, S. Zhang M.Sc. (jointly with JBI).

Temporary staff and postdocsDr. M. Mazo (until September 2012) , Dr. S. Fiaz (jointly with JBI)(until October 2012), Dr.T. Liu Dr. S. Rao (jointly with JBI).division SMST. Scholten, Ph.D. SMS, from 1 December2012, S. Trip, Ph.D. SMS, from 15 August 2012, M. Jafarian, Ph.D. SMS,

Cooperation with

division DTPAAustralian National University, Australia; Irmato, Drachten; City University of Hongkong,Hongkong; Delft University of Technology; ECN, Petten; Eindhoven University of Technology;HIT, Assen; KEMA, Groningen; Imperial College, London, UK; INCAS3, Assen; Nanonext,Netherlands; Nagoya University, Japan; NXP semiconductors, Eindhoven; Peking University,China; Politecnico di Bari, Italy; Princeton University, USA; Renault, France; Supelec, France;TNO, Groningen, Delft; Tsinghua University, China; University of Groningen; University ofOldenburg, Germany; University of Twente; UPC, Barcelona, Spain;Yale University,

USA; Zhejiang University, China. University of Tel Aviv; LAGEP, Université de Lyon, Lyon;LAAS-CNRS, Toulouse; University of Bath, Bath, Uk; University California of Santa Barbara,USA; Universidad de Guadalajara, Mexico; DFKI, Bremen.

division SMSAalborg University, Denmark; Grundfos, Denmark; INCAS3, Assen; Laboratoire des signauxet systemes, CNRS, Supelec, France; Politecnico di Torino, Italy; University of Groningen;University of Rome La Sapienza, Italy; University of Wurzburg, Germany; University ofStuttgart, Germany; Université catholique de Louvain, Belgium; Aarhus University,Denmark;University of Bologna, Italy; Forschungszentrum Telekommunikation Wien, Austria; Dong


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Energy, Denmark; Danfoss, Denmark; Grundfos, Denmark; kk-electronic, Denmark;Universiteit Twente, Enschede; TNO,Groningen; Waterbedrijf Groningen; Verkley.

Keywordsdivision DTPADistributed control systems, electrical circuits, electro-mechanical systems,mechanical systems, mechatronics, modeling, model reduction methods, nonlinear controlsystems, nano-manufacturing, passivity based control, space applications, autonomousrobots, sensor networks, distributed algorithms, cooperative control, graph theory, microand nano scale assembly.division SMSControl under communication constraints, cooperativecontrol, distribution networks, distributed control, event-based control, fault detection,formation control, hydraulic networks, manufacturing systems, networked control systems,nonlinear control systems, output regulation, quantized control, time-delay control systems,heat networks, smart grids, dynamic pricing, event-based control, cyber-physical systems.

Brief description

division DTPAIndustrial Technology and Management is the research institute of the faculty of Mathematicsand Natural Sciences that is connected to the Industrial Engineering and Managementeducation of the University of Groningen. This report is about the Discrete Technology andProduction Automation group within the institute. The group was started on 1 January 2007with the appointment of prof. Scherpen. The group has been growing in the past years withnew staff members and development of the lab.

The core research activity deals with the development of new nonlinear control systemsmodeling, realization and order reduction methods, distributed control systems, coordinationmethods, as well as control methods for nonlinear systems while relying on the physicalstructure of the system. The group focuses on applications to electrical, mechanical andelectro-mechanical systems, nano-manufacturing, mechatronics, robotics, smart grids,(distributed) sensor systems, as well as some space systems.

division SMSThe group Smart Manufacturing Systems was established in May 2011 with the appointmentof Prof. De Persis. The group is affiliated with the research institute Industrial Technologyand Management, Faculty of Mathematics and Natural Sciences.The research of the groupsfocuses on the modeling and control of complex systems by nonlinear dynamics andlarge-scale dimensions and their interaction with communication media and computationaldevices. Examples of these systems are found in manufacturing systems, distributionnetworks, supply chains, formation control systems, smart grids. Research areas whichprovide fundamental tools to investigate these problems include quantized and discontinuouscontrol, event-triggered control, time-delay systems, hybrid systems, cooperative controlsystems, output regulation. Since malfunctions in complex systems may have disruptiveeffects, fault detection and fault-tolerant control also play an important role.


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DISC projects

Distributed control of a network of households with micro CHP systems

J.M.A. ScherpenProjectleader:N.D. van Foreest (Operations dept, Faculty of Economics and Business)Participants:G. K. H. LarsenPhD students:Flexines (Koers Noord)Sponsored by:

DescriptionIn this project, we develop pricing mechanisms to control the electricity supply of largenumbers of micro Combined Heat Power (CHP) systems to the electricity grid. This type ofelectricity production differs from the current one: rather than a single-supplier multi-consumermarkets it becomes a multi-supplier multi-consumer market. As a household canindependently decide to switch on and off its micro CHP, the electricity supply may showlarge fluctuations, leading to instabilities of the electricity grid. Interesting control mechanismto match supply and demand are dual decomposition methods combined with pricing.

Coordination of mobile agents using coarsely quantized information

M. CaoProjectleader:H. LiuPhD students:

DescriptionIn this project, we look into the issues arising when the distributed controllers for thecoordination of mobile multi-agent systems can only utilize coarsely quantized information.The first step is to look at the formation control problems where range measurements areused. We will also look into techniques to reduce chattering as a result of the quantizationeffects. Later on, stability and robustness will also be studied to make the control strategiesapplicable in practical settings.

Analysis and control design for hysteretic systems

B. JayawardhanaProjectleader:R. OuyangPhD students:

DescriptionHysteresis is anonlinear phenomenon that is commonly found in a wide range of physicalsystems, such as, magnetic material, piezo-electric material and mechanical friction.Hysteresis phenomenon that is due to the friction, either between the magnetic domain-wallsor between mechanical surfaces, is known to dissipate energy by heat. This is related tothe concept of dissipativity in the systems theory literature. The aim of this research projectis to study the dissipativity property of Duhem hysteresis operator which can be useful forthe analysis and control design for systems containing such hysteresis elements.


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Passivity based control of a 7 DOF robotic arm for domotic applications

J.M.A. ScherpenProjectleader:M. Munoz AriasPhD students:Technological Institute Costa RicaSponsored by:

DescriptionThe Philips experimental robot arm is a kinematically redundant manipulator which is mainlyaimed at increasing dexterity. The robot manipulator, developed by Philips AppliedTechnologies for domotic applications, has seven degrees of freedom and includes humanoidcharacteristics of an upper limb motion. Humanoid kinematics and dynamics allow newdevelopments in the field of robotics. In this work, a model is derived and put in a physicalmodeling framework, so that passivity can be used as an instrumental property to derivecontrol methods that are relevant for domotic applications.

Structure preserving model reduction for port-Hamiltonian systems

J.M.A. Scherpen, A.J. van der Schaft (JBI)Projectleader:M. SeslijaPhD students:NWOSponsored by:

DescriptionThis project aims at structure-preserving discretaization methods for linear and nonlinearsystems. More specifically it aims at approximating port-Hamiltonian models, as naturallyobtained by network-modeling of multi-physics systems, by spatially discrete port-Hamiltoniansystems. Furthermore, control of spatially continuous systems by finite dimensional controlmethods in the port-Hamiltonian framework is considered.

Cooperative control of robotic multi-agent systems

M. CaoProjectleader:W. XiaPhD students:

DescriptionThis project studies nonlinear behaviors in robotic multi-agent systems. Distributedcooperative control laws will be designed for achieving desirable global performance byusing only local information.The results obtained will be applied to large scale mobile sensornetworks.

Energy-efficient design and control of robotic sensor networks

J.M.A. ScherpenProjectleader:M. Cao, A.J. van der Schaft (JBI)Participants:E. VosPhD students:STWSponsored by:

DescriptionThe aim of this research is to develop new energy-efficient design methodologies and novelcontrol strategies for robotic sensor networks. The key is to take a multidisciplinary andintegrative approach by jointly considering the hardware level of mobile sensor-equipped


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robotic devices and the system level of wireless coordination of groups of mobile roboticsensors. For the design of mobile sensor-integrated robotic devices, research will focus ontaking full advantage of newly developed sensors, methodology to harvest and optimizeenergy sources and integrate such sensors with mobile robotic platforms. With optimalenergy consumption and a proper system design, the platforms to be developed will be ableto operate in complex, time-varying, unknown, harsh and hazardous environment and acquiredata reliably via ground penetration radars (GPR), ultrasound imagers, magnetic fielddetectors and other sensors. Parallel to the development of each individual energy-consciousrobotic sensor, a system level assault on the energy efficient control of sensor networks willalso be carried out.

Mechatronic design of a cryogenic chopper mechanism for mid-infraredwavelength observations

B. JayawardhanaProjectleader:J.M.A. ScherpenParticipants:R. HuismanPhD students:SRONSponsored by:

DescriptionMid infrared wavelength observations are recognized as an important field of study inastronomy. These observations can provide further evidence of the early universe andconfirm various theories about objects that are intrinsically cold or redshifted due to theexpansion of the universe. The observation at mid-infrared wavelength is known to becorrupted by noise from thermal background in the sky. A chopping mechanism is commonlyused to reduce this thermal noise. In order to fulfill its specific functionality, the design ofchopping mechanisms have to take several factors into account: Firstly, it must work in thecryogenic environment where the sensitive mid-infrared instrument is located; Secondly, itmust have fast response time in order to maximize observation time; Thirdly, it provides anaccurate movement. In this project, advanced modeling and controller design for the choppingmechanism in several instruments will be developed, where one instrument, and thus thechopping mechanism is currently being designed in close collaboration with our project.

Formation swimming of robotic fish

M. CaoProjectleader:C. WangParticipants:

DescriptionIn this project, we utilize the home-made robotic fish testbed to develop distributed controlalgorithms to coordinate the swimming of a group of robotic fish. We utilize the existingresults on collective hydrodynamics caused by the fish groups and try to come up withenergy-efficient control strategies. Such algorithms on the one hand can be useful forbiologists to understand real fish behavior and on the other hand provide new inspirationfor the design of new locomotion for underwater robots.


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Constrained controllability of diffusively coupled multi-agent systems

M. Cao, K. Camlibel(JBI)Projectleader:S. ZhangPhD students:Ubbo Emmius fundSponsored by:

DescriptionIn this project, we are concerned with the controllability issue for multi-agent systems whenthe agents are diffusively coupled together and when the control signals are constrained indifferent ways. The goal is to identify the class of constrained control inputs such that thesystem is controllable.This can be used for designing distributed control laws for autonomousrobotic teams. A robotic testbed will be utilized to test theoretical results.

Event-triggered distributed control

M. CaoProjectleader:M. MazoParticipants:INCAS3Sponsored by:

DescriptionWe aim at developing new control strategies for distributed networked systems wherecontrollers are activated only when certain events take place. The advantage of suchevent-triggered approach is that the energy consumption for control actions can be greatlyreduced. We introduce the practical stability in this context and look for control strategiesthat can be implemented in industrial distributed networks.

Distributed Control in The New Gas Chain

J.M.A. ScherpenProjectleader:B. Jayawardhana, A.J. van der SchaftProjectleader:S. RaoParticipants:D. AlkanoPhD students:EdgarSponsored by:NWO – Groningen Centre for Systems BiologySponsored by:

DescriptionIn the near future, the Dutch gas distribution is changing due to the decline of domestic gasproduction and the increase of renewable gas from a share of 0.1% to 8 - 12% and 15 - 20%in 2020 and 2030, respectively. Renewable gas is mainly produced by farmers. Hence, theycan be both producer and consumer (prosumer) in the gas grid. This leads the gasinfrastructure change toward a multi-producer multi-consumer market. Along with thepossibilities that the prosumers have gas storage, the future gas grid can no longer bepassive. The grid needs a way to monitor and control the balance among gas production,consumption, and storage within the network.

The research aims at providing a fair and optimal price mechanism for heterogeneousprosumers in the gas grid.The expected outcome is a balance among supply, demand, andstorages in the network. The mechanism will be developed using similar principles appliedin Flexines project which is developed for the electricity grid.


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DescriptionBiological ageing can be defined as the decline of vital functions of an organism withincreasing age. Energy metabolism and the process of ageing are intricately linked. First,(mild) calorie restriction extends the average life span of many different organisms, fromyeast to mammals, and it delays the onset of age-related diseases. Second, in higherorganisms physical exercise - which is on the demand side of energy metabolism - decreasesdisease risk and extends life span. Third, many of the genes that were found to be relatedto ageing and lifespan, are directly involved in energy metabolism. And last but not least,the functionality of the metabolic system itself declines with age. The aim of the project is(i) to reveal the changes in the metabolic network in mouse that cause the decline of flexibilityof the metabolic system with age and (ii) understand how this decline is modulated by calorierestriction and exercise.

Ongoing work

Modeling and analysis of energy metabolism in mouse

Distributed Coordination and Model Reduction of Multi-Agent Networks

J.M.A. Scherpen, H.L. Trentelman (JBI)Projectleader:Fan ZhangPhD students:CSCSponsored by:

DescriptionWe investigate robust cooperative control of multiple locally interacting dynamic nonlinearsystems with uncertainties. We focus on a nonlinear extension of existing results aboutrobust synchronization protocols, which is closely related to practical engineering applications,e.g. satellite swarms and mobile robotic sensor networks. In addition, we consider large-scalenetworks, where model reduction may first be needed to make the analysis and applicationof distributed control methods feasible. The model reduction methods for distributed controlof networks will be developed further, and stability and error bounds will be investigated.

Evolutionary Games in Multiagent Systems

Ming CaoProjectleader:Jianlei ZhangPhD students:Bernoulli ScholarshipSponsored by:

DescriptionThis PhD research project is to study evolutionary games in complex networks. In particular,efforts are made to investigate why and how individuals cooperate with others. Complexnetwork models are used to describe the structures of populations in order to revealmechanisms that lead to the emergence and maintenance of cooperation in populations. Itis also of interest to know how different strategies spread in complex networks and how theyinfluence each other. Theoretical yet realistic models are expected to be constructed toexplain the evolutionary dynamics in complex networks.


