Interactive Bank of Unscented Kalman Filters for Fault Detection and Isolation in Reaction Wheel Actuators of Satellite Attitude Control System

Abstract

The main objective of the research investigated in this paper is the detection and isolation of partial (soft) and total (hard) failures in the reaction wheel (RW) actuators of the satellite attitude control system (ACS) during its mission operation. The fault detection and isolation (FDI) is accomplished using the interactive multiple models (IMM) scheme developed based on the unscented Kalman filter (UKF) algorithm. Towards this objective, the healthy mode of the ACS system under different operating conditions as well as a number of different fault scenarios including changes and anomalies in the temperature, power supply bus voltage, and unexpected current variations in the actuators of each axis of the satellite are considered. We describe and develop a bank of interacting multiple model unscented Kalman filters (IMM-UKF) to detect and isolate the above mentioned reaction wheel failures in the ACS system. Also, it should be emphasized that the proposed IMM-UKF technique is implemented based on a high-fidelity highly nonlinear model of a commercial RW. Compared to other fault detection and isolation (FDI) strategies developed in the control systems literature, the proposed FDI scheme is shown, through extensive numerical simulations, to be more accurate, less computationally demanding, and more robust with the potential of extending to a number of other engineering applications