Introduction toIntelligent Control Part 1keffe006/Workshop/ECE4951-Lecture1.pdf · Introduction...

Introduction to Intelligent Control

Part 1

ECE 4951 - Spring 2010

Prof. Marian S. StachowiczLaboratory for Intelligent Systems

ECE Department, University of Minnesota Duluth

January 19 - 21, 2010

Instructors

• INSTRUCTORS: Prof. Marian S. Stachowicz,

• MWAH 273, phone: 218- 726-6531,

• [email protected]

• http://www.d.umn.edu/ece/lis

• TIME/LOCATION: Lectures (first three weeks)

• T, Th, 8:00 – 8:50, MWAH 191

• F 16:00 – 16:50, MWAH 175

•• Laboratories (first three weeks)

• F 14:00 – 15:50, MWAH 293, • F 14:00 – 15:50, MWAH 293,

• 8 hours per week, MWAH 293 (next 10 weeks)

•• OFFICE HOURS: 14:00 - 15:30, T, Th, MWAH 273

••• CONSULTANT: Prof. Christopher Carroll

• MWAH 252, phone: 218 - 726-7530,

• [email protected]

•• OFFICE HOURS: TBA, MWAH 252

•

2Intelligent Control

REFERENCES

• 1. M.S. Stachowicz and L. Beall , Fuzzy Logic Package for Mathematica, Version 5.2, Wolfram Research, Inc., 2003

• 2. R.C. Dorf and R.H. Bishop, Modern Control Systems, 11th Edition, Prentice Hall, 2008, 11th Edition, Prentice Hall, 2008,

• 3. Kasuo Tanaka, An Introduction to Fuzzy Logic for Practical Applications, Springer, 1997

• 4. J. Yen and R. Langari, Fuzzy Logic, Prentice Hall, Inc., 1999

• 5. K.M. Passino and S. Yurkovich, Fuzzy Control, Addison Wesley Longman, Inc., 1998


• 6. D. J. Pack, Steven F. Barrett, The 68HC12 Microcontroller: The theory and Applications, Prentice Hall, 2008

• 7. F. M. Cady, Software and Hardware Engineering, Oxford University Press, Inc.,2008

• 8. H.R. Everett, Sensors for Mobile Robots, A K Peters, 1995• 8. H.R. Everett, Sensors for Mobile Robots, A K Peters, 1995• 9. ECE 4899-4999, ECE 4951 – ECE Senior Design Project

Handbook, ECE Dep. 2009


References for reading

1. R.C. Dorf and R.H. Bishop, Modern Control Systems,

10th Edition, Prentice Hall, 2008,Chapter 1.1 - 1.10

2. J.J. DiStefano, A. R. Stubberud, I. J. Williams, Feeedbackand Control Systems, Schaum's Outline Series, McGraw-Hill, Inc., 1990Chapters 1, 2

Control Systems

Control

• The word control is usually taken to mean :

- regulate,

- direct,- direct,

- command.

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Control system

• A control system is an interconnection of

components forming a system configuration that

will provide a desired system response.will provide a desired system response.


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The Input – Output relationship represent the Cause – Effect relationship

8

Input

• The input is the stimulus, excitation or

command applied to a control system.

• Typically from external energy source,

usually in order to produce a specified

response from the control system.


Output

• The output is the actual response obtained

from a control system.

• It may or may not be equal to specified

response implied by the input.


Two Types of Control Systems

• Open Loop

– No feedback

– Difficult to control

output with accuracy

• Closed Loop

– Must have feedback

– Must have sensor on output

– Almost always negative output with accuracy – Almost always negative

feedback


Open-loop control

An open-loop control system utilizes an actuating

device to control the process directly without using

feedback.

A common example of an open-loop control system

is an electric toaster in the kitchen.


Closed-loop control

A closed-loop control system uses a measurement

of the output and feedback of this signal to

compare it with the desired output.compare it with the desired output.


Manual control system

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Goal: Regulate the level of fluid by adjusting the output valve.

The input is a reference level of fluid and is memorized by operator.The power amplifier is the operator.The sensor is visual.Operator compares the actual level with the desired level and opens or closes the valve ( actuator).

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The level of fluid in a tank control.


Terms and concepts

• Automation - The control of a process by automatic means.

• Closed-loop feedback control system -A system that uses a measurement of the output and A system that uses a measurement of the output and compares it with the desired output.


Design-The process of conceiving or inventing the forms, parts, and details of a system to achieve a specified purpose.

Feedback signal - A measure of the output of the Feedback signal - A measure of the output of the system used for feedback to control the system.

Multivariable control system - A system with more than one input variable or more than one output variable.


Negative feedback -The output signal is fed back so that it subtracts from the input signal.

Open-loop control system - A system that utilizes a Open-loop control system - A system that utilizes a device to control the process without using feedback.

Optimization -The adjustment of the parameters to achieve the most favorable or advantageous design.


Positive feedback -The output signal is fed back so that it adds to the input signal.

Process -The device, plant, or system under control.

Productivity -The ratio of physical output to physical input of an industrial process.


Robot - Programmable computers integrated with a

manipulator.

Synthesis - The combining of separate elements or Synthesis - The combining of separate elements or

devices to form a coherent whole.

System - An interconnection of elements and devices

for a desired purpose.


