Centralized Fault Detection of Complex Uncertain Hybrid Systems ⁎⁎This work has been supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 739551 (KIOS CoE) and from the Government of the Republic of Cyprus through the Directorate General for European Programmes, Coordination and Development.

Abstract

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.