Centralized Fault Detection of Complex Uncertain Hybrid Systems

This paper presents a centralized fault detection scheme for hybrid systems with nonlinear uncertain continuous dynamics and measurement noise. The scheme features a modular observer based on a modified hybrid automaton framework, that models each subsystem individually and the whole system as a composition of these models. The fault detection scheme employs a filtering approach, that attenuates the effect of measurement noise and allows tighter detection thresholds, and also an algorithm that handles autonomous mode transitions. As a result, the proposed approach can detect both discrete and parametric faults and guarantees no false alarms under all circumstances. Simulation results from a two-tank hybrid system example illustrate the effectiveness of the proposed scheme.