Fault detection and isolation for a class of uncertain nonlinear systems: A dual-monitoring model-based approach

This paper presents a fault detection and isolation (FDI) scheme for a class of uncertain nonlinear systems with unknown faults, in which fault isolation process and control reconfiguration are integrated via a supervisory switching strategy. A group of adaptive estimators is performed together with the switching process. The proposed FDI approach, namely dual-monitoring model-based approach, can exploit information both from backstepping procedure and estimators, by which a set of monitoring functions is constructed to detect the occurrence of fault and also identify the specific fault type. In particular, based on some principles, the fault isolation process can be accelerated under a novel interacted isolation scheme. It can be seen that the tracking error can be always guaranteed within a prescribed performance in the existence of system faults. © 2022 The Franklin Institute