Scholarlink

<p>This paper addresses event-triggered fault detection for nonlinear networked control systems (NCSs) with time-varying delays. A Takagi-Sugeno (T-S) fuzzy model is employed to capture the system nonlinearity, and an event-triggered scheme (ETS) is introduced to reduce communication burden by transmitting data only when necessary. Different from existing works based on continuous or periodic communication, the proposed method integrates event-triggered transmission with fault detection filtering under time-varying delays. The aim is to design a fault detection filter such that the residual system is asymptotically stable and satisfies a prescribed <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(H_{\infty }\)</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi>H</mi> <mi>∞</mi> </msub> </math></EquationSource> </InlineEquation> performance. By constructing an appropriate Lyapunov functional, sufficient conditions are derived in terms of linear matrix inequalities (LMIs), from which the filter parameters are obtained. Simulation results demonstrate the effectiveness of the proposed method.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Event-triggered fault detection for T-S fuzzy networked control systems with time-varying delays

  • 期刊论文

  • 发表日期：

    2026年7月22日

查看全文
  • Cheng Tan,
  • Ce Wang,
  • Tongtong Ding,
  • Yaqi Wang

摘要

This paper addresses event-triggered fault detection for nonlinear networked control systems (NCSs) with time-varying delays. A Takagi-Sugeno (T-S) fuzzy model is employed to capture the system nonlinearity, and an event-triggered scheme (ETS) is introduced to reduce communication burden by transmitting data only when necessary. Different from existing works based on continuous or periodic communication, the proposed method integrates event-triggered transmission with fault detection filtering under time-varying delays. The aim is to design a fault detection filter such that the residual system is asymptotically stable and satisfies a prescribed \(H_{\infty }\) H ∞ performance. By constructing an appropriate Lyapunov functional, sufficient conditions are derived in terms of linear matrix inequalities (LMIs), from which the filter parameters are obtained. Simulation results demonstrate the effectiveness of the proposed method.