Event triggered [formula omitted] fault detection and isolation for T-S fuzzy systems with local nonlinear models

Abstract

This paper is concerned with network-based fault detection and isolation(FDI) observer design for a class of Takagi–Sugeno (T-S) fuzzy systems with local nonlinear models. First, by combining the original system with the FDI observer, the closed-loop systems with asynchronous membership functions are modeled. Second, a new condition is introduced into the event-triggered scheme(ET scheme). This condition facilitates dealing with the asynchronous membership functions. Third, new relaxation terms are added to deal with the time delay disturbance and faults introduced by the Lyapunov–Krasovskii function(LKF) method. Then, sufficient conditions for the existence of the desired FDI observer which ensures the H−/H∞ performance are proposed. Besides, a two-step algorithm is given to co-design the parameters of the ET scheme and a bank of observers are constructed such that each of them is sensitive to particular faults. An inverted pendulum example is given to illustrate the effectiveness of the new results.