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Embracing constraints in complex control systems design

J.M.A. Scherpen, B. JayawardhanaProjectleader:M. Z. RomdlonyPhD students:DIKTI scholarshipSponsored by:

DescriptionConstraints on sensors and actuators, on energy and resources and no computational powerare inevitable limitations that have to be dealt with for the design of complex systems. Theypose significant systems design challenges and can hinder the innovation process. As anenabling and integration technology in the design of modern complex systems, control designmust confront these challenges and be able to embrache them in the feedback loop.

In a contrast to the matured control methods for linear systems, control methods for nonlinearsystmes with constraints are still a far cry from being complete. Therefore the proposedresearch program focuses on the development of novel nonlinear control methods thathandle contraints, with low computational load and with prescribed transient, as well as,prescribed robust behavior.The developments are facilitated by recent advances for nonlinearcontrol systems.

Controller design for robots in ship inspection

J.M.A. Scherpen, M.CaoProjectleader:H. Garcia de Marina PeinadoPhD students:Interreg Smartbot ProjectSponsored by:

DescriptionThis project is carried out in the context of the Interreg Smartbot project that aims to useautonomous robots equipped with sensors to carry out complex tasks. In particular, theproject is mainly concerned with the Roboship subproject that develops autonomous intelligentrobots for the inspection and repair of ballast water tanks of ships and the Sinbot subprojectthat uses smart industrial robots in complex production environment.The focus of this projectis to develop controllers that will enable the robots to localize, track, manoeuvre andcoordinate efficiently even in the face of an unknown environment with unexpected events.

division SMS

QUICK

C. De PersisProjectleader:M. JafarianPhD students:NWOSponsored by:

DescriptionThe purpose of this research is to develop distributed formation control methods underlimited information. By limited information it is usually meant that each element of theformation exchange measurements regarding its internal state with a limited number ofagents called neighbors. In this research the plan is to go further and investigate the problemin the case the information exchange (and the control laws)are allowed to take values in afinite set and are transmitted (respectively, are applied) asynchronously, and where thedynamics of the elements of the formation have a particular physical structure.


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EDGE

C. De PersisProjectleader:Sebastian TripPhD students:Danish Council for Strategic ResearchSponsored by:

DescriptionThe EDGE project focuses on how to use windmill energy efficiently. We will investigatecontrol algorithms and dynamic pricing for distributing and storing wind energy whileincreasing the overall welfare. The algorithms must cope with the physical constraintsimposed by the power grid as well as with the dynamics of the economic market. Academicpartners within the project are Aalborg University, Aarhus University and ForschungszentrumTelekommunikation Wien. Industrial partners are Dong Energy, Danfoss and kk-electronic.

Flexiheat

C. De PersisProjectleader:Tjardo ScholtenPhD students:SNN (Samenwerkingsverband Noord-Nederland)Sponsored by:

DescriptionThis project is concerned with the control, metering and pricing of thermal networks. Similarlyto other utility networks, thermal networks involve a large number of autonomous agents(producers and consumers) which share interest for a common product (the heat) withdifferent needs and demands. The actions taken by producers and consumers affect eachother via the shared network through which the heat is distributed. General methods tomanage (control) the entire systems are needed in order to: (i) avoid destabilizing effects inthe network due to the interplay among agents with contrasting interests; (ii) increase thegeneral social welfare, measured in terms of surplus (profit minus costst) for both consumersand producers while balancing supply and demand; (iii) suppress possible undesiredtransients (large oscillations) in the distribution network due to time-varying working conditionsand control pressures with reduced power pump consumption. The aim of this project is toprovide provably correct methodologies to control heat networks. Partners and involvedcompanies are RenQi, Hanzehogeschool Groningen, Universiteit Twente, TNO, A.Hak,Attero, Electrabel, Holland Malt, KEMA, Waterbedrijf Groningen, Rendo, Essent, TCN Sig,Verkley, Groningen Seaports, Liandon

Publications

Book chapters/parts

Jeltsema, D., J.M.A. Scherpen; Power-based modeling; In Dynamics and Control of SwitchedElectronic Systems, Advances in Industrial Control, Eds. F. Vasca, L. Iannelli, SpringerVerlag, London (2012) 245-271. Online via http://dx.doi.org/10.1007/978-1-4471-2885-4_8.


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Camlibel, M.K., S. Zhang, M. Cao, M.; Comments on Controllability analysis of multi-agentsystems using relaxed equitable partitions; International Journal of Systems, Control andCommunications, Vol. 4, no 1-2, p. 72-75

Cao M., A. S. Morse; An adaptive approach to the range-only station keeping problem;International Journal of Adaptive Control and Signal Processing, Special Issue on RecentTrends in Adaptive Switching/Mixing Control, Vol. 26, no.8, p. 757-777

De Persis, C., B., Jayawardhana; Coordination of Passive Systems under QuantizedMeasurements; SIAM Journal on Control and Optimization, Vol. 50, no. 6, p. 3155–3177

Del Puerto Flores, D., R. Ortega, J.M.A. Scherpen; A cyclo-dissipativity characterization ofpower factor compensation of nonlinear loads under nonsinusoidal conditions; International Journal of Circuit Theory and Applications, Vol. 40, no 10, p. 1053-1069.Online available via http://onlinelibrary.wiley.com/doi/10.1002/cta.771/abstract .

Dirksz, D.A., J.M.A. Scherpen; On tracking control of rigid joint robots with only positionmeasurements; in IEEE Transactions on Control Systems Technology. Online availablevia http://dx.doi.org/10.1109/TCST.2012.2204886 .

Dirksz, D.A., J.M.A. Scherpen; Power-based control: Canonical coordinate transformations,integral and adaptive control; Automatica, Vol. 48, p. 1046-1056. Online viahttp://dx.doi.org/10.1016/j.automatica.2012.03.003 .

Dirksz, D.A., J.M.A. Scherpen; Power-based setpoint control: experimental results on a planarmanipulator; IEEE Transactions on Control Systems Technology, Vol. 20, no. 5, p.1384-1391. Online via http://dx.doi.org/10.1109/TCST.2011.2163514 .

Dirksz, D.A., J.M.A. Scherpen; Structure preserving adaptive control of port-Hamiltonian systems;IEEE Transactions on Automatic Control, Vol. 57, no. 11, p. 2880-2885. Online availablevia http://dx.doi.org/10.1109/TAC.2012.2192359 .

Egerstedt, M., S. Martini, M. Cao , M. K. Camlibel, A. Bicchi; Interacting with networks: Howdoes structure relate to controllability in single-leader, consensus networks?; ControlSystems Magazine, Vol. 32, no. 4, p. 66-73

Garcia de Marina Peinado, H., F. Espinosa, C. Santos; Adaptive UAV Attitude EstimationEmploying Unscented Kalman Filter, FOAM and Low-Cost MEMS Sensors; Sensors2012, Vol. 12, p. 9566-9585

Jayawardhana, B., R. Ouyang, V. Andrieu; Stability of systems with the Duhem hysteresisoperator: The dissipativity approach; Automatica Vol. 48, p. 2657–2662

Liu, H., M. Cao, C. De Persis; Quantization effects on synchronized motion of teams of mobileagents with second-order dynamics, Systems and Control Letters, Vol. 61, no. 12, p.1157-1167

Meza, C., D. Biel, D. Jeltsema, J.M.A. Scherpen; Lyapunov-based control scheme forsingle-phase grid-connected PV central inverters; IEEE Transactions on Control SystemsTechnology, Vol. 20, no. 2, p. 520-529. Online viahttp://dx.doi.org/10.1109/TCST.2011.2114348 .

Rao, S., P. Rapisarda; An algebraic approach to the realization of lossless negative imaginarybehaviors; SIAM Journal on Control and Optimization, Vol. 50, no. 3, p. 1700-1720

Rao, S.; A Minimal State Map for Strictly Lossless Positive Real Behaviors; Automatic Control,IEEE Transactions on, Vol. 57 , no. 7, p. 1696 – 1708

Rao, S.; Controllability of conservative behaviours; International Journal of Control, Vol. 85, no.8, p. 983-989


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Seslija M., A.J. van der Schaft, J.M.A. Scherpen; Discrete exterior geometry approach tostructure-preserving discretization of distributed-parameter port-Hamiltonian systems;Journal of Geometry and Physics, Vol. 62, no. 6, p. 1509-1531. Online viahttp://dx.doi.org/10.1016/j.geomphys.2012.02.006 .

Stewart, A., M. Cao, A. Nedic, D. Tomlin, N. E. Leonard; Towards human-robot teams:Model-based analysis of human decision making in two-alternative choice tasks withsocial feedback; Proceedings of IEEE, Special Issue on Interaction Dynamics at theInterface of Humans and Smart Machines ,Vol.100, no. 3, p. 751-775


De Persis, C., B. Jayawardhana; On the internal model principle in formation control and inoutput synchronization of nonlinear systems; In: Proceedings 51st IEEE Conference onDecision and Control, Maui, December 2012, p. 4894-4899

De Persis, C., H. Liu, M. Cao; Robust decentralized output regulation for uncertainheterogeneous systems; In: Proceedings of 2012 American Control Conference, Montreal,Canada, July 2012, p. 5214-5219

De Persis, C., P. Frasca; Self-triggered coordination with ternary controllers; In ProceedingsIFAC Workshop on Estimation and Control of Networked Systems, Santa Barbara, CA,USA, Sep. 2012, p. 43–48

Dirksz, D.A., J.M.A. Scherpen, A.J. van der Schaft, M. Steinbuch; Notch filters forport-Hamiltonian systems; In: Proceedings American Control Conference, ACC12 (inIEEE Xplore), Montreal, Canada, June 2012, p. 238-243

Dirksz, D.A., J.M.A. Scherpen; A port-Hamiltonian approach to visual servo control of a pickand place system; In: Proceedings IEEE 51st Annual Conference on Decision and Control(CDC), 2012, p. 5661-5666

Doria-Cerezo, A., L. van der Heijden, J.M.A. Scherpen; Memristive Port-Hamiltonian Control:Path-Dependent Damping Injection in Control of Mechanical Systems; In: ProceedingsIFAC Workshop on Langrangian and Hamiltonian Methods for Nonlinear Control(LHMNLC12), Bertinoro,Italy, August 2012, p. 172-177

Huisman, R., B. Jayawardhana; On the design of hybrid robust output regulation for the METIScold chopper; In: Proceedings 7th IFAC Symposium on Robust Control Design, Aalborg,June 2012, 593-598

Ionescu, T.C., J.M.A. Scherpen, O.V. Iftime, A. Astolfi; Balancing for linear systems as a momentmatching problem; In: Proceedings Symposium on Mathematical Theory for Networksand Systems, MTNS12, Melbourne, Australia, July 2012, 8 pages

Jayawardhana, B., S. Rao, A. van der Schaft; Balanced chemical reaction networks governedby general kinetics; In: Proceedings 20th Mathematical Theory of Networks and Systems,Melbourne, June 2012, 4 pages extended abstract

Jayawardhana, B., S. Rao, A. van der Schaft; Chemical reaction networks and consensusdynamics; In: Proceedings 20th Mathematical Theory of Networks and Systems,Melbourne, June 2012, 4 pages extended abstract

Larsen, G.K.H., N.D. van Foreest, J.M.A. Scherpen; A Price mechanism for supply demandmatching in a grid of households with micro CHP; In Proceedings EPJWeb of Conferences,2nd European Energy Conference, 33, 01011 (2012), EDP Sciences, DOI:10.1051/epjconf/20123301011, 8 pages

Larsen, G.K.H., S. Trip, N.D. van Foreest, J.M.A. Scherpen; Local supply demand balancingthrough prices: Distributed MPC for controlling micro-CHP's in a network; In: ProceedingsAmerican Control Conference, ACC12 (in IEEE Xplore), Montreal, Canada, June 2012,p. 3089-3094


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Liu, T., D.J. Hill, B. Liu; Synchronization of dynamical networks with distributed event-basedcommunication; In: Proceedings IEEE 51st Annual Conference on Decision and Control(CDC), 2012, p. 7199 – 7204

Mazenc, F., C. De Persis, M. Bekaik; Practical stabilization of nonlinear systems withstate-dependent sampling and retarded inputs; In: Proceedings American ControlConference (ACC), 2012, p. 4703-4708

Mazo Jr., M., M. Cao; Decentralized event-triggered control with one bit communications; In:Proceedings of the 4th IFAC Conference on Analysis and Design of Hybrid Systems,Eindhoven, The Netherlands, June 2012, p. 52-57

Munoz-Arias, M., J.M.A. Scherpen, D.A. Dirksz; A Class of Standard Mechanical System withForce Feedback in the Port-Hamiltonian Framework; In: Proceedings IFAC Workshopon Langrangian and Hamiltonian Methods for Nonlinear Control (LHMNLC12), Bertinoro,Italy, August 2012, p. 90-95

Munoz-Arias, M., J.M.A. Scherpen, D.A. Dirksz; Force feedback of a manipulator system in theport-Hamiltonian framework; In: Proceedings Symposium on Mathematical Theory forNetworks and Systems, MTNS12, Melbourne, Australia, July 2012, 4 pages extendedabstract

Nuño, E., R. Ortega, B. Jayawardhana, L. Basanez; Coordination of Multi-agent Systems viaEnergy-Shaping: Networking Improves Robustness; In: Proceedings 4th IFAC Workshopon Lagrangian and Hamiltonian Methods for Non Linear Control, Bologna, August 2012,p. 155-160

Ouyang, R., B. Jayawardhana, V. Andrieu; On the robustness of hysteretic second-ordersystems with PID: iISS approach; In: Proceedings 51st IEEE Conference on Decisionand Control, Maui, December 2012, p. 5894-5899

