Satellite fault diagnosis using a bank of interacting Kalman filters

The main objective of this work is development and testing of a detection, isolation, and diagnosis algorithm based on interacting multiple model (IMM) filters for both partial (soft) and total (hard) reaction wheels faults in a spacecraft. This is shown to be accomplished under a number of different faulty mode scenarios for these actuators associated with the attitude control system (ACS) of a satellite. Various operating and faulty conditions due to changes and anomalies in the temperature, the power supply line voltage, and the loss of effectiveness of the torque and the current are considered in each reaction wheel associated with the three axes of the satellite. Once a fault mode is detected and isolated the recovery procedure can subsequently be engaged by invoking appropriate switching control strategies for the ACS. The application of a bank of interacting multiple Kalman filters for detection and diagnosis of anticipated reaction wheel failures in the ACS is described and developed. Compared with other model-based fault detection, diagnosis and isolation (FDDI) strategies developed in the control systems literature, our FDDI strategy is shown, through extensive numerical simulations, to be more accurate and robust with potential for extension to a number of other application areas.