Event-triggered fault detection filter design for semi-Markov jump neural networks with time delays

被引：0

作者：

Lin W.-J. ^{[1
,2
]}

He Y. ^{[1
,2
]}

机构：

[1] School of Automation, China University of Geosciences, Wuhan

[2] Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, Wuhan

来源：

Kongzhi Lilun Yu Yingyong/Control Theory and Applications | 2021年 / 38卷 / 09期

基金：

中国国家自然科学基金;

关键词：

Event-triggered: time delays; Fault detection; Lyapunov-Krasovskii functional; Semi-Markov jump neural networks;

D O I：

10.7641/CTA.2021.00502

中图分类号：

学科分类号：

摘要：

In this paper, the problem of fault detection is addressed for delayed semi-Markov jump neural networks based on an event-triggered communication scheme. By introducing a filter, the addressed fault detection problem is converted into an H∞ filtering problem. Then, based on the Lyapunov-Krasovskii functional theory, by constructing a delay-product-Lyapunov-Krasovskii functional and using the improved reciprocally convex combination approach, a fault detection filter that guarantees the asymptotic stability and the desired H∞ performance of the residual system is designed. Finally, numerical simulations are provided to illustrate the effectiveness and superiority of the presented results. © 2021, Editorial Department of Control Theory & Applications South China University of Technology. All right reserved.

引用

页码：1341 / 1350

页数：9

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