The Control System Design Process

• Design is the process of conceiving or inventing

the forms, parts, and details of a system to

achieve a specified purpose.

Engineering design

achieve a specified purpose.

• It is the central task of the engineer.

• It is a complex process in which both creativity and analysis play major role.


• Complexity, trade-off, gaps, and risk are inherent in designing new systems and devices.


Trade-off

The result of making a judgment about how

to compromise between conflicting criteria.to compromise between conflicting criteria.


Goals

Twin goals of understanding and controlling are

complementary because effective systems

control requires that the systems be control requires that the systems be

understood and modeled.


Control engineering

Control engineering is based on the foundations

of feedback theory and linear system analysis,

and it integrates the concepts of network theory

and communication theory.and communication theory.


Given a process, how to design a feedback

control system?

Three steps:

• Modeling. Obtain mathematical description of the systems.

• Analysis. Analyze the properties of the system.

• Design. Given a plant, design a controller based on performance specifications.

The course spans each of these steps in that sequence.


The basis for analysis of a system is the

foundation provided by linear system theory,

which assumes a cause-effect relationship for

the components of a system.the components of a system.


Design 1


Design 2


Design 3


The design of control systems is a specific example of engineering design.

The goal of control engineering design is to obtain the configuration, specifications, and

Intelligent Control

obtain the configuration, specifications, and identification of the key parameters of a proposed system to meet an actual need.

36

The design process consists of seven main building blocks, which are arrange into three groups:

1.Establishment of goals and variables to be controlled, and definition of specifications

Intelligent Control

controlled, and definition of specifications against which to measure performance.

1.System definition and modeling.

1.Control system design and integrated system simulation and analysis

37

Design examples

Rotating disk speed control


Step 1. Control goal

• Design a system that will held a rotating disk

at a constant speed. Ensure that the actual speed at a constant speed. Ensure that the actual speed

of rotation is within a specified percentage of

desired speed.


Step 2. Variable to be controlled

• Speed of rotation disc


Step 3. Control design specification

• Design a system that will ensure that

the actual speed of rotation is within a the actual speed of rotation is within a

specified percentage of desired speed.


Step 4. Preliminary system configuration


Step 4 Preliminary system configuration


With precision components, we could expect

to reduce the error of the feedback system toto reduce the error of the feedback system to

one-hundredth of error of the open-loop system.


Insulin delivery system

Step 1. Control goal

• Design a system to regulate the blood sugar

concentration of a diabetic by controlled concentration of a diabetic by controlled

dispensing of insulin.


The blood glucose and insulin concentrations for a healthy person.


Step 2. Variable to be controlled

• Blood glucose concentration


Step 3. Control design specification

• Provide a blood glucose level for the diabetic

that closely approximates the glucose level of

a healthy person.a healthy person.


Step 4 Preliminary system configurations


E 4.1 Tracking the sun

H(s) = 1

Gc(s) = 1

H(s) = 1

N(s) = 0

G(s) = 100/(ττττ s + 1)


P 4.17 A robot gripper control

Km = 30

Rf = 1 ohmRf = 1 ohm

Kf = Ki = 1

J = 0.1,

b = 1


AP 4.1 Tank level regulator


Performance Indices

Elevator


Simplified description of a control system


Elevator input and output

When the fourth floor button is pressed on the firs t floor, the elevator rises to the fourth floor with a speed and floor level accuracy designed for passenger comfort. 57Intelligent Control

Push of the fourth-floor button is an input that

represent a desired output, shown as a step function.


Transient response

Passenger comfort and passenger patience are dependent upon the transient response. If this response is too fast, passenger comfort is sacrificed; if too slow, passenger patience is sacrificed.


Steady-state error

Passenger safety and convenience would besacrificed if the elevator is not properly level.


Performance Indices

• A performance index is a quantitative

measure of the performance of a system and

is chosen so that emphasis is given to the is chosen so that emphasis is given to the

important system specifications.


Response of the system


ISE - Integral of Square of Error

I = e2(t)T

∫ dtI1 = e (t)0

∫ dt


The Integral Squared Error

T

∫I1 = e2(t)0

T

∫ dt


IAE - Integral of the Absolute Magnitude of the

Error

I = e(t)T

∫ dtI2 = e(t)0

∫ dt


ITAE - Integral of Time Multiplied by Absolute

Error

I = t e(t)T

∫ dtI3 = t e(t)0

∫ dt


ITSE - Integral of Time Multiplied by Squared

Error

I = te2(t)T

∫ dtI4 = te (t)0

∫ dt


General form of the performance integral

I = f [e(t),r(t),c((t),t]T

∫ dtI = f [e(t),r(t),c((t),t]0

∫ dt


Section 5.9

∫=T

dtteISE0

2 )( ∫=T

dtteIAE0

|)(|

∫=T

dttetITAE0

|)(| ∫=T

dttteITSE0

2 )(0 0

∫=T

dtttytrtefI0

)),(),(),((


Performance criteria

T(s) = 1

s2 + 2ζs +1


Optimum system

• A control system is optimum when the elected

performance index is minimized.

• The optimum value of the parameters depends

directly upon the definition of optimum, that is,

the performance index.


Open-loop and closed-loop systems


Thank you.


Introduction toIntelligent Control Part 1keffe006/Workshop/ECE4951-Lecture1.pdf · Introduction...

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