引用本文:林文娟,何勇.时滞半Markov跳变神经网络系统事件驱动故障检测滤波器设计[J].控制理论与应用,2021,38(9):1341~1350.[点击复制]
LIN Wen-juan,HE Yong.Event-triggered fault detection filter design for semi-Markov jump neural networks with time delays[J].Control Theory and Technology,2021,38(9):1341~1350.[点击复制]
时滞半Markov跳变神经网络系统事件驱动故障检测滤波器设计
Event-triggered fault detection filter design for semi-Markov jump neural networks with time delays
摘要点击 2122  全文点击 762  投稿时间:2020-08-03  修订日期:2021-08-30
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DOI编号  10.7641/CTA.2021.00502
  2021,38(9):1341-1350
中文关键词  半Markov跳变神经网络  故障检测  事件驱动  时滞  Lyapunov-Krasovskii泛函
英文关键词  semi-Markov jump neural networks  fault detection  event-triggered: time delays  Lyapunov-Krasovskii functional
基金项目  国家自然科学基金项目(61973284), 湖北省自然科学基金项目(2019CFA040), 111计划项目(B17040), 中国地质大学(武汉)中央高校基本科研业务费资助项目
作者单位E-mail
林文娟 中国地质大学(武汉)自动化学院 linwenjuan0221@163.com 
何勇* 中国地质大学(武汉)自动化学院 heyong08@cug.edu.cn 
中文摘要
      本文针对一类具有时滞的半Markov跳变神经网络系统, 研究其基于滤波器的故障检测问题. 首先, 通过引 入一种事件驱动通讯机制和一个滤波器, 并将时变时滞以及网络诱导时滞考虑进来, 建立残差系统, 将故障检测问 题转化为求解满足一定H1性能指标的滤波问题. 然后, 基于Lyapunov-Krasovskii(L–K)泛函方法, 通过利用时滞乘 积型L–K泛函思想、积分不等式、改进逆凸矩阵不等式等方法, 以线性矩阵不等式形式给出故障检测滤波器的设计 方法. 最后, 数值仿真结果验证本文所设计故障检测滤波器的有效性与优越性.
英文摘要
      In this paper, the problem of fault detection is addressed for delayed semi-Markov jump neural networks (S-MNNs) based on an event-triggered communication scheme. By introducing a filter, the addressed fault detection problem is converted into an $H_\infty$ 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 $H_\infty$ performance of the residual system is designed. Finally, numerical simulations are provided to illustrate the effectiveness and superiority of the presented results.