Www.ifr.uni-stuttgart.de Institute of Flight Mechanics and Control Barcelona, LISA7 Symposium, June...

PowerPoint-PräsentationIFR – University of Stuttgart
LISA Pathfinder Data Analysis
Barcelona, LISA7 Symposium, June 17th 2008
Hannover, 10. April 2008
Outline
Simulation
Analysis
Conclusion
Outline
Simulation
Analysis
Conclusion
The LTP Science objective
x1
x2
Dx
The Drift Mode : 2 objectives
DC gravity term
x1
x2
Dx
DC gravity term
x1
x2
Dx
Force noise without actuation
x1
x2
Dx
x1
x2
Dx
x1
x2
Dx
The Drift Mode Functionning
A Custom control mode is used
A control cycle is necessary
The Drift Mode Specificities
Unstable phase
Science data is "sliced“
Modeling the dynamics
Observation with cross talks
Same type of equations in other DOFs
For performance, the dynamics of x and φ must be coupled in the model
Assumption on electrodes 1-2-3-4 :
is close to +1
x
y
z
Same type of equations in other DOFs
For performance, the dynamics of x and φ must be coupled in the model
Assumption on electrodes 1-2-3-4 :
is close to +1
DC voltage noise constant
Constraints on the dynamics
External Forces and Torques
DC gravity is dominating
Outline
Simulation
Analysis
Conclusion
Control Strategy and Implementation
Drift phases
Duration 100-500 s
Fall 4-40 μm
t
X2
T0
T1
Drift phases
Short impulses
t
X2
T0
T1
Drift phases
Short impulses
controlled maneuvers
Using sliding mode controller
t
X2
T0
T1
Drift phases
controlled maneuvers
Short impulse
Let Phi drift as well ?
WR/HR for the capacitive actuation ?
Control Strategy and Implementation :
D C D C D
D K D C D K D C
D K D K D
K D K D K D K
Repeated Drifts/Controls
Drifts/Controls with a kick
TELECOMAND CONTROL Pre-defined sequence executed on a pre-defined timeline
ON-BOARD CONTROL Sequence computed by On-Board-Computer
A controlled maneuver corrects for uncertainties
C D K D K D K D C
C D K D K D K D C
Telecomand based
Stabilize with controlled maneuver
Force noise and Open loop mismatch limit number of kicks.
1% FDC → 2000s
Settings for a kick
Phase
Parameters
WR
Outline
Simulation
Analysis
Conclusion
Simulation
Filters can be automatically derived from same model
Image of mario‘s work
Simulation
Simulation
Results
But SC angular motion was perturbed by sliding mode controller
Strong coupling between θ and x !
Simulation
Results
Simulation
Results
Difference between PSDs is checked
Simulation
Results
Difference between PSDs is checked
Model matching guarrantees goodness of filters for analysis : here calibration is needed
Outline
Simulation
Analysis
Conclusion
Analysis
Using a Kalman smoother
Linear sys
Analysis
Using a Kalman smoother
Linear sys
U
Analysis
Linear sys
Kalman Smoother
Analysis
Ratio is optimized
Stiffness very observable
U
Analysis
Usefull data is isolated
Analysis
~2 mHz and 0.5 mHz
Analysis
Retrieving Noise spectrum
Gap filling must be used at and below the cutting frequency
It is combined with windowing of the whole signal
Show first example data filled and windowed
Analysis
Obained by minimizing the criterion:
Analysis
Works well at low freq.
Analysis
Works well at cutting freq.
Analysis
Works well at cutting freq.
Not so goot at high freq.
Analysis
Analysis
Outline
Introduction
Simulation
Analysis
Conclusion
Conclusions
Implementation limitations have a cost
Conclusions
Control stability limit is insufficiently known
Force noise in WR and φ cross talk TBC
Conclusions

Www.ifr.uni-stuttgart.de Institute of Flight Mechanics and Control Barcelona, LISA7 Symposium, June...

Documents

Transcript of Www.ifr.uni-stuttgart.de Institute of Flight Mechanics and Control Barcelona, LISA7 Symposium, June...