Dynamic Event-Triggered H Filtering for Fuzzy Markov Jump Systems Subject to Mismatched Quantization

Yang Gu, Mouquan Shen, Ju H. Park, Qing Guo Wang, Yang Yi, Yonghui Sun

Research output: Contribution to journalArticlepeer-review

Abstract

This paper is dedicated to a dynamic event-triggered H filtering method of fuzzy Markov jump systems via a mismatched quantization scheme. The system outputs are triggered by a dynamic event-triggered mechanism and then quantized via a mismatched quantizer before being sent to the remote filter. The dynamic triggering scheme with a special diagonal matrix structure threshold is built to reduce the network burden. The quantizer is