Fault detection for asynchronous T–S fuzzy networked Markov jump systems with new event‐triggered scheme
Muhammad Shamrooz Aslam, Qianmu Li, Jun Hou
Abstract
Abstract In this article, an adaptive event‐triggered fault detection problem for the asynchronous Takagi–Sugeno fuzzy networked Markov jump systems is investigated based upon the time‐varying delays. The purpose of designing a fault detection filter is to detect the fault signal under the influence of disturbance with network transmission. In the design process, one essential factor, time‐varying delay in the fuzzy filter with appearing in the residual signal, is taken into consideration. In order to rationally utilise network resources and elaborately avoid unnecessary continuous monitoring, an adaptive event‐triggered scheme is designed to guarantee the Takagi–Sugeno fuzzy networked Markov jump systems. Thus it helps to lower the energy consumption of communication while ensuring the performance of the system. Different from the conventional triggering mechanism, in this article, the parameters of the triggering function are based on a new adaptive law which is obtained online rather than a predefined constant. Based on the associated Lyapunov stability theory and appropriate inequality, some sufficient criteria in the form of linear matrix inequalities are obtained to ensure the stability of the resulting error system. Finally, a tunnel diode example is employed to illustrate the effectiveness of the proposed methods.