Ouyang, R., B. Jayawardhana; Stability analysis and controller design for a linear system withDuhem hysteresis nonlinearity; In: Proceedings American Control Conference (ACC),2012 , p. 1676-1681

Rao, S., B. Jayawardhana, A.J. van der Schaft; On the graph and systems analysis of reversiblechemical reaction networks with mass action kinetics; In: Proceedings IEEE AmericanControl Conference, Montreal, June 2012., p. 2713-2718

Seslija, M., J.M.A. Scherpen, A.J. van der Schaft; Port-Hamiltonian systems on discretemanifolds; In: Proceedings MathMod 2012 - 7th Vienna International Conference onMathematical Modeling

Seslija, M., J.M.A. Scherpen, A.J. van der Schaft; Reduction of Stokes-Dirac structures andgauge symmetry in port-Hamiltonian systems; In: Proceedings 4th IFAC Workshop onLagrangian and Hamiltonian Methods for Non Linear Control, Bertinoro, Italy, 29-31August 2012, p. 114-119

Seslija, S., J.M.A. Scherpen, A.J. van der Schaft; Composition of canonical port-Hamiltoniansystems on smooth and discrete manifolds; In: Proceedings MTNS 2012 - the 20thInternational Symposium on Mathematical Theory of Networks and Systems, Universityof Melbourne, 9-13 July 2012, 5 pages extended abstract

Shaik, F., D. Zonetti, R. Ortega, J.M.A. Scherpen, A.J. van der Schaft; On Port-HamiltonianModeling of the Synchronous Generator and Ultimate Boundedness of Its Solutions; In:Proceedings IFAC Workshop on Langrangian and Hamiltonian Methods for NonlinearControl (LHMNLC12), Bertinoro, Italy , August 2012, p. 30-35

Shaik, F., D. Zonetti, R. Ortega, J.M.A. Scherpen, A.J. van der Schaft; Port-Hamiltonian modelingof power networks; In: Proceedings Symposium on Mathematical Theory for Networksand Systems, MTNS12, Melbourne, Australia, July 2012, 4 pages extended abstract


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Vos, E., J.M.A. Scherpen, A.J. van der Schaft; Port-Hamiltonian approach to deployment; In:Proceedings Symposium on Mathematical Theory for Networks and Systems, MTNS12,Melbourne, Australia, July 2012, 4 pages extended abstract

Wang, C., B. Wu, M. Cao, G. Xie; Modified snowdrift games for multi-robot water polo matches;In: Proceedings of the 24th Chinese Control and Decision Conference, Taiyuan, China,May 2012, , p. 164-169

Wang, C., G. Xie, M. Cao, L. Wang; Circle formation for anonymous mobile robots with orderpreservation; In: Proceedings of 51st IEEE Conference on Decision and Control, Maui,USA, December 2012, p. 1433-1438

Xia, W., M. Cao; Cluster Synchronization and controllability of complex multi-agent networks;In: Proceedings of the 2012 IEEE International Symposium on Circuits and Systems,Seoul, Korea, May 2012, p. 165-168

Zhang, S., M. Cao, M. K. Camlibel; On the controllability of diffusively coupled multi-agentnetworks with switching topologies; In: Proceedings of the 20th International Symposiumon Mathematical Theory of Networks and Systems, Melbourne, Australia, August, 2012, 3 pages extended abstract

M.Sc. theses

Boomer, J.Title: Improving noise reduction in astronomical observations: A hybrid control designfor the HIFI Focal Plane Chopper. Supervisors: B. Jayawardhana, C. De Persis, Friday,23 November 2012

Bruins, M. Title: Designing a multi-agent collaborative control system to improve traffic flow.Supervisors: J.M.A. Scherpen, M. Cao, Monday, 27 August 2012

Smit, K. Title: The Optimal Extraction Rate of Non Renewable Resources Using Pontryagin'sMaximum Principle. Supervisors: M. Cao, J.M.A. Scherpen, E. Fossas, Thursday, 23August 2012

Van Logtestijn, M. Title: System identification and inversion of complex nonlinear systems:Application to a Waste-to-Energy plant. Supervisors: J.M.A. Scherpen, H.J. Heeres, A.Astolfi, Monday, 17 December 2012

Other publications

Alkano, D., J.M.A. Scherpen; Distributed Dynamic Price Mechanism in The New Gas Chain;In Proceedings 31st Benelux Meeting on Systems and Control, Heijderbos,Heijen/Nijmegen, The Netherlands, March 27-29, 2012, page 51 book of abstracts

Dirksz, D.A., J.M.A. Scherpen, A.J. van der Schaft, M. Steinbuch; Notch filters forport-Hamiltonian systems; In: Proceedings 31st Benelux Meeting on Systems and Control,Heijderbos, Heijen/Nijmegen, The Netherlands, March 27-29, 2012, page 150 book ofabstracts

Huisman, R., B. Jayawardhana; Hybrid Robust Output Regulation for the METIS Chopper; InProceedings 31st Benelux Meeting on Systems and Control, Heijderbos, Heijen/Nijmegen,The Netherlands, March 27-29, 2012, page 145 book of abstracts

Jafarian, M., C. De Persis; Quantized average consensus with delay; In: Proceedings 31stBenelux Meeting on Systems and Control, Heijderbos, Heijen/Nijmegen, The Netherlands,March 27-29, 2012, page 61 book of abstracts

Larsen, G.K.H., N.D. van Foreest, J.M.A. Scherpen; Optimal control of electricity generationfrom μ-CHPs in a network; In: Proceedings 31st Benelux Meeting on Systems and Control,Heijderbos, Heijen/Nijmegen, The Netherlands, March 27-29, 2012, page 100 book ofabstracts


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Munoz-Arias, M., J.M.A. Scherpen; Force Feedback of a Manipulator System in theport-Hamiltonian Framework; In: Proceedings 31st Benelux Meeting on Systems andControl, Heijderbos, Heijen/Nijmegen, The Netherlands, March 27-29, 2012, page 64book of abstracts

Ouyang, R.Y., B. Jayawardhana; Stability analysis for a system with hysteresis; In: Proceedings31st Benelux Meeting on Systems and Control, Heijderbos, Heijen/Nijmegen, TheNetherlands, March 27-29, 2012, page 36 book of abstracts

Seslija, M., J.M.A. Scherpen, A. van der Schaft; Port-Hamiltonian Systems on SimplicialComplexes; In: Proceedings 31st Benelux Meeting on Systems and Control, Heijderbos,Heijen/Nijmegen, The Netherlands, March 27-29, 2012, page 181 book of abstracts

Seslija, M., J.M.A. Scherpen, A.J. van der Schaft; Dirac structures and Port-Hamiltonian systemson discrete manifolds with application to structure-preserving discretization of field-theories;In: Proceedings 7th workshop on Advanced Computational Electromagnetics, ACE2012,Karslruhe, Germany, March 2012, 1page

Shaik, F., A.J. van der Schaft, J.M.A. Scherpen, D. Zonetti, R. Ortega; Port Hamiltonian modelingof Power Networks; In Proceedings 31st Benelux Meeting on Systems and Control,Heijderbos, Heijen/Nijmegen, The Netherlands, March 27-29, 2012, page 140 book ofabstracts

Vos, E., J.M.A. Scherpen, A.J. van der Schaft; Port-Hamiltonian approach to deployment on aline; In: Proceedings 31st Benelux Meeting on Systems and Control, Heijderbos,Heijen/Nijmegen, The Netherlands, March 27-29, 2012, page 111 book of abstracts

Wang, C., B. Wu, M. Cao, G. Xie; Coordinating robots in water polo matches using modifiedsnowdrift games; In: Proceedings 31st Benelux Meeting on Systems and Control,Heijderbos, Heijen/Nijmegen, The Netherlands, March 27-29, 2012, page 66 book ofabstracts

Xia, W., M. Cao; Sarymsakov matrices and coordination tasks for multi-agent systems; In:Proceedings 31st Benelux Meeting on Systems and Control, Heijderbos, Heijen/Nijmegen,The Netherlands, March 27-29, 2012, page 94 book of abstracts

Zhang, S., M.K. Camlibel, M. Cao; Controllability of diffusively coupled multi-agent systemswith switching topologies; In Proceedings 31st Benelux Meeting on Systems and Control,Heijderbos, Heijen/Nijmegen, The Netherlands, March 27-29, 2012, page 156 book ofabstracts


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University of GroningenJohann Bernoulli Institute for Mathematics and ComputerScienceResearch Program SystemsControl and Applied Analysis

General Information

AddressJohann Bernoulli Institute for Mathematics and Computer Science, University of Groningen,P.O. Box 407, 9700 AK Groningen, The Netherlands.

Scientific staffDr. M.K. Camlibel, Prof.dr. A.J. van der Schaft, Prof.dr. H.L. Trentelman, Dr. M.E. Dür (tillSeptember first).

Technical and administrative staffK.M.E. Schelhaas

PhD studentsP.J.C. Dickinson, A. Everts, S. Gottimukkala, L. Gijben, O. Ivanov, B. Jargalsaikhan, D.Kaba, Q.T. Le, N. Monshizadeh, M. Seslija, E. Vos, J.Q. Wei. S. Zhang F. Zhang

Temporary staff and postdocsDr. C. Dobre. Dr. S. Fiaz. Dr. S. Rao

Cooperation withThe members of the program have direct collaboration with colleagues working in otherscientific disciplines such as control engineering, robotics, mechatronics, economics,management science, and systems biology.

In particular, there is a close collaboration with the control engineering groups at theneighboring Institute for Industrial Engineering and Management within the recentlyestablished Groningen Center for Systems and Control.

Lanshan Han (Purdue University),

Jong-Shi Pang (University of Illinois, Urbana-Champaign),

Maurice Heemels (Eindhoven University of Technology),

Hans Schumacher (Tilburg University),

Bernard Brogliato (INRIA Rhone-Alpes),

Kiyotsugu Takaba (University of Kyoto, Japan),

Jochen Trumpf (ANU, Canberra, Australia),

Paolo Rapisarda (University of Southhampton, UK),

Jan C. Willems (Katholieke Universiteit Leuven, Belgium).

General Information

University of GroningenJohann Bernoulli Institute for Mathematics and Computer Science

Research Program SystemsControl and Applied Analysis

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KeywordsThe research program Systems, Control and Applied Analysis (SCAA) is devoted to theanalysis, control and optimization of complex systems. The mathematical research in thisprogram is motivated by a wide range of application areas in various fields of engineering,operations research, and systems biology. Mathematical systems and control theory dealswith the mathematical modeling, analysis and control of open systems evolving in time. Thedynamics is often described by ordinary or partial differential equations, but can be also amixture of continuous and discrete dynamics. This dynamical behavior is not only sought tobe analyzed, but to be influenced controlled and optimized as well; by the selection ofparameters, addition of feedback loops, and the interconnection to other dynamical systemsit controller design. Typically the mathematical system models under consideration aredescribed by under-determined sets of differential equations. Hence there are free variablesin the system description corresponding to inputs, which allow for interaction with theenvironment. Furthermore, the systems point of view is emphasized, in the sense thatlarge-scale and heterogeneous dynamical systems are viewed as the interconnection ofsmaller system components, where the overall dynamics is determined by the dynamics ofthe components the interconnection structure. This point of view is prevailing in many areasof engineering and economics, and is receiving increasing attention in the life sciences(systems and synthetic biology, biological feedback systems, etc.). Mathematical optimizationtheory is concerned with the development of solution algorithms for optimization problems.Depending on the structure of the objective function and the feasible set, methods involvingdiscrete or nonlinear features have to be developed. Special emphasis in the researchprogram is given to nonlinear quadratic problems which at the same time involve binaryvariables. These problems have numerous applications in science, engineering andeconomics.They can be modeled as linear problems over special matrix cones semidefiniteprogramming, copositive programming which permits a new approach to tackle theseproblems. The main lines of research in the program are:

DISC projects

Modeling, simulation and control of multi-physics systems asport-Hamiltonian systems.

Arjan van der SchaftProjectleader:Marko Seslija, Ewoud Vos, Shaik Fiaz, JieQiang WeiPhD students:

DescriptionPort-Hamiltonian systems are generalized Hamiltonian systems where the geometric structureis derived from the interconnection structure of the complex system.The aim of this researchis to provide a systematic mathematical theory

for the modeling, analysis and simulation of multiphysics,mixed lumped- and distributedparameter,systems by making explicit the underlying physical structure, including energybalances and other conservation laws. Current research themes include structure-preservingspatial discretization and model reduction, and modeling of power and distribution systems.Furthermore, the

port-Hamiltonian framework is employed for controller design, by attaching controllerport-Hamiltonian systems and shaping the Hamiltonian and other

University of GroningenJohann Bernoulli Institute for Mathematics and Computer ScienceResearch Program SystemsControl and Applied Analysis

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conserved quantities to a desired Lyapunov function for the controlled system, leading tophysically inspired and robust control strategies.

Applications include the coordination control of robotic networks and the control andoptimization of distribution networks.

Behavioral systems theory, and control by interconnection.

Harry TrentelmanProjectleader:Arjan van der SchaftParticipants:Sasanka Gottimukkala, Harsh VinjamoorPhD students:

DescriptionThe traditional way of modeling dynamical systems that interact with their environment isby an input-output map. However, physical systems in general

do not exhibit the information flow direction that is presupposed by the input-output structure.In the behavioral approach, all external system variables are therefore a priori treated onan equal footing, while the mathematical model specifies a subset of the set in which theexternal variables take their values as being possible. This subset is called the behavior ofthe system. Many

modeling and control questions are fruitfully studied in this novel setting, including the 'controlby interconnection' problem generalizing classical feedback control design for achieving acertain specification. Although most of

the research aims at linear differential systems it also provides inspiration

for nonlinear and hybrid dynamical systems.

