Open AccessFault detection for asynchronous T–S fuzzy networked Markov jump systems with new event‐triggered scheme
Author(s) -
Aslam Muhammad Shamrooz,
Li Qianmu,
Hou Jun
Publication year - 2021
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/cth2.12136
Subject(s) - control theory (sociology) , fault detection and isolation , fuzzy logic , computer science , filter (signal processing) , lyapunov function , fault (geology) , fuzzy control system , lyapunov stability , markov chain , linear matrix inequality , asynchronous communication , nonlinear system , mathematics , mathematical optimization , control (management) , artificial intelligence , actuator , computer network , physics , quantum mechanics , machine learning , seismology , computer vision , geology
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.