Event-triggered fault detection for discrete-time T-S fuzzy systems

This paper is concerned with the design of piecewise fuzzy diagnostic observers for discrete-time T-S fuzzy systems under an event-triggered (ET) communication mechanism. Considering that the premise variables of the fuzzy diagnostic observer and the system may belong to different local space regions due to the introduction of ET mechanism, a partition method-based piecewise fuzzy diagnostic observer is designed to detect faults. The two-term approximation approach is introduced to approximate the time-varying delay. By transforming the augmented system into an input-output form consisting of two interconnected subsystems, the design condition of the piecewise fuzzy diagnostic observer is obtained by using the scaled small gain (SSG) theorem and a piecewise Lyapunov-Krasovskii functional. Furthermore, the L∞/L2 and L∞ fault detection (FD) scheme is used to optimize the FD performance. Finally, two simulation examples are provided to show the efficiency of the proposed design method.