Analysis and design of piecewise-affine, switching, and hybrid dynamicalsystems

Kanat CamlibelProjectleader:Arjan van der Schaft, Harry Trentelman.Participants:Thuan Quang Le, Devrim Kaba, Nima Monshizadeh, Shuo ZhangPhD students:

DescriptionHybrid systems are a mixture of interacting continuous and discrete dynamics, and arisenaturally in embedded systems and physical systems modeling. Important

research issues concern the analysis of hybrid systems and their solution trajectories, thedevelopment of compositional reasoning techniques, the analysis of structural properties ofcontrollability and stabilizability, and the design of controllers. From a mathematical point ofview hybrid systems necessitate the merging of concepts and tools from continuous dynamicswith

those from discrete dynamics, thus linking to formal verification tools from computer science.The mathematical analysis of piecewise-affine and hybrid

systems is heavily intertwined with optimization theory and non-smooth analysis.



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Network dynamics

Kanat Camlibel, Harry Trentelman, Arjan van der SchaftProjectleader:Shuo Zhang, JieQiang Wei, Nima MonshizadehPhD students:

DescriptionNetwork dynamics and dynamical multi-agent systems arise in many fields of engineeringand science. Systems and control theory contributes to this

area by providing concepts and tools for the study of structural properties such ascontrollability (leaderfollower networks) and their control, and issues such as synchronizationand model reduction of multi-agent systems. This entails a close interplay of geometricsystems and control theory and algebraic graph theory.

Mathematical optimization theory

Mirjam DürProjectleader:Peter Dickinson, Luuk Gijben, Bolor JargalsaikhanPhD students:

DescriptionMathematical optimization theory is concerned with studying structural properties anddeveloping solution methods for mathematical optimization problems. The focus is oncombinatorial problems and on nonconvex quadratic optimization problems. The studiedmethodology is to transform the problem into a higher dimensional matrix space, permittingto move the difficult constraints (quadratic and/or binary) entirely into a certain cone constraint.This leads to

copositive and semidefinite programming.

M.K. Camlibel: Analysis of piecewise affine dynamical systems, linear systems with convexconstraints, model reduction of switched linear systems, controllability of multi-agent systems.

P.J.C. Dickinson: Structural properties of co-positive optimization problems.

Cristian Dobre: Semidefinite and copositive optimization problems, modeled both in finite andinfinite dimensional settings.Whereas in the finite setting the data of the problems are matrices,in the infinite case the duality between the space of continuous functions and the space ofmeasures is exploited.

A.R.F. Everts: Analysis of piecewise affine dynamical systems, geometric approach, disturbancedecoupling.

M. Dür: Mixed-integer nonlinear optimization. Optimization over convex matrix cones. Copositiveprogramming. Quadratic and binary optimization problems.

S. Fiaz: Modeling and analysis of power networks; coordination control of physical systems.

S. Gottimukala: Rational representations; stability analysis of uncertain behavioral systems,gap metric, behavioral distance.


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L. Gijben: Quadratic programming problems.

B. Jargalsaikhan: Semi-infinite approaches to copositivity.

D. Kaba: Linear systems with convex constraints.

Q.T. Le: Analysis of piecewise affine dynamical systems.

N. Monshizadeh: Model reduction of switched linear systems, synchronization of multi-agentsystems under switching network topologies, model reduction of multi-agent systems.

M. Seslija (co-supervision J.M.A. Scherpen, ITM):

Structure-preserving discretization and model reduction of port-Hamiltonian systems.

H.L. Trentelman: Control in a behavioral setting; pole placement and stabilization byinterconnection, implementability of system behaviors, synthesis of dissipative systems; robuststabilization, model reduction and approximation in a behavioral context; network dynamics;control and model reduction of multi-agent systems.

A.J. van der Schaft}: Geometric network modeling, analysis and control of complex engineeringand hybrid systems; nonlinear systems and control theory; network dynamics; modeling andanalysis of chemical reaction networks and power systems, and coordination control of physicalsystems.

E.Vos (co-supervision J.M.A. Scherpen, ITM): Coordination control of robotic sensor networks.

J. Wei: Analysis and control of distribution networks.

S. Zhang (co-supervision M. Cao, ITM): Controllability of leader-follower multi-agent systems.

F. Zhang (co-supervision J.M.A. Scherpen, ITM): Robust synchronization and formation controlof nonlinear multi-agent systems.

Publications

Other publications

The master student Hidde-Jan Jongsma (supervised by H.L. Trentelman and M.K. Camlibelhas been awarded a grant in the NWO-DISC honeurs program for a four year PhD positionin the research group Systems Control & Applied Analysis, starting in 2013.

Publications

Book chapters/parts

H.L. Trentelman, “Behavioral methods in control”, In Williams S. Levine, editor, The ControlHandbook, CRC Press, Taylor and Francis, Boca Raton, FL, 2011, 5-58 – 5-81,.



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R.V. Polyuga, A.J. van der Schaft, “Structure perserving port-Hamiltonian model reduction ofelectrical circuits”, Chapter 14 in P. Benner et al. (eds.), Model Reduction for CircuitSimulation, Lecture Notes in Electrical Engineering, 74, Springer Science+BusinessMedia B.V., 2011, 242–260.


A.J. van der Schaft, P. Rapisarda, State maps from integration by parts, SIAM J. Control andOptimization, 49 (6), 2011, 2415 - 2439.

D. Napp Avelli and H.L. Trentelman, Linear-quadratic control and quadratic differential formsfor multidimensional behaviors, Linear Algebra and its Applications, 434 (1), 2011, 117- -130.

E. de Klerk and C. Dobre, A comparison of lower bounds for the Symmetric Circulant TravelingSalesman Problem, Discrete Applied Mathematics, 159(16), 2011, 1815–1826.

E. de Klerk, C. Dobre, and D. Pasechnik, Numerical block diagonalization of matrix *-algebraswith application to semi definite programming, Mathematical Programming B, 129(1),2011, 91–111.

H. Vinjamoor, A.J. van der Schaft, The achievable dynamics via control by interconnection,IEEE Transactions on Automatic Control, 56(5), 2011, 1110–1117.

H.Vinjamoor, A.J. van der Schaft, What can the canonical controller in principle tell us?, Systems& Control Letters, 60, 2011, 644–649.

H.L.Trentelman, A behavioral characterization of the positive real and bounded real characteristicvalues in balancing, Systems & Control Letters, 60, 2011, 7 – 14.

H.L. Trentelman, S. Fiaz and K. Takaba, Optimal robust stabilization and dissipativity synthesisby behavioral interconnection, SIAM J. Control and Optimization, 49 (1), 2011, 288 - 314.

J. Zilinskas and M. Dür, Depth-first Simplicial Partition for Copositivity Detection, with anApplication to MaxClique, Optimization Methods and Software, 26, 2011, 499–510.

L.Q. Thuan and M.K. Camlibel, Continuous piecewise affine dynamical systems do not exhibitZeno behavior, IEEE Trans. on Automatic Control, 56(8), 2011, 1932–1936.

N. Monshizadeh-Naini, A. Fatehi, A. Kahki-Sedigh, Descriptive vector, relative error matrix, andinteraction analysis of multivariable plants, Automatica, 47 (1), 2011, 108–114.

P. Rapisarda and H.L.Trentelman, Identification and data-driven model reduction of state-spacerepresentations of lossless and dissipative systems from noise-free data, Automatica,47, 2011, 1721 – 1728.

P.J.C. Dickinson, Geometry of the Copositive and Completely Positive Cones, J. MathematicalAnalysis and Applications, 380(1), 2011, 377–395.

R. Polyuga, A.J. van der Schaft, Structure preserving moment matching for port-Hamiltoniansystems: Arnoldi and Lanczos, IEEE Transactions on Automatic Control, 56(6), 2011,1458–1462.

R.V. Polyuga, A.J. van der Schaft, Effort- and flow-constraint reduction methods for structurepreserving model reduction of port-Hamiltonian systems, Systems & Control Letters,61(3), 2011, 412–421.

S. Fiaz, K. Takaba and H.L. Trentelman, Tracking and regulation in the behavioral framework,Automatica, 47 (11), 2011, 2343 – 2345.

S.V. Gottimukkala, S. Fiaz and H.L. Trentelman, Equivalence of rational representations ofbehaviors, Systems & Control Letters, 60, 2011, 119 - 127.

W.P.M.H. Heemels, M.K. Camlibel, J.M. Schumacher, and B. Brogliato, Observer-based controlof linear complementarity systems, Int. J. Robust and Nonlinear Control, 21(10), 2011,1193–1218.


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A.J. van der Schaft, On the relation between port-Hamiltonian and gradient systems, Preprintsof the 18th IFAC World Congress, Milano (Italy) August 28 - September 2, 2011,3321–3320.

A.J. van der Schaft, P. Rapisarda, From external to internal system decompositions, Preprintsof the 18th IFAC World Congress, Milano (Italy) August 28 - September 2, 2011,3316–3320.

A.J. van der Schaft, Positive feedback interconnection of Hamiltonian systems, 50th IEEE Conf.Decision and Control and European Control Conf. (CDC-ECC), Orlando, FL, USA,December 12-15, 2011, 6510–6515.

F. Kerber, A.J. van der Schaft, Compositional properties of passivity, 50th IEEE Conf. Decisionand Control and European Control Conference (CDC-ECC), Orlando, FL, USA, December12-15, 2011, 4628–4633.

F. Kerber, A.J. van der Schaft, Decentralized control using compositional analysistechniques,50th IEEE Conf. Decision and Control and European Control Conf. (CDC-ECC),Orlando, FL, USA, December 12-15, 2011, 2699–2704.

J.M.A. Scherpen, A.J. van der Schaft, Balanced model reduction of gradient systems, Preprintsof the 18th IFAC World Congress, Milano (Italy) August 28 - September 2, 2011,12745–12750.

N. Monshizadeh, H.L. Trentelman and M.K. Camlibel, Simultaneous balancing and modelreduction of switched linear systems, 50th IEEE Conf. Decision and Control and EuropeanControl Conf. (CDC-ECC), Orlando, USA, 2011, 6552–6557.

S. Zhang, M.K. Camlibel, and M. Cao, Controllability of diffusively-coupled multi-agent systemswith general and distance regular coupling topologies, 50th IEEE Conf. Decision andControl and European Control Conf. (CDC-ECC), Orlando, FL, USA, 2011, 759–764.

Ph.D. theses

Florian Kerber, Compositional analysis and control of dynamical systems, March 11, 2011,Promotor Prof. A.J. van der Schaft, Faculty of Mathematics and Natural Sciences,University of Groningen.

Harsh Vinjamoor, Achievability of linear systems up to bisimulation, July 8, 2011, PromotorProf. A.J. van der Schaft, Faculty of Mathematics and Natural Sciences, University ofGroningen.

Other publications

A.J. van der Schaft: Editor-at-Large for the journal European Journal of Control, AssociateEditor for the journal Systems \& Control Letters, Associate Editor for the journal Journalof Geometric Mechanics.

H.L.Trentelman: Associate Editor for the journal Systems and Control Letters, Associate Editorfor the journal IEEE Transactions on Automatic Control.

M.K. Camlibel: Subject Editor for the journal International Journal of Robust and NonlinearControl, Member of the Conference Editorial Board for the IEEE Conference on Decisionand Control, Member of the Conference Editorial Board for the American ControlConference, Conference Associate Editor for the IEEE Conference on Decision andControl, Conference Associate Editor for the American Control Conference, Member ofthe National Organizing Committee for the IFAC Conference on Analysis and Design ofHybrid Systems, Member of the International Program Committee for the 12th EuropeanControl Conference.



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Mirjam Dür: Member of the Editorial Board of the journal Optimization Methods and Software,Member of the Editorial Board of the journal Mathematical Methods of OperationsResearch, Member of the Editorial Board of the journal Journal of Global Optimization.


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Tilburg UniversityFaculty of Economics and Business AdministrationDepartment of Econometrics and Operations Research

General Information

AddressTilburg University, Department of Econometrics and Operations Research (K527), P.O. Box90153, 5000 LE Tilburg. Phone (secretary): 013–4662340. Fax: 013–4663280. E–mail:[email protected]

Scientific staffdr. J.C. Engwerda, prof.dr. J.M. Schumacher.

Cooperation withTechnical University Eindhoven, University of Groningen, University of Twente, CentralPlanning Bureau (The Hague),

University of Antwerp, University of La Sapienza Rome, INRIA,

Oxford University, University of Warsaw, Hasselt University, Gadjah Mada UniversityYogyakarta, GERAD Montreal.

Keywordsrobust control design, optimal control, time–varying systems, hierarchical systems, hybridsystems, nonsmooth dynamics, dynamic game theory, coalition formation, macroeconomicpolicy design and European monetary union, portfolio selection, risk management, financialmathematics

Brief descriptionThe aim of the project is to develop system–theoretic methods for control and identificationin economics and finance. The participants also take part in the Center for EconomicResearch of Tilburg University.

DISC projects

System Theoretic Methods in Economics

J.M. Schumacher, J.C. EngwerdaProjectleader:Netspar, Insentif Riset Dasar (Indonesia)Sponsored by:

DescriptionVarious problems arising in economics and finance are analyzed using system–theoreticmethods. The aim is to achieve a better insight into these problems and to find rules foroptimal economic behaviour and risk management.

Subprojects and participants:

a) The interaction of monetary and fiscal policy within EMU (J.C. Engwerda, J.E.J. Plasmans)

b) Nonsmooth dynamics and complementarity (J.M. Schumacher)

Tilburg UniversityFaculty of Economics and Business Administration Department of Econometrics and Operations Research

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c) Risk measurement and control (J.C. Engwerda, J.M. Schumacher)

d) Dynamic game theory (J.C. Engwerda, J.M. Schumacher, P.V. Reddy)

e) Open-loop LQ Game Descriptor Systems and Application on Monetary Cooperation inASEAN (J.C. Engwerda, J.M. Schumacher; joint project with Gadjah Mada University)

Ongoing workThe interaction of monetary and fiscal policy within EMU

The transmission and interaction of national fiscal policies and monetary policy of theEuropean Central Bank in the European Monetary Union are analysed using a dynamicgames approach. A special focus is on how coalitions among fiscal and monetary authoritiesare formed and on the effects these coalitions have on the stabilization of output and prices.In particular, the consequences for these issues are studied of different institutional contextsin which policy makers may act.

