FAULT DETECTION for SPACECRAFT ATTITUDE CONTROL SYSTEM M. Amin Vahid D. Mechanical Engineering Department Concordia University December 19 th, 2010
Attitude control : the exercise of control over the orientation of an object with respect to an inertial frame of reference or another entity (the celestial sphere, certain fields, nearby objects, etc.).
Controlling vehicle attitude requires : sensors to measure vehicle attitude actuators to apply the torques needed to re-orient the vehicle to a desired attitude algorithms to command the actuators based on (1) sensor measurements of the current attitude and (2) specification of a desired attitude.
Momentum wheels These are electric motor driven rotors made to spin in the direction opposite to that required to re-orient the vehicle. Since momentum wheels make up a small fraction of the spacecraft's mass and are computer controlled, they give precise control.
Momentum wheels are generally suspended on magnetic bearings to avoid bearing friction and breakdown problems. To maintain orientation in three dimensional space a minimum of two must be used, with additional units providing single failure protection.
Spacecraft systems need increased on board autonomy to detect the occurred faults, isolate the faulty components, and effectively handle their operation in the presence of such faults. In this research a scheme of fault detection and diagnosis is developed for spacecraft Attitude Control System.
Fault detection and isolation a subfield of control engineering which concerns itself with monitoring a system, identifying when a fault has occurred, and pinpointing the type of fault and its location.
Fault detection: the identification of the presence of an unknown fault.
FDD Methods Analythical Redundancy Hrdware Redundancy Model Base Signal Base Heuristic Model Analytical Model Spectrum Analysis Wavelet Techniques Expert Knowledge Base/Neural Network System State EStimation Parameter estimation
Model-based FDI In model-based FDI techniques some model of the system is used to decide about the occurrence of fault. The system model may be mathematical, or knowledge based. Some of the model-based FDI techniques include observer-based approach, parityspace approach, and parameter identification based methods.
State estimation approach In the Kalman Filter method, the innovation of K.F is used as the fault detection residual. This residual is white and has a zero mean under nonfaulty conditions, and becomes non-zero in the presence of a fault. The key idea in the parity relation approach is to check the consistency of the mathematical equations of the system (analytical redundancy relations) by using the actual measurements. In this method, residuals are colored and disturbance decoupling improves.
Description and Modeling of Spacecraft Attitude Control System Equations of motion:
In the other hand so :
Reference frame
ω RIB C θ C ψ C θ S ψ S θ S ψ C φ S φ S θ C ψ C ψ C φ S φ S θ S ψ S φ C θ S φ S ψ C φ S θ C ψ S φ C ψ C φ S θ S ψ C φ C θ 0 ω 0 0 ω BR M I S h w ω BI h B h w I S I S ω RIB p q r Q ϕ θ ψ
M G Reaction wheels we have: w w dem Max angular moment 0.2Nm/s Max angular velacity 280 rad/sec Inertia moment Nominal Velocity Nominal torque 0.00043 kgm2 100 rad/sec 1 N.m
Linearization
Computing the state transition matrix
The linear state space representation of the process model: The covariance matrix M before the:
Computing the Kalman gain matrix K Kalman Filter as a Residual Generator
Euler angles (fault-free) Angular velocity (fault-free)
6 5 4 3 2 1 0-1 0 5 10 15 20 25 30 35 40 Euler angle (fault injected for in t=13s) Residuals (fault injected in t=13s)
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