Satellite Attitude Control System Design Using Reaction Wheels Bhanu Gouda Brian Fast Dan Simon

Satellite Attitude Control System Design Using Reaction Wheels Bhanu Gouda Brian Fast Dan Simon

Outline 1. Overview of Attitude Determination and Control system. Problem formulation 3. Control schemes 3.1 Modified PI Controller 3. Active Disturbance Rejection Control 4. Conclusion

ADCS ADCS: Attitude Determination and Control subsystem Attitude Determination - Using sensors Attitude Control - Using actuators 3

Aerodynamic Gravity gradient Magnetic Solar radiation Micrometeorites Disturbance torques 4

Attitude control modes Orbit insertion Acquisition Slew Contingency or Safe 5

Spacecraft control type Passive control - Gravity gradient control - Spin control 6

Spacecraft control type Active control (Actuators) - Reaction wheels - Momentum wheels - Control - moment gyros - Magnetic torquers -Gas Jets or Thrusters 7

Tetrahedron configuration of Reaction wheels 8

Outline 1. Overview of Attitude Determination and Control system. Problem formulation 3. Control schemes 3.1 Modified PI Controller 3. Active Disturbance Rejection Control 4. Conclusion 9

Problem formulation 10

Mathematical model Angular momentum of each disk H H 1 = I1w1 = I w 1 = mr 1 = mr + md + md [ w ] 1 [ w ] Moment with respect to the space craft M = Mass of the space craft m i = mass of the reaction wheel w i = angular velocity of the wheel θ = Angular position of space craft r = radius of the wheel I= moment of inertia = ( Mr + Md ) θ I θ 11

Mathematical model Conservation of angular momentum d dt [ H 1 H ] + = I θ d dt 1 mr 1 + md θ d dt ( w ) + + ( ) = ( + ) 1 mr md w Mr Md ( w + w ) 1 =. M m. θ ( w + w ) 1 = M m θ + c 1

Outline 1. Overview of Attitude Determination and Control system. Problem formulation 3. Control schemes 3.1 Modified PI Controller 3. Active Disturbance Rejection Control 4. Conclusion 13

Control Scheme Two types of controllers are investigated - Modified PI Controller - Active Disturbance Rejection Controller 14

Simplorer Simplorer Circuit element models Electric machine models Data analysis tools Interfaces with Matlab / Simulink 15

Outline 1. Overview of Attitude Determination and Control system. Problem formulation 3. Control schemes 3.1 Modified PI Controller 3. Active Disturbance Rejection Control 4. Conclusion 16

Modified PI Controller This controller is used as the baseline controller Only one tuning parameter Generalized DOF control structure is proposed Reference: A Robust Two-Degree-of-Freedom Control Design Technique and its Practical Application -Robert Miklosovic, Zhiqiang Gao 17

k i s -1 Plant transfer function θ des θ act ( θ des θ act ). ki S k p. θ act = ( θ des θ act k p c ω ). S. ω. θ c act 18

The desired trajectories as the command input in the closed loop control In this case, a profile generator is used to produce desired angle to the system Motion profile is used instead of step. Motion profiling 19

Simulation Results Plant Model θ act w1 w1 theta theta_de GAIN Motion_profi error in theta control signal w w theta_dot GAIN t Y GAIN GAIN Theta Actual theta_dot_de t_des_de deg_rad Motion profile Modified PI Controller Disturbanc SUM5 RANDOM CONST Random_Nois Random Noise 0

Plant Model GAIN3 10 w1 GAIN 10 theta_do 10 GAIN Modified PI Controller w GAIN4 SUM4 I 10 theta 10 10 I GAIN error_in_the INTG GAIN 10 disturbance 10 theta_actu GAIN GAIN ( w + w ) 1 = θ + c ki ω c θ des θ act ). k p. θ act = ( θ des θ act ).. ω c. ( S S θ act 1

Simulation Results Theta Actual & desired 0.1k 80 t_des_ theta_d 0.1k 80 60 t_des_ theta_d 60 40 40 0 0-10 0 4 6 8 10 t [s] -10 0 4 6 8 10 Noise amplitude: 0.07-0.1 t [s] Noise interval: sec

Simulation Results control inputs w1 and w 8 7 6 5 4 w1.val w.val 7 5 4 3 w1.val w.val 3 0 0 4 6 8 10 1 0 4 6 8 10 t [s] Noise amplitude: 0.07-0.1 Noise interval: sec t [s] 3

Outline 1. Overview of Attitude Determination and Control system. Problem formulation 3. Control schemes 3.1 Modified PI Controller 3. Active Disturbance Rejection Control 4. Conclusion 4

Active Disturbance Rejection Controller New digital controller to motion control problems Disturbances are estimated using extended state observer (ESO) and compensated in each sampling period. Dynamic compensation reduces motion system to a double integrator which can be controlled using a nonlinear PID controller 5

6 Extended State Observer It is a unique nonlinear observer Proper Selection of the gains and functions are critical to the success of the observer Once ESO is properly setup, the performance of the observer is quite insensitive to plant variations and disturbances + = y u b z z z z o o o o o 1 1 0 0 1 ω ω ω ω

Simulation Results Plant Model 7

Simplorer and Matlab Define Simplorer inputs and outputs in the property dialog of the SiMSiM component 8

Matlab/Simulink Model Inputs to the simplorer Outputs from the Simplorer 9

Simulation Results Theta Actual and Theta desired 0.1k 80 60 40 0-10 0 0. 0.4 0.6 0.8 1.1 t_des_d GAIN1. theta_d t [s] 0.1k 80 60 40 0-10 00. 0.6 1 1. 1.7 Noise amplitude: 0.05 Noise Interval: 0.5 sec t_des_ theta_ t [s] 30

Simulation Results 1 8 6 4 w1 and w w1.va w.va 15 5 0-5 -10 w1.va w.va - 0 0. 0.4 0.6 0.8 1.1 t [s] -0 0 0.4 0.8 1 1. 1.7 t [s] Noise amplitude: 0.05 Noise Interval: 0.5 sec 31

Conclusion and Future work The simulation of Modified PI and ADRC showed that ADRC worked well for the system 1 DOF problem will be extended to 3 degrees of freedom problem Implementation of the controller design in microcontroller/fpga microchip. Comparisons with other controllers 3