Risk measurement and control

For corporations as well as for public institutions, monitoring of financial risk is essential.Risk control must be based on appropriate indicators which need to be constructed, andshould consist of appropriate actions of risk mitigation by means of buffers and/or dynamichedging policies. Financial institutions are subject to increased regulation, which calls for asuitable collection of risk measures. Mitigation of risk by sharing is important in collectivessuch as pension funds. Design of risk sharing systems should be undertaken with dueattention towards the interests of all stakeholders involved.

Nonsmooth dynamics and complementarityThis research project is concerned with nonsmooth dynamical systems. Such systems occurfrequently both in engineering and in optimization. Methods from system theory can beapplied to study issues such as existence and uniqueness of solutions, controllability, andstabilizability.

Analysis of Dynamic Games

This project involves the development of system theoretic tools to analyse dynamic games.In particular games within a linear quadratic setting are studied.

Publications

Books

Bernhard, P., Engwerda, J.C., Roorda, B., Schumacher, J.M., Kolokoltsov, V., Saint-Pierre, P.,and Aubin, J.-P., 2013. The Interval Market Model in Mathematical Finance.Game-Theoretic Methods, Birkhäuser, Boston.


J. Engwerda, O. Boldea, T. Michalak, J. Plasmans and Salmah, 2012. A simulation study ofan ASEAN Monetary Union. Economic Modelling 29, pp. 1870-1890. DOI information:10.1016/j.econmod.2012.05.032

J.C. Engwerda and Salmah, 2012. Feedback Nash equilibria for linear quadratic descriptordifferential games. Automatica 48, pp. 625-631 DOI information:10.1016/j.automatica.2012.01.004


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J.C. Engwerda, 2012. Open-Loop Nash Equilibria in the Non-cooperative Infinite-planningHorizon LQ Game. Proceedings of the 15th IFAC Workshop on Control Applications ofOptimization, University of Bologna, Rimini, Italy Sep.13-16, 2012. CD-Rom. Also availableat IFAC-PapersOnline: http://www.ifac-papersonline.net/

Other publications

J.C. Engwerda, 2012.Open-Loop Nash Equilibria in the Non-cooperative Infinite-planningHorizon LQ Game.CentER Discussion Paper Series No. 2012-052, also available athttp://www.tilburguniversity.edu/research/institutes-and-research-groups/center/pub/dp2012.html

J.C. Engwerda, 2012.Prospects of Tools from Differential Games in the study of macroeconomicsof climate changeCentER Discussion Paper Series No. 2012-045, also available athttp://www.tilburguniversity.edu/research/institutes-and-research-groups/center/pub/dp2012.html

J.C. Engwerda, B. van Aarle, J. Plasmans, A. Weeren, 2012.Debt stabilization games in thepresence of risk premia.CentER Discussion Paper Series No. 2012-056, also availableathttp://www.tilburguniversity.edu/research/institutes-and-research-groups/center/pub/dp2012.html

P.V. Reddy, J. M. Schumacher and J.C. Engwerda, 2012.Optimal Management and DifferentialGames in the Presence of Threshold Effects - The Shallow Lake Model.CentER DiscussionPaper Series No. 2012-001, also available at http://ssrn.com/abstract=1978802

R. Dai, J.C. Rodríguez, and J.M. Schumacher, 2012. Benefit Provision in a Cyclic Economy.Netspar Discussion Paper 03/2012-006.


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Wageningen Universiteit.Departement Agrotechnologie en Voedingswetenschappen,leerstoelgroep Biomass Refinery & Process Dynamics

General Information

AddressWageningen University, Systems and Control Group, Bornse Weilanden 9, 6708 WGWageningen, The Netherlands. Phone: 0317 - 484955 / 482124. Fax: 0317 - 484957. E-mail:[email protected]

Scientific staffDr.ir. A.J.B. van Boxtel, Dr.ir. K.J. Keesman, Dr.ing. R.J.C. van Ooteghem MSc., Prof.Em.dr.ir.G. van Straten, Dr.ir. L.G. van Willigenburg.

Technical and administrative staffIng. C.J. van Asselt, M.G. Portengen.

PhD studentsE.Y.A. Amankwah, J.C. Atuonwu MSc, ir. H.J. Cappon, ir. X. Jin, N. Khairudin MSc.,R.Khiewijit MSc., ir. J.B.M. Klok, J. Omony MSc., ir. P.M. Slegers, C.M. Agudelo Vera MSc.,M. Sampaio MSc.

Cooperation withKU Leuven, Heverlee (B); University of Hohenheim, Tropical Farm Technology (D); Schoolof Applied Sciences, Cranfield University (UK), Centro de Estudos Florestais, InstitutoSuperior de Agronomia,Universidade Técnica de Lisboa, 5 INRA, Montpellier (F), BogorUniversity, Bogor (Indonesia); Diponegoro University, Semaring (Indonesia); IIASA, Laxenburg(A); ICAM (Integrated Catchment Assessment ans Management Centre), ANU, Cranberra(Australia);Applikon, Schiedam; Plant Sciences Group, Wageningen; Food and Biobased Research,Wageningen (v/h IMAG/ATO); Business Unit Glastuinbouw, Bleiswijk; UNESCO-IHE Delft;Univ. Twente, Systems, Signals and Control group; Univ. Twente, Tissue Regeneration;Hogeschool Zeeland; KWR, Nieuwegein; Vitens; PRIVA Hortimation, De Lier; Hortimax,Pijnacker; Witteveen + Bos, Deventer; Wetsus, Leeuwarden; Ebbens Engineering, Lochem;Unilever; Friesland Campina; Agentschap NL; Shell Global Solutions International.

KeywordsEnvironment, climate control, food processing, agriculture, greenhouses, modelling,identification, systems theory, control system synthesis, optimal control, neural networks,fuzzy control.

Brief descriptionThe transition from the Chair for Systems and Control (SCO) to the chair for Biomass Refinery& Process Dynamics started in 2012. Besides administrative issues, we defined a newresearch programme.The organisation of product routings and efficient recovery of resources,the interaction of decentralized processing systems nearby farms, and water and energyrecovery in urban systems are new main topics. Some of the on-going projects fitted well inthe new task, while research areas as indoor climate control and mechatronics are being

Wageningen Universiteit.Departement Agrotechnologie en Voedingswetenschappen, leerstoelgroep Biomass Refinery & Process Dynamics

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closed. The design of a BSc-course on biorefinery, together with other chair groups, is alsoan important step towards our new task.

The new applications are subject to dynamic environments. Input of resources as solarradiation, variability of the properties of the feed, seasonal production peaks and varyingdemand of products request for systems with a wide range of operational conditions, a highdegree of flexibility, and robustness. These demands raise new questions which can beapproached with the available expertise as modelling, learning from the data, analysis ofthe dynamic properties, optimization etc. We search now for additional expertise to startwith the definition of research theme on biomass refinery.

This annual report illustrates the research activities during 2012. If you would like moreinformation about our education and other activities, please consult our websitehttp://www.wageningenur.nl/en/Expertise-Services/Chair-groups/Agrotechnology-and-Food-Sciences/Biorefinery-and-Process-Dynamics-Group.htm

Activities of Biomass Refinery and Process Dynamics

The Biomass Refinery and Process Dynamics Group develops and optimizes methods forprocessing, pretreatment and refining of raw biomass prior to conversion towards food, feed,fuel and materials. The group also works on the dynamics in the processing systems andon methods to monitor, design, operate, control and automate these systems.

The activities of the Biomass Refinery & Process Dynamics Group concern:• Biorefinery. Development and optimization of systems that separate biomass

components produced by plants and organisms and from residue streams. Thesecomponents are used as building blocks for products in the biobased economy.

• Integrated systems. Analysis and design of sustainable processes having a reducedfootprint and closed cycles for components whenever possible.

• Dynamics and control. To exploit and to manage the dynamic environment of biomassprocessing systems, to use the dynamic properties of processing systems for systemmonitoring, and to control for flexible, consistent and high performance processing.

The approach of BRD is based on modelling, technological experiments, advanced designmethods, optimization and control.

DISC projects

Systems and Control Applications in Agriculture

L.G. van WilligenburgProjectleader:L.G. van WilligenburgParticipants:

DescriptionThe aim of this project is to study the applicability of systems and control theory in agriculturalengineering and related fields. Major topics are robust control, optimal control, non-linearidentification (AI), and modelling, with an emphasis on agricultural engineering applications.

This project also serves to initiate possible new PhD projects.

Ongoing workThis is reported in the separate project description under:

• Optimal Digital Control (van Willigenburg)


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Optimal Digital Control

L.G. van WilligenburgProjectleader:L.G. van WilligenburgParticipants:

DescriptionThis project is the current realization of a project with a wider scope that includes digitaloptimal control, reduced-order control, adaptive control and model predictive control (recedinghorizon control).The application areas are indoor climate control (greenhouses and stables),robot control, automatic guidance of agricultural field machines and the control of processesin the food industry (sterilization, drying). The aim of this project is to develop generalmethodologies for the synthesis of optimal digital controllers for non-linear systems.

Ongoing workThe aim of this project is to develop general methodologies for the synthesis of optimaldigital controllers for non-linear systems.

Our recent research concerning optimal reduced-order LQG controller synthesis for nonlinearsystems tracking optimal trajectories triggered a reinvestigation of the controllability,reachability, observability and reconstructability of time-varying linear systems in bothcontinuous and discrete-time. This led to the development of the differential Kalmandecomposition in continuous-time and the j-step, k-step Kalman decomposition indiscrete-time. These decompositions reveal and establish the temporal changes ofreachability/controllability and observability/reconstructability. The linearised system aboutoptimal trajectories may be temporarily uncontrollable and/or temporarily unreconstructable.During these periods the LQG compensator is partly ineffective. This may lead to closedloop instability. To establish the latter temporal stability, temporal stabilizability and temporaldetectability are new key system properties. One-step stabilizability and one-step detectabilityare the discrete-time counter parts of differential stabilizability and differential detectability.The continuous-time results have recently been published online in Optimal ControlApplications & Methods.The discrete-time results have been published on-line in IET ControlTheory and Applications. Currently the extension of these properties to time-varying linearsystems with white stochastic parameters is under investigation. They are of practicalimportance for robust output perturbation feedback design.

Using the delta operator the system property compensatability, that determines whether asystem with white stochastic parameters can be stabilized means of dynamic output feedback,was carried over to continuous-time where it is new. Also the associated numerical testsand measures to verify this property were carried over. This enabled a complete unificationof full and reduced-order LQG controller synthesis for systems with deterministic and whitestochastic parameters in both continuous and discrete time. The result was published in theInternational Journal of Control. Currently the possible use of the delta operator to computetemporal compensatability properties of continuous and discrete-time systems with whitestochastic parameters is being studied.

U-D factorization of LQG controller algorithms enhances their numerical efficiency andstability. Currently we investigate the possibility of U-D factorization of similar algorithms forsystems with white stochastic parameters. An initial result shows that full-order compensatoralgorithms can be U-D factorized. An interesting by-product concerns the minimalrepresentation of matrix valued white stochastic processes. A paper describing these hasbeen published. Reduced-order compensator algorithms are currently studied as well as


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alternative algorithms based on Lyapunov equations instead of the conventional generalizedRiccati and strengthened optimal projection equations.

Optimal control and LQG compensation require a reasonably well established dynamicsystems model. If such a model is not (yet) obtained, active adaptive optimal controllersform an attractive alternative. At present an active adaptive controller structure is underinvestigation through its application to benchmarks.The controller structure aims at enablinga cheap, fast and smooth transition from standard to advanced (multivariable optimal) digitalfeedback control within industrial environments.

Process Control in Food and Bio Process Technology

A.J.B. van BoxtelProjectleader:A.J.B. van Boxtel, G. van StratenParticipants:

DescriptionAt present, in the food processing and biotechnology industries mostly traditional controlmethods are being applied. However, these methods are limited in their abilities to realizethe increasing demands on product quality, and efficiency and flexibility of the production.As a consequence the significance of high performance process control methods grows.The objective of the project is the development and application of high performance controlmethods and strategies for food processing and bioprocess technology with the aim to (i)improve product quality, (ii) realize flexible operations, (iii) raise process efficiency.


Ongoing workThe following topics are described as separate projects below:

• Modelling and control of food and biochemical processes (Amankwah, van Boxtel,van Straten) and Eu-café: computer aided food engineering (van Willigenburg)

• Energy efficient adsorption drying of healthy food (Atuonwu, Jin, van Boxtel)• Scenario studies for biodiesel production with algae (Slegers, van Boxtel)• GeneNet: System dynamic analysis of gene networks in fungal systems(Omony, van

Boxtel)

Modelling and Control of Food and Biotechnological Processes

A.J.B. van BoxtelProjectleader:A.J.B. van Boxtel, G. van Straten, L.G. van Willigenburg, R.J.C. vanOoteghem.

Participants:

E.Y.A. AmankwahPhD students:WUF – Wageningen UniversitySponsored by:

DescriptionThe project aims at exploring novel ways for modelling and control of biotechnologicalprocesses, or at exploring the applicability of methods known from other areas.

Ongoing workSolar adsorption drying

The overview on zeolite drying written together with TNO for the book series “Modern DryingTechnology” part 4 “Energy”, edited by Tsotsas and Mujumdar is published in 2012. Moreover


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a publication is written with a former PhD, who is now a researcher in Indonesia on thedrying of carrageenan using zeolite.

