Event‐Based Fault Detection Filtering for Networked Switched Repeated Scalar Nonlinear Systems

ABSTRACT This paper concerns the dynamic event‐triggered fault detection (FD) problem for switched repeated scalar nonlinear systems subject to stochastic disturbance. First, an internal dynamic variable is incorporated into an event‐triggered framework to adjust the triggered condition, significantly extending the triggering intervals and reducing data transmission. Then, a time‐varying FD filter, which is dwell‐time‐dependent, is designed to produce a residual signal. By minimizing the error between residual and faults, the FD issue is transformed into an filtering problem. By applying a dwell‐time‐dependent Lyapunov function (DTDLF) approach and the properties of positive diagonally dominant matrices, sufficient conditions are derived to guarantee that the filtering error system is mean‐square asymptotically stable with non‐weighted performance. This method avoids the conservatism associated with the traditional multiple Lyapunov function approach in weighted performance analysis. Finally, a simulation example demonstrates the effectiveness of the developed method.