Fault Detection and Isolation for Affine Fuzzy Systems With Sensor Faults

Abstract

This paper investigates the fault detection and isolation (FDI) problem for a class of nonlinear systems with sensor outage faults. The considered nonlinear systems are described as affine fuzzy models, and the system outputs are chosen as the premise variables of fuzzy models. Different from the existing results, the influence of sensor faults on premise variables is considered. As a result, the well-known parallel distributed compensation scheme cannot be used for FDI filters design. By using the structural information encoded in the fuzzy rules, the affine fuzzy system is represented by multiple operating-regime-based models in fault-free case and faulty cases. In the multiple-model scheme, a bank of piecewise FDI filters are constructed, each of them is based on the affine fuzzy model that describes the system in the presence of a specified fault. The fault-dependent residual signals generated from the filters are used for detecting and isolating the specified fault. The FDI filter design conditions are obtained in the formulation of linear matrix inequalities. Finally, a numerical example is given to illustrate the effectiveness and merits of the proposed method.