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Nonfragile fuzzy filtering for nonlinear systems with event-triggered and quantized mechanisms

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  • Liu, Guo-Jun
  • Wang, Fan
  • Hu, Donghong

Abstract

This paper addresses the problem of nonfragile fuzzy filtering for continuous-time nonlinear systems with event-triggered and quantized mechanisms. Firstly, the continuous-time nonlinear systems are represented by Takagi-Sugeno fuzzy models. Secondly, the dynamic quantization strategies and event-triggered mechanisms are used to reduce the communication burden and improve resource efficiency. Thirdly, considering the uncertainty of filtering parameters, the analysis and synthesis of nonfragile H∞ filters are carried out using integral Lyapunov functions and decoupled inequality techniques. In addition, the optimization parameter results of three factors including event-triggered mechanisms, dynamic quantization and nonfragile filtering are obtained by using linear matrix inequality. Finally, two simulation examples are presented to demonstrate the effectiveness of the proposed method.

Suggested Citation

  • Liu, Guo-Jun & Wang, Fan & Hu, Donghong, 2026. "Nonfragile fuzzy filtering for nonlinear systems with event-triggered and quantized mechanisms," Applied Mathematics and Computation, Elsevier, vol. 522(C).
    • Handle: RePEc:eee:apmaco:v:522:y:2026:i:c:s0096300326000366
    DOI: 10.1016/j.amc.2026.129984
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