Fault Diagnosis of Uncertain Hybrid Systems

This paper presents an online monitoring and fault diagnosis architecture for hybrid systems with nonlinear uncertain discrete-time dynamics. The architecture 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 can detect both discrete and parametric faults using a mode dependent time-varying threshold that guarantees no false-positives alarms due to modeling uncertainty. The fault isolation scheme can anticipate which fault events may have occurred and dynamically employs only the necessary number of isolation estimators that try to isolate the fault by calculating residual thresholds and approximating the unknown parameter values. Simulation results of a two-tank hybrid system example illustrate the effectiveness of the proposed approach. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.