A new project started on solar adsorption drying systems. This project is a sandwich PhDfor E. Amankwah at KNUST in Kumasi Ghana. The aim of this project is to dehumidify airwith adsorbents before drying of yam. With a good strategy, drying can be continued duringthe night, while the adsorbent is regenerated during daytime when excess solar energy isavailable. This systems is called “solar adsorption dryer system” (SADS).

In 2012 the experimental program for this system started. Initially, the performance of thesystem was below expectation due to heat losses in the pipes and the size of the dryingcabins. By changing the dimensions and piping and position of the solar collectors theperformance increased. Next experiments were started to dry yam particles. Parallel to theSADS experiments the same products were dried in a solar dryer (only during day time) andby open sun drying.The SADS dryer was beneficial in its total drying time.The dried productsare now analysed with respect to the functional properties.

Parallel to the drying experiments at KNUST in Ghana, the drying properties (sorptionisotherms, drying kinetics and shrinkage) of yam were measured under controlled conditionsat the laboratories in Wageningen. The data is now subject for analysis. As a first result,variation of the drying rate constant in the initial phase of drying was observed from recursiveparameter estimation. It shows that the interaction between water and the food matrix isrelated to the water content.

Modelling alternative method for small scale sugar processingIn the Netherlands sugar beets are processed in two large factories. The cost fortransportation of the beets towards these centralized locations and the transport of byproductsback to the farm or other users takes now half of the processing costs. As an alternative,sugar beets can be pre-processed at the farm which reduces the transport volume and costs.

The ideas for this alternative approach are developed by the chair group BCH (BiobasedCommodity Chemicals). In 2011 BRD and BCH together developed a model for the processingsystem on the farm. The processing system on the farm includes the alternative sugarprocessing system, anaerobic fermentation for biogas generation, recovery of energy andby products and local energy generation. While setting-up the model we found a number oflimitations in the process system. In 2012 we worked on a system redesign with emphasison the performance and technical feasibility of the sugar processing unit. Significantimprovements have been proposed. Moreover, an analysis is made on the reduction oftransportation costs for central vs decentral processing. It was shown that the transportationcosts can be reduced till only 20-30% of the current level. With this result the perspectivefor decentral processing increases.

Optimizing membrane filtration of food productsThe WUR research institute FBR (Food and Biobased Research) participates in the EU-projectEU-cafe (computer aided food engineering). In 2011 SCO obtained participation in thisproject on optimal control. Our task in the project is to develop an adaptive optimal strategyfor control membrane fouling that occurs during separation of food products.

The objective was to design, simulate and experimentally validate what may be gained froman adaptive optimal control approach as compared to conventional control. Adaptive optimalcontrol relies on a dynamic model of the beer membrane filtration process and an objectivefunction reflecting quantitatively the control objectives.The dynamic model assumes a radialsymmetric membrane and filter and therefore is spatially distributed in one dimension, alongthe main axis of the membrane and filter. Several optimal control policies have been


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investigated. The most advanced one considers optimal variable flow patterns during eachfiltration phase. Optimal control computations and simulations indicate potential reductionof filtration costs up to 20%. Validation results show improvements, some of which exceedthis percentage. So one major conclusion is that adaptive optimal control is technicallyfeasible and realised showing up and over 20% reduction in costs. Another major conclusionis that further improvements and reliability demand for sensor development to measurefouling of beer at different locations. The developments and results obtained with adaptiveoptimal control will be published in a control journal. Some preliminary results have alreadybeen published by project partners.

Energy efficient adsorption drying of healthy food

A.J.B. van BoxtelProjectleader:A.J.B. van Boxtel, G. van StratenParticipants:J.C. Atuonwu, X. JinPhD students:Agentschap NLSponsored by:

DescriptionIn 2009 a new drying project, granted by Agentschap NL, was started.This project concernslow temperature adsorption drying, i.e. in the range 10-50°C where conventional dryers haveonly an energy efficiency of 10-25%. The project focuses on drying of food products withcomponents that have a positive effect on health. We look especially for drying of cabbageslike broccoli which contain glucosinolates. If these glucosinolates are well activated duringdrying they can contribute to the prevention of intestine cancer.

In total 3 PhD-students started with their work in 2009. The subprojects concern 1) kineticsof activation and deactivation of glucosinolates, 2) drying strategies to maintain bioactiveglucosinolates, 3) dryer development and control. Subproject 2 and 3 are carried out by theSystems and Control Group, subproject 1 by the chair group Product Design and Quality.

Ongoing workDrying strategies to maintain bioactive glucosinolates (X.Jin)

A spatially distributed model for the drying behavior of pieces of broccoli is derived andprogrammed in the program of Comsol Multiphysics. In this model three elements arecombined:

• Moisture transport in the particles is based on diffusion, but instead of the standardArrhenius expression for the diffusion coefficient, the free volume theory is used.Thistheory is based on physical properties of the product. As such, it takes the effect ofproduct changes on the mobility of water during drying into account. For example, theglass transition parameters of the polymeric chains in the product are involved.

• For the broccoli model two parts are considered 1) the highly porous hemisphericalfloret and 2) the cylindrical stalk. In order to deal with the porous structure of theproduct (especially the floret), the free volume theory is combined with a multi-phasemodel for diffusion in porous media (Maxwell-Eucken theory).

• The model includes the shrinkage phenomena as well.

The free volume theory can also be applied in the estimation of sorption isotherm. The freevolume theory is a composition based theory, based on the composition data, sorptioncharacteristics can be predicted. Experimental data have shown that for broccoli, differentparts have different ratio of composition, and it also can be influenced by differentpre-treatments. Therefore, the influence of pre-treatments (e.g. drying and blanching) onsorption characteristics were investigated for different parts of broccoli as well.


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With traditional experiments the model for the internal moisture distribution can only bevalidated by destructive methods. As an alternative, magnetic resonance imaging (MRI) isused to validate the model for the internal moisture distribution during drying.With continuousand controlled hot air supply, moisture transport during drying is recorded.

During the MRI measurements, it was found that for the drying of fresh broccoli stalks, themoisture content in the core of the product increased half way the drying time. Additionalexperiments showed that the skin of the product blocked the mass transfer and the watermolecules needed a longer time to diffuse from the core to the surface. Pretreatments, suchas peeling, blanching and freezing, affect this problem and reduce the drying time.

Furthermore, the drying model is tuned according to these experimental results. As someof the kinetic data have been collected, drying optimization strategy has been setup. Tocombine retention of bioactive compounds in combination with high energy efficiency, optimaldrying trajectories are calculated for the control variables air flow rate and temperature. Fordrying of broccoli the considered bioactive compounds are vitamin C and glucosinolates.Optimal drying trajectories plotted in state diagrams with degradation and drying rates,explain the calculated drying strategies. The drying strategies allow for halving the energyconsumption and a significant increase of vitamin C content.

Dryer development and control (J.C. Atuonwu)

In adsorption drying air is dehumidified by using an adsorbent. Regeneration of the adsorbentcan be done under favorable conditions which allow recovery of heat which is not possibleunder standard drying conditions.With the heat recovery, energy efficiency of low temperaturedrying is significantly enhanced. The concept of adsorption drying is under continuousdevelopment.

Mathematical models of the adsorption drying system components, namely, the adsorber(A),regenerator (R), dryer and heat recovery devices have been developed and linked to forman integrated system. These models have been applied in an optimization scheme thatoptimizes energy performance under constrained temperatures and moisture contents ofselected food products using their drying kinetic and equilibria models. The constraints areindicative of desired product qualities. In the scheme, two optimization approaches areconsidered: sequential and simultaneous. In the sequential approach, the zeolite adsorptiondryer is optimized for energy efficiency, subject to product temperature and final moistureconstraints using the zeolite, drying and regeneration air flowrates as well as the regenerationair inlet temperature as decision variables. Heat is then optimally recovered from the processexhaust streams using pinch analysis. In the simultaneous method, heat recovery isconsidered an integral part of the drying process and the entire system simultaneouslyoptimized. Since the heat recovery stream properties are now unknown a priori, the pinchpoint is not unique but determined by optimization.The sequential and simultaneous methodsreduce energy consumption by about 45% and 55% respectively, compared to a conventionalconvective dryer at the same drying temperature of 50°C.

Also, a superstructure model of a multistage adsorption dryer with different adsorbent choicepossibilities per stage is developed and the associated mixed integer nonlinear optimizationproblem solved for maximum energy efficiency. For a two-stage case where the search-spaceof adsorbents is limited to zeolite, silica-gel and alumina, results show that with heat recovery,a hybrid system with zeolite in the first stage and silica gel in the second stage of a two-stagesystem reduces energy consumption by about 60% relative to a conventional two-stagedryer at the same drying temperatures.


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Controllability studies on the adsorption drying system show additional degrees of freedomfor controlling moisture content and temperature compared to the conventional dryer.Theseinclude the regeneration air flowrate, temperature and the zeolite flow speed. These extradegrees of freedom allow for more flexibility of dryer control. Furthermore, energy performanceresilience to unfavourable disturbances is improved. A relationship is established betweenelements of the dryer process gain matrix (sensitivities of product moisture and airtemperature to air flowrate step changes) and energy efficiency. It is shown that byincorporating the adsorbent system to dehumidify the drying air before contact with the wetproducts, the energy efficiency improvements achieved is linked to process gain alterationswhich can in turn be manipulated by adsorbent system design and operating conditions.This has controllability implications.

Scenario studies for biodiesel production with algae

A.J.B. van BoxtelProjectleader:A.J.B. van Boxtel, G. van StratenParticipants:P.M. SlegersPhD students:WetsusSponsored by:

DescriptionMicro-algae have high potential for biotechnology and their application for biodiesel productionis hot! Besides the development of new technology and the quest to understand the behaviourof the organism, the success for algae based biodiesel production is also related with theinteraction of the production systems and their environment. To evaluate the interaction ofdifferent production systems and cultivation technology and to find bottlenecks in theapplications a project on scenario studies was started in 2009.

Ongoing workAlgae biomass production is the first step of biodiesel production. Models have beendeveloped for algae biomass production in open raceway ponds (Slegers et al., Unpublishedresults), flat panels (Slegers et al., 2011) and tubular photobioreactors (PBRS) (Slegers etal., in press). This year the model for horizontal tubular PBRs was extended to includevertical tubular PBR designs. Design scenarios were applied to quantify the effect of location,weather conditions, algae species and reactor design on biomass production.

The sensitivity of the results to the inputs was studied. As example, sensitivity analysis wasapplied to the production at the best light path.In this case, productivity is most sensitive tothe growth rate and absorption coefficient. Up to 85% of the variance in productivity can bereduced when accurate values are used for these parameters. A global sensitivity analysiswill be done to indicate which parameters contribute most to the model uncertainties ingeneral.

Most algae downstream processes are developed using general fixed process settings thatare based on heuristic methods. Since algae cultivation is coupled to and interacting withthe downstream processing (DSP) units, we used a systematic and flexible approach toselect the best processing route and the best process conditions for DSP of algae. Weapplied mixed integer non-linear programming (MINLP) to study the DSP network of algaein more detail.The improvement in energy consumption through optimisation is at least 10%and can go up to 35% for routes using centrifugation. The range in improvement is causedby the level of optimisation that was already done in the models.


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The environment and algae production have a strong interaction since resources like waterand carbon dioxide have to be transported to the production plant. Last year an approachhas been developed to assess the supply chain of algae cultivation by combining thecultivation models developed previously with a logistic model developed at IIASA, called“BeWhere”. This model was designed for planning biofuel plants based on wood. Duringthe analysis we discovered limitations of BeWhere for the algae cultivation chain.Therefore,in 2012 a new version of BeWhere was developed, to specifically answer why plants arepositioned in certain regions. In addition to the previous version, this version also gives moreresults that can be used in the analysis to understand the selection of algae plants, forexample transport distances. With the new version it is easier to get insight in the criticalelements in the algae supply chain.

This project is performed as part of the program of Wetsus, centre of excellence forsustainable water technology (www.wetsus.nl).

Project common with Bioprocess Engineering (WU)

GeneNet: System dynamic analysis of gene networks in fungal systems

A.J.B. van BoxtelProjectleader:A.J.B. van BoxtelParticipants:J. OmonyPhD students:graduate school VLAG, IPOP Wageningen UniversitySponsored by:

DescriptionSystems biology is a relatively new field of science aiming at gaining deeper insights intothe functionality of biological systems. This field of study involves computations andsimulations using mathematical, statistical, biological tools to solve real life biologicalproblems. The goals of this project are to improve current techniques and develop newmethodologies to quantify performance of genetic networks identification with respect to:

• efficient identification of quantitative relationships from limited data sets obtained bytranscriptomics.

• the automatic identification of network substructures.• the improvement in genetic network identification by perturbation studies.• developing improved strategies for time course experiments.

Ongoing workThis project involves studies of the dynamics and inference of the XlnR regulon of thefilamentous fungus A. niger. By using a systems biology approach, model structures wereproposed to describe the regulatory mechanisms of the enzymes in this regulon. Theproposed models then formed the basis for computations and simulations. The goals of thisproject were to improve existing techniques and develop methods to quantify the performanceof genetic network identification with respect to: (i) efficient identification of quantitativerelationships from limited data sets obtained by transcriptomics, (ii) the improvement ingenetic network identification by perturbation studies, (iii) assessing the qualitative andquantitative effects of the catabolic repressor protein (CreA) on transcription, (iv) study anyvariations in transcription between the wild type and mutant CreA strain after induction ofthe XlnR regulon with D-xylose, (v) assess for differential expression between enzymes overtime, and (vi) the development of improved strategies for performing for time courseexperiments. Achieving these objectives involves using in silico experiments, followed byvalidation with model using real experimental data.


