Parameter estimation-based fault detection, isolation and recovery for nonlinear satellite models

This brief is concerned with the problem of nonlinear fault detection, isolation, and recovery (FDIR) for the satellite's orbital and attitude models through construction of residual generators that are based on least-squares parameter estimation techniques. By viewing system anomalies caused by faults and/or malfunctions as changes of certain parameters in the system, our goal is to detect, isolate, and recover from faults through estimating these parameters and adaptively redesigning and reconfiguring the controllers. The convergence and robustness properties of the residual generators are analytically and experimentally investigated. Furthermore, the corresponding decision logic and thresholds for fault diagnosis are properly selected and specified. Numerical simulation results for the proposed technique as applied to nonlinear satellite models are presented to demonstrate its performance capabilities.