Intelligent hybrid robust fault detection and isolation of reaction wheels in satellite attitude control system

This paper presents a novel hybrid scheme for robust detection and isolation of faults affecting control torques of reaction wheel motors in the satellite control system. The proposed fault diagnosis scheme consists of a residual generation module relying on a bank of residual filters, followed by an intelligent residual evaluation module. The residuals are designed to be decoupled from aerodynamic disturbance and maneuvers by exploiting a nonlinear geometric approach. The residual evaluation module is then implemented via two separate schemes arranged in series and parallel forms. In particular, in the series form the detection module detects the occurrence of a fault, whilst the isolation module identifies the occurred fault in cascade. On the other hand, the parallel form exploits a single module carrying out these tasks simultaneously. Furthermore, an ensemble classification scheme, defined as blended learning, is exploited along with geometric approach for the first time in this work. This strategy blends heterogeneous classification schemes to improve the fault classification performances. Extensive assessments on the performances and robustness properties of the presented methods are performed by a high-fidelity satellite simulator with respect to parameter uncertainties, attitude maneuvers, disturbances, and measurements errors. The results document that the suggested hybrid fault detection and isolation outperforms the classic nonlinear geometric approach.

I. Introduction

The increasing operational requirements for onboard autonomy in satellite control systems need Fault Detection and Isolation (FDI) methods providing fundamental information about the system health status, to allow subsequent accommodation actions to improve system reliability and availability, while maintaining desirable performances [1]. Several research efforts have been recently dedicated to develop active robust FDI methods for sensors and actuators of satellite Attitude Control Systems (ACSs) by mapping the satellite system into subsystems decoupled from disturbances [2], [3] and [4]. Most of these methods exploit the Nonlinear Geometric Approach (NLGA) to decouple the generated residuals from environmental disturbing inputs.