Fault detection and accommodation of a class of nonlinear systems

Fault detection and accommodation strategy for a nonlinear system is proposed in this paper. The faults only related to the system states are considered, these typical faults are very common in physical systems. The basis idea is that when the desired trajectory is periodic, then the fault function can be expended to parameterized known basis functions by Fourier series, and thus an adaptive learning scheme based on the known basis functions for accommodating failures can be constructed. A fault detection scheme based on the nominal model is designed via the dynamic of the tracking errors. The robustness and sensitivity of the proposed fault detection scheme with respect to modeling uncertainties are analyzed. The stability of the proposed accommodation controller is also proved and the tracking performance is saved.