Title: Dynamics Modeling and First Design of DragFree Controller for ASTROD I
1Dynamics Modeling and First Design of Drag-Free
Controller for ASTROD I
- Hongyin Li, W.-T. Ni
- Purple Mountain Observatory, Chinese Academy of
Sciences - S. Theil, L. Pettazzi,
- M. S. Guilherme
ZARM University of Bremen, Germany
2Outline
- Introduction of the Mission
- Simulator
- Controller Development
- Conclusion
- Outlook
3Mission Introduction
- Science goal
- Solar-system gravity mapping relativistic
gravity test - Orbit
- Heliocentric orbit, 0.5AU-1AU
- Orbit launch in 2015 ?
- SC configuration
- Cylinder 2.5 (diameter)m 2 m covered by
solar panels. - FEEP(Field Emission Electric Propulsion)
- Star Sensor, Gyroscope (??)
- EPS(Electrostatic Positioning/ Measurement
System) - 1 test mass
4Simulator
- Equations of Motion
- Disturbance Environment
5Coordinates I
6Coordinates II
7Equations of Motion
8Disturbance Environment
- Gravity Field (first order--spherical)
Elements of
Elements of
9Disturbance Environment
- Gravity Field (second order )
- One of the Science goal of ASTROD I is to test
the gravity field parameter of the solar gravity.
So, It must be included in the further
model.
10Disturbance Environment
11Solar Pressure
- Solar pressure at 0.5 AU is 4 times that of
1AU - A low-pass filter is used to get the
stochastic part with a white noise passed
deterministic part
Solar pressure at 1AU
12Coupling between SCTM
Translation coupling
Rotation coupling
13Sensors and actuators
- Star-Sensor
- EPS-position measurement
- EPS-attitude measurement
- EPS-attitude suspension
- FEEP-force
- FEEP-torque
- White noise ? shaped noise
- Need to consider sample frequency, nonlinearity
in the future model.
14Simulator
15Controller Design
- Structure of Controller
- Requirements of controller
- Synthesis
- Closed loop Analysis
16Structure of Controller
17Requirements of Controller
18Synthesis I
LQR Linear-Quadratic-Regulator
Given following linear system
- With the LQR method we can derive the optimal
gain matrix K such that the state-feedback law
minimizes the quadratic cost function
Just as the kalman filter we can get the minimum
steady-state error covariance
19Synthesis II
- LQG LQR KF
- Linear-Quadratic-Gaussian
Linear-quadratic-regulator kalman
filter(Linear-quadratic-filter) - With DC disturbance need feed forward
DC disturbance
20LQG Design Plant
21Controller
Standard LQR used here is MIMO PD controller.
Its feedback is proportion (position, angle )
and derivative (velocity and angular velocity) of
outputs of system. Feed forward part can cancel
the static error.
22Synthesis III
- What does feed forward do to the frequency
- Response of the controller?
- Improve the performance in low frequency
range.(integral ) - but reduce the stability of the closed loop
,need to trade-off - Stability of the closed loop system?
- with some weight gains, there is still some
poles on the right phase because the negative
stiffness. So we need to chose the weight gain
carefully. Try and tuning to get better
performance as well as a stable system. -
23Closed loop analysis
- Transfer function PSD of Simulation Data
- Pointing accuracy
-
24Test mass position
25Transfer functionanalysis
26PSD analysis
27Conclusion
- A model for ASTROD I is built. However it is
simple, the structure is established and each
subsystem can be extended to get a more detailed
model. - LQG (LQRKF) was developed which can meet the
requirements of the mission.
28Outlook
- Detailed model Based on SC design
- Inertial sensorCross-coupling between DOFs
- Star sensorSample frequency,data fusion of two
sensors. - Gyroscope to help the attitude estimate.
- FEEP nonlinearity,frequency response.Location of
FEEP clusters. - Advanced control strategy
- Loop-Shaping with weighted LQR
- Decoupling of controllers and DOFs
- Robust Control method