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Mechanistic models describing the XlnR regulon dynamics were studied (Omony et al. 2011,BMC Systems Biology). With modeling and simulation studies, we derived insight into thechallenge of network reconstruction – particularly for small dimensional biological networks.The modeling enabled identification of variables and parameters that are crucial in determiningthe XlnR system dynamics. Omony et al. 2012 (IEEE/ACM TCBB) looked at the strategiesfor performing time course experiments that lead to enriched data sets and improved networkreconstruction. These strategies involve objective administration of the D-xylose stimulusto the XlnR regulon in a bid to improve the information in the data sets. Sensitivity analysiswas used to classify the influence of the kinetic parameters on the gene expression responsein time.The effects of timing of the second D-xylose pulse, and the magnitude and sequenceof the administered D-xylose were also studied with respect to the information content inthe gene expression data. In conclusion: (i) through strategic experimental designs costscan be significantly reduced by using fewer samples, enriched data sets can be obtainedand the identification of the network kinetic parameters can be improved, (ii) the parameterestimates are improved by using a second inducer pulse instead of merely using a singlepulse. Using the second pulse significantly improved the experimental design. The secondD-xylose pulse should be administered at an effective moment in time – for low inducerconcentrations, (iii) the results show that for time course experiments, the data samplingintervals can be optimized.

The PhD thesis was successfully defended on December 19, 2012.

Identification, Prediction and Control of Environmental Systems

K.J. KeesmanProjectleader:K.J. Keesman, van StratenParticipants:

DescriptionThroughout history water has confronted humanity with some of its greatest challenges.Water is a source of life and a natural resource that sustains our environments and supportslivelihoods – but it is also a source of risk and vulnerability. Nowadays, many people all overthe world experience water related threats, as sea level rise, river floods, droughts, terroristattacks, water-borne diseases, poverty and at a local level, desertification, eutrophication,water pollution, etc. At the same time, new developments, e.g. fast (wireless) communication,fast computation and globalization, can be seen. From both these threats and newdevelopments, integration of system theoretic tools and water-based systems applicationsfor further insight, better operation, planning and design will be aimed for.

Our objective is to use system theory and information & communication technologies fordata acquisition, data analysis, modelling and decision support, to manage, control anddesign water based systems in a sustainable manner for equitable and efficient use of waterfor many different purposes.


Ongoing workThis is reported in the separate project descriptions under:

• Acoustic waves for water disinfection, filtration and purification (Cappon, Keesman)• Development of new bioreactor for a process for biological sulphide oxidation (Klok,

Keesman, Janssen)• Closing cycles in the built environment: Urban Harvest Approach: An urban resource

management approach (Agudelo,Mels, Rijnaarts, Keesman)


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• Optimisation of heavy metals removal producing bioreactors (Sampaio, Lens, Keesman)• Modelling and optimization of Nitrogen (N) transformation in a fertilised flooded rice

paddy field for loss reduction (N. Khairudin, K.J. Keesman and M.P. Zakaria)• Computer–aided design and monitoring of WWTPs towards energy and nutrient

recovery (Khiewwijit, Keesman, Temmink)• Sensorfish (van Straten, Keesman)

Acoustic waves for water disinfection, filtration and purification

K.J. KeesmanProjectleader:K.J. KeesmanParticipants:H.J. CapponPhD students:Hogeschool Zeeland, WetsusSponsored by:

DescriptionThe objective for acoustic purification research is to develop a laboratory scale acousticseparation unit, which is capable of removing suspended solids, particles from 10 up to 500mu, from polluted water by means of ultrasound.

The work incorporates a numerical-experimental approach, using both computer simulationsand testing on experimental data. It consists of the following steps:

1. Modelling of the separator using Matlab and Comsol software

2. Experimental demonstration of separation principles in air and water

3. Scaling and prototype construction

4. Determination of filtration efficiency

5. Control unit for optimal separation strategy

Ongoing workIn 2012 steps 3, 4 and 5 were the main areas of focus.

Scaling and prototype constructionFirst of all an IEEE-UFFC paper was written on modeling the separator cuvette using knownparameters and estimating the unknown remainder and numerical-experimental validation.The paper was accepted in December 2012.

Secondly, many simulations were performed to determine the best starting (initial) designfor numerical system optimization. System simulation involves three sequential steps: flowsimulation, frequency response / acoustic simulation and particle trajectory simulation. Theflow direction, piezo orientation, and flow rate were varied, resulting in a basis design tostart with. The best separation efficiency is obtained when the flow is perpendicular to thepiezo transducer surface, thus flowing towards or away from this surface / wall. This meansthat the flow must be bent within the separator, since the inlet cannot be located where thetransducer is. Moreover, laminar flow is needed inside the cavity, thus with wide separatorcavities this either results in long channels or multiple, parallel channels, the latter requiringsome sort of flow splitting. Lastly, longer pathways will increase the chance of particlesgetting caught in the cavity. This means that multiple passages through the separator cavity(forth and back) may result in better performance.

Then a Design of Experiments (DOE) approach was used to study the influence of separatorcavity width and wall thickness on system performance. Performance is indicated by thedisplacement of particles within the acoustic field: small displacement means good particle


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retention. As particle trajectory modeling takes quite some time and a flow simulation isneeded as input, an alternative performance index was sought for just the acoustic systemoptimization, which can be evaluated independent of the other simulations. It was found thatthe minimum displacement corresponds to the maximum averaged absolute pressure withinthe entire cavity. High average pressure, means small particle displacement, means bestparticle retention.

Control system modelingA master thesis study was performed on system control strategies using BioSep with theaim to obtain improved filtration efficiency through optimal control. Optimal open-loopswitching control was used to obtain the best filtration performance possible using suspendedstarch. The efficiency increased from 92% to 96% using only the control strategy, whileapplying a fixed flow rate. A paper for Purification and Separation Technology was written,accepted and published in December 2012. Future control strategies should also incorporatecontrol of power and flow rate using feedback control.

Full scale dynamics of biological sulfide oxidation

K.J. KeesmanProjectleader:K.J. Keesman, A. JanssenParticipants:J.B.M. KlokPhD students:Shell Global Solutions InternationalSponsored by:

DescriptionIn biological gas desulphurization, H2S-containing gas is absorbed into an alkaline solution.In the sulfur producing bioreactor, the dissolved sulfide is subsequently oxidized into elementalsulfur under oxygen-limited conditions whilst a part is oxidized to sulfate by a mixed populationof sulfide oxidizing bacteria. In addition, non biological sulfide oxidation occurs merely leadingto the formation of thiosulfate. Formation of (thio)sulfate in the sulfur producing bioreactoris unwanted because it reduces the overall process efficiency and leads to an increasedchemical consumption of e.g. ethanol or H2-gas.

Ongoing workProgress 2012

Models have been developed which describe full-scale reactors. A local sensitivity analysis,based on the evaluation of a proposed physiologically based kinetic model, revealed complexparameter interactions between several biological parameters. Furthermore, meta-modelswere derived from the full-scale model, which indicate a non-linear scale up effect. Theobtained meta-model can be used for understanding, scale up and optimization of thebiological desulfurization process.


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Project common with Environmental Technology (WU)

Closing cycles in the built environment: Urban Harvest Approach: An urbanresource management approach

K.J. KeesmanProjectleader:K.J. Keesman, A.R. Mels, H.H.M. Rijnaarts,Participants:M.C. Agudelo VeraPhD students:EU-SwitchSponsored by:

DescriptionAccelerating urbanization, increasing scarcity of resources and climate change force us tore-think and redesign urban systems. In a world of cities, it is needed to understand howurban systems function, and how the urban environment can be managed in a sustainableway. A paradigm shift towards closing cycles, by reusing and recycling of resources isneeded. There are many unexplored potentials to minimize impacts and maximize reuseand recovery of resources within urban areas. This research studies water, energy andnutrient cycles of different urban typologies and defines strategies for improvement of urbancycles to achieve self-sustainable urban areas. The urban harvest approach is beingdeveloped on the concept of urban metabolism.

To achieve sustainability goals, it is crucial to find ways to improve urban cycles in quantitativeand in qualitative terms by analyzing spatial and temporal implications, implementingcascading, recycling and multisourcing. For this calculatory models are being developedwith which urban flows of energy, water and nutrients can be quantified and the sustainabilityof scenarios for urban development and design can be evaluated. Inputs of differentdisciplines are needed herein to make scientifically based concepts and tools for optimalurban resource utilization.


A paper with the theoretical background of the “Urban Harvest Approach” (UHA) has beenpublished. The UHA explores the potential of improving urban resource management bydemand minimization and harvesting of local and renewable resources. UHA works on theprinciple that urban systems and their direct peri-urban surroundings can becomeself-sufficient by applying three strategies, namely: minimizing demand, minimizing outputsand multi-sourcing. The UHA uses three indicators to characterize the Metabolic Profile(MP): Demand Minimization Index, Waste Output Index and Self-sufficient Index. The UHAwas applied to model and evaluate the water management in The Netherlands, three papersshowing the applicability of the UHA at building unit, urban block and city level are inpreparation. Results indicated that water-saving technologies can reduce up to 20% of theconventional demand. Moreover by recycling light grey water from shower, it is possible tofully supply non-potable domestic demand (toilet and laundry demands). Due to variationsin the daily pattern, efficiency is larger for building units with multiple households than forbuilding units with a single household.

The project was successfully finished in 2012.The PhD graduation ceremony took place onJune 20, 2012.


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Project common with Environmental Technology (WU)

Optimisation of heavy metals removal producing bioreactors

K.J. KeesmanProjectleader:K.J. Keesman, P.N.L. LensParticipants:M. SampaioPhD students:EU-Madame CurieSponsored by:

DescriptionHeavy metals are among the most frequent water and soil pollutants in Europe and dischargesinto the environment can lead to devastating effects on aquatic and terrestrial ecosystems.Nevertheless, it is also known that several heavy metals can be beneficial for biotechnologyprocesses and a minimum quantity is required for the well functioning of bioreactors, namelyin anaerobic wastewater treatment systems.

Progress 2012

Writing PhD thesis.

Numerous treatment technologies exist for the removal of heavy metals from natural watersand wastewaters, but most of them produce concentrated sludges that need to be stored incontrolled hazardous waste disposal sites. Moreover, treatment processes should also focuson recovery of the metals as the metal resources are depleting.

Technological Challenge

In industry, by far the most widely used treatment process for wastewater is hydroxideprecipitation. However, it is also well known that precipitation with sulphide has somefundamental advantages like lower effluent concentration and possibility of selectiveprecipitation.

Project common with UNESCO-IHE, Delft

Modelling and optimization of Nitrogen (N) transformation in a fertilisedflooded rice paddy field for loss reduction

K.J. KeesmanProjectleader:K.J. Keesman, M.P. ZakariaParticipants:N. KhairudinPhD students:Universiti Putra Malaysia, Ministry of Higher Education Malaysia (MOHE)Sponsored by:

DescriptionIn Malaysian rice fields, the soil is fertilized with urea between three and five times for eachcropping season. However, not all of the applied N fertilizer will be taken up by rice crop.Our main objective is to model and to estimate N transformations in a flooded rice field forscientific understanding of the key processes and for scenario analyses.

Progress in 2012

From January to May 2012, soilwater and floodwater samples were collected from a paddyplot and from laboratory set-ups. These samples were analysed for mineral N, namelyammonium (NH4

+) and nitrate (NO3-). However, these data were not used for model calibration

because they were not informative. We looked for secondary soil N data in literature, butextensive measurements of soil and floodwater N were not easily available for a flooded


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rice system. Alternatively, an indirect validation technique was aimed for, where othermeasured variables will be used to check the reliability of our model. Furthermore, for anopen-field biological system, as the flooded rice field, we encountered two main challenges:1) the system is complex and many conversion parameters affect the N in the soil, and 2)these parameters are influenced by rate limiting, environmental variables such as weathervariables, soil variables and floodwater variables on an hourly/daily time step. These ratelimiting variables were not described in our model.

As of now, we focused on fine-tuning the model conceptualisation and its parameters inorder to address the first challenge. This is to ensure we give emphasis on significantparameters. Consequently, the number of parameters that will be estimated from experimentaldata will be reduced. For an ill-defined system like this with a limited amount of experimentaldata, parameters can be estimated using a set-membership approach.

Previously, we hypothesized that denitrification contributes to N loss. Denitrification is limitedby amount of NO3

- concentration. However, now we assumed that all NO3- produced within

the rhizosphere is directly taken up by rice crop. Hence, we partially concluded thatdenitrification is not an important pathway for N loss under planted and flooded conditions.This indicates that the accuracy of the model may be less sensitive to nitritification anddenitrification parameters. In our model, the NH4

+ adsorption was described as a correctionterm (fraction) and not modelled as a sink. Such approach slows down NH4

+ dynamics butnot its steady state behaviour. Hence, we adjusted the model by using a first order kineticto describe NO3

- adsorption as a sink. Typically, N crop uptake is included as a major sinkwhile NH4

+ adsorption is completely neglected. However, we assumed that rice crop willuptake NH4

+ from the adsorbed NH4+ pool. In addition, we also included a leaching term in

our model because most secondary data suggested occurrence of NO3 leaching. As of now,we partially concluded that NH3 volatilisation, NH4

+ diffusion and NH4+ adsorption are the

driving parameters in our model, and we will attempt to estimate these parameters. Futurework in 2013 includes parameter estimation using set-membership approach and sensitivityanalyses.

Computer – aided design and monitoring of WWTPs towards energy andnutrient recovery

K.J. KeesmanProjectleader:K.J. Keesman, H. TemminkParticipants:R. KhiewwijitPhD students:WetsusSponsored by:

DescriptionUnder the pressure of rising energy prices, additional treatment steps as anaerobic digestion,have been added to provide valuable energy. However, to make wastewater treatment plant(WWTP) energy positive further research is still needed. In addition to making the WWTPenergy positive, the WWTPs could also be designed and controlled such that nutrientsrecovery such as N and P, reduction of CO2 emission and reuse of treated wastewater arerealized.

The challenge of this study is to (re)design, monitor and control existing and novel WWTPsfor positive energy, cost-effective nutrients recovery, reduction of CO2 emission, and goodquality of the treated water, preferable suitable for reuse. In order to achieve this challenge,the following sub-objectives have been defined:


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• Identify bottlenecks in conventional WWTPs design• Design novel WWTPs layouts, using the latest insights in domestic wastewater

treatment• Design monitoring and control strategies for the realization for the novel WWTPs

layouts• Validate the novel designs by lab-scale and pilot-scale experiments.

Progress 2012

In 2012, sub-objectives 2 and 3 were the main areas of focus. New designs of the futuremunicipal WWTPs were investigated, using the Netherlands as a case. The information of(latest) sustainable treatment and recovery technologies was collected from the literature,and then integrated these technologies to new designs. Numerical modelling techniqueswere used to assess the new designs compared to the conventional activated sludge systems.The potential of these new designs need to: 1) treat municipal wastewater to achievedischarge EU guidelines; 2) operate the whole year through; 3) maximize energy productionand nutrients recovery; and 4) minimize CO2 emissions and energy consumption. Thenumerical results indicate an optimal design out of four new designs for Dutch municipalWWTPs of the future.This optimal design will support the development of municipal WWTPsto achieve positive energy yield, P recovery product, less space requirement, and reduceCO2 emissions. A study has been started on a sensitivity analysis (focused on temperaturesand wastewater characteristics) of this optimal design using a dynamic modelling approach,as this will offer insight in the development of municipal WWTPs in other countries andregions. Next, how each of these parameters affects each process will be investigated inlab-scale experiments that can be compared with modelling results.

Project in collaboration with Environmental Technology (WU)

Sensorfish

K.J. KeesmanProjectleader:G. van StratenParticipants:EUSponsored by:

DescriptionFish farming and aquaculture is the world’s fastest growing sector within the food industry,providing nearly 50 percent of fish consumed globally and creating more than 5 million jobsworldwide. Aquaculture is of growing importance to the European Community given themere fact that the industry employs the local population in many rural areas of severalcountries in Europe. Especially the European fisheries and aquaculture must enhance theircompetitiveness while maintaining the sustainable production of aquaculture and marineresources. The only possible answer is to use highly advanced technologies for fish farmmanagement; to create competitive, sustainable and multifunctional fisheries and aquaculturesystems and to optimize the quality of products along with fish health and welfare.

The advance of climate change, leading to warmer water temperatures, will make themonitoring of the state of the water environment even more important. For cold-water species,such as Atlantic salmon, warmer water means that more energy is consumed for maintainingbasic life functions; hence less energy is available for growth and coping with stress (i.e.farming operations, diseases, poor water environment etc). A continuous and reliable systemfor monitoring the aquatic environment so that the farmer can make informed decisions istherefore essential for the future growth of the industry. Very similar challenges arise inhighly stocked ponds or raceways. Recirculation systems conditions are generally easier to


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control but their success is closely related to the reliable function of monitoring equipment.This underlines the need for continuous and precise monitoring of the aquatic environment,fish behaviour and the functionality of technical equipment, particularly in highly stocked fishfarming facilities.

The overall aim of this programme is networking and increased collaboration between groupsin Europe, China, USA and Canada working on intelligent sensor network and systemtechnologies for fish farming.

Our contribution to the scientific objectives are:• To design smart monitoring strategies using a minimum of hardware sensors and

using soft-sensors to estimate unknown rates and concentration in the recirculationsystem for insight into the dynamics and for advanced (model-based) control.

• To design remote, advanced (model-based) control strategies for safe, energy efficientand economically optimal fish farming.

• To deepen the study of real-world system integration for fish farming. For the realizationof this an intelligent monitoring and control pilot system for fish farming will be realizedand tested in China and Norway. The participation of the European and Americaninstitutions will support the laboratory experiments related to mixing processes.


The kick-off meeting took place in Berlin from 18-19 Feb 2012. The first annual meeting ofthe project was organised by CAU, Bejing, Oct 21, 2012.

Climate and Nutrient Control in Greenhouse Production

G. van StratenProjectleader:G. van Straten,Participants:

DescriptionIndoor climate in agricultural buildings is usually controlled by heuristic control designs. Theobjective of the project is the development of advanced, intelligent control algorithms forgreenhouses and other agricultural buildings in order to achieve better compliance with everincreasing requirements of energy savings, product quality, environmental protection andeconomy.


Ongoing workThis is reported in the separate project description under:

• Optimal Management of Energy Resources in greenhouses – OMER (P.J.M. vanBeveren, J. Bontsema (PRI), E.J. van Henten (FTE), G. van Straten)


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Optimal Management of Energy Resources in greenhouses – OMER

G. van StratenProjectleader:G. van Straten, E. van Henten, J. BontsemaParticipants:P.J.M. van BeverenPhD students:STW Smart Energy ProgrammeSponsored by:

DescriptionThis STW project is part of the Smart Energy Systems programme of STW. In the interestof reducing energy consumption and CO2 emission while maintaining productivity, greenhousegrowers have installed a wide range of auxiliary equipment, such as assimilate lighting, heatexchangers, short and long term heat buffers, co-generation units and heat pumps. Thetask of the grower to manage his equipment in the most economical way has become verycomplicated, not only because of the complex intrinsic physics of the greenhouse dynamics,but also because of the uncertainty in the weather, and, in addition, the strongly fluctuatingmarket prices of energy. The aim of this project is to develop optimal scheduling ormanagement procedures. Scientifically, this can be seen as a non-linear dynamic optimizationproblem with uncertainty in external prices and external influences. While under assumedprices and future weather the problem can – theoretically – be solved off-line by knownnumerical methods, the real challenge is to obtain feasible on-line optimal or near optimaloperation strategies. The project started at the end of 2011, with the appointment of Petervan Beveren MSc as post graduate student. His provisioned promoters are Prof. Eldert vanHenten and Prof. em. Gerrit van Straten, who have been responsible within the universityfor the proposal.The work will be supervised primarily by Jan Bontsema of Wageningen URGreenhouse Horticulture (former SCO staff member). It will be conducted in close cooperationwith Hortimax (dr. Ad de Koning), and an advanced grower.


In the interest of reducing energy consumption and CO2 emission while maintainingproductivity, greenhouse growers have installed a wide range of auxiliary equipment, suchas assimilate lighting, heat exchangers, short and long term heat buffers, co-generationunits and heat pumps. The task of the grower to manage his equipment in the mosteconomical way has become very complicated, not only because of the complex physics ofthe greenhouse dynamics, but also because of the uncertainty in the weather, and, in addition,the strongly fluctuating market prices of energy. The main challenge of this project is toformulate and solve this optimization problem and to develop optimal scheduling ormanagement procedures.

Project in collaboration with Farm Technology (WU) and Wageningen UR GreenhouseHorticulture

Publications

Books

Boxtel, A.J.B. van, Boon, M.A., Deventer, H. van & Bussmann, P.J.T. (2012). Zeolites forreducing drying energy usage. In E. Tsotsas & A.S. Mujumdar (Eds.), Modern DryingTechnology (Energy Savings, 4) (pp. 163-197). Weinhem, Germany: Wiley-VCH VerlagGmbH & Co. KGaA.


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Agudelo, C., Mels, A., Keesman, K.J. & Rijnaarts, H.H.M. (2012).The Urban Harvest Approachas an Aid for Sustainable Urban Resource Planning. Journal of Industrial Ecology, 16(6),839-850.

Atuonwu, J.C., Jin, Xin, Straten, G. van, Deventer, H. van & Boxtel, A.J.B. van (2011). Reducingenergy consumption in food drying: opportunities in desiccant adsorption and otherdehumidification strategies. Procedia Food Science, 1, 1799-1805.

Atuonwu, J.C., Straten, G. van, Deventer, H. van & Boxtel, A.J.B. van (2012). A Mixed IntegerFormulation for Energy- efficient Multistage Adsorption Dryer Design. Drying Technology,30(8), 873-883.

Boels, L., Keesman, K.J. & Witkamp, G.J. (2012). Adsorption of Phosphonate Antiscalant fromReverse Osmosis Membrane Concentrate onto Granular Ferric Hydroxide. EnvironmentalScience and Technology, 46(17), 9638-9645.

Cappon, H.J., Stefanova, L.A. & Keesman, K.J. (2013). Concentration based flow control inacoustic separation of suspensions. Separation and Purification Technology, 103, 321-327.

Djaeni, M., Sasongko, S.B., Prasetyaningrum, Aji A, A.A., Jin, Xin & Boxtel, A.J.B. van (2012).Carrageenan drying with dehumidified air: drying characteristics and product quality.International Journal of Food Engineering, 8(3).

Draaisma, R.B., Wijffels, R.H., Slegers, P.M., Brentner, L.B., Roy, A. & Barbosa, M.J. (2012).Food commodities from microalgae(Online first). Current Opinion in Biotechnology, 24.

Gerdessen, J.C., Slegers, P.M., Souverein, O.W. & Vries, J.H.M. de (2012). Use of OR todesign food frequency questionnaires in nutritional epidemiology. Operations Researchfor Health Care, 1(2/3), 30-33.

Higuera, G.A., Boxtel, A.J.B. van, Blitterswijk, C.A. van & Moroni, L. (2012). The physics oftissue formation with mesenchymal stem cells.Trends in Biotechnology, 30(11), 583-590.

Jin, Xin, Sman, R.G.M. van der, Gerkema, E., Vergeldt, F.J., As, H. van & Boxtel, A.J.B. van(2011). Moisture distribution in broccoli: measurements by MRI hot air drying experiments.Procedia Food Science, 1, 640-646. Graaff, C.M. de,

Keesman, K.J., Norton, J.P., Croke, B.F.W., Newham, L.T.H., Jakeman, A.J. Set-membershipapproach for identification of parameter and prediction uncertainty in power-lawrelationships: the case of sediment yield. Environmental Modelling & Software, 2012.DOI:10.1016/j.envsoft.2012.09.007

Klok, J.B.M., Bijmans, M.F.M., Muyzer, G. & Janssen, A.J.H. (2012). Application of a 2-stepprocess for the biological treatment of sulfidic spent caustics. Water Research, 46(3),723-730.

Omony, J., Mach-Aigner, A.R., Graaff, L.H. de, Straten, G. van & Boxtel, A.J.B. van (2012).Evaluation of Design Strategies for Time Course Experiments in Genetic Networks: CaseStudy of the XlnR Regulon in Aspergillus niger. IEEE/ACM Transactions on ComputationalBiology and Bioinformatics, 9(5), 1316-1325.

Stein, N.E., Hamelers, H.V.M., Straten, G. van & Keesman, K.J. (2012). Effect of ToxicComponents on Microbial Fuel Cell-Polarization Curves and Estimation of the Type ofToxic Inhibition. Biosensors, 2(3), 255-268.

Stein, N.E., Hamelers, H.V.M., Straten, G. van & Keesman, K.J. (2012). On-line detection oftoxic components using a microbial fuel cell-based biosensor. Journal of Process Control,22(9), 1755-1761.

Willigenburg, L.G. van & Koning, W.L. de (2012). Equivalent optimal compensation problem inthe delta domain for systems with white stochastic parameters (Online first). InternationalJournal of Systems Science.


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Willigenburg, L.G. van & Koning, W.L. de (2012). Minimal representation of matrix valued whitestochastic processes and U–D factorisation of algorithms for optimal control (Online first).International Journal of Control.


Djaeni, M. & Boxtel, A.J.B. van (2012). Development of a novel energy-efficient adsorptiondryer with zeolite for food product. In Conference Proceeding of the 2nd InternationalSymposium on Processing and Drying of Foods, Vegetables and Fruits (ISPDFVF 18-19June 2012).

Keesman, K.J. & Walter, E. (2012). Optimal Input Design for Model Discrimination. In Preprintsof the 16th IFAC Symposium on System Identification, Brussels, Belgium, 11-13 July,2012 (pp. 668-673). Brussels: IFAC.

Ph.D. theses

Agudelo Vera, C.M. (2012, June 20). Dynamic water resource management for achievingself-sufficiency of cities of tomorrow. WUR Wageningen UR (208 pag.) ([S.l.]: [s.n.]).Prom./coprom.: Prof dr ir H.H.M. Rijnaarts, Dr ir K.J. Keesman & Dr ir A.R. Mels.

Omony, J. (2012, December 19). The Dynamics of the XInR Regulon of Aspergillus niger: asystems biology approach.WUR Wageningen UR (158 pag.) ([S.l.]: [s.n.]). Prom./coprom.:Prof Emeritus dr ir G. van Straten, ,Dr ir A.J.B. van Boxtel & Dr ir L.H. de Graaff.

M.Sc. theses

Boer, M.M. de, Parameter estimation in sulfur oxidizing reactions. Afstudeervak, BiomassRefinery & Process Dynamics WUR, 2012.

Braak, M.J.C. van den, The effect of temperature on algal growth from both a practical andmodelling point of view. Afstudeervak Biomass Refinery & Process Dynamics, WUR,2012.

Girdhari, R.S.K., Modelling of energy consumption for algae photo bioreactors in variousscenarios. Afstudeervak Biomass Refinery & Process Dynamics, WUR, 2012.

Koetzier, B.J., Optimization of the downstream processing of microalgal biomass to biodiesel.Afstudeervak Biomass Refinery & Process Dynamics, WUR, 2012.

Loperena Lopez, A., Comparing LCA studies for biodiesel from algae and rapeseed.Afstudeervak Biomass Refinery & Process Dynamics, WUR, 2012.

Stefanova, L.A., Concentration based flow control in acoustic separation of suspensions.Afstudeervak Biomass Refinery & Process Dynamics, WUR, 2012.

Voogt, R.J., Optimization of energy and watercycles at block level in Wageningen. AfstudeervakBiomass Refinery & Process Dynamics, WUR, 2012.

Vuist, J.E., Optimizing of cleaning procedures scheduling in beer microfiltration. AfstudeervakBiomass Refinery & Process Dynamics,WUR, 2012.

Zhuang, S., System identification for indoor temperature in an office environment. AfstudeervakBiomass Refinery & Process Dynamics, WUR, 2012.


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