Fault detection and isolation for a class of nonlinear systems based on a bundle of observers and zonotope analysis

This paper introduces a novel fault detection and isolation (FDI) approach for nonlinear systems subject to unknown but bounded disturbances. The proposed approach combines a bundle of fault detection observers (FDOs), tuned by a peak-to-peak performance technique, with an offline reachability method to generate reliable actuator fault detection and isolation thresholds. Moreover, a sliding-window algorithm, based on zonotopic computation, is designed to be able to provide dynamical fault detection thresholds. This allows one to reduce the conservatism and, by the way, enhance the efficiency of the proposed approach. A quadruple-tank system is considered as a case study, where the theoretical findings of this work are supported by simulation results. In addition, on this example, the performance of the proposed method is compared to that of another method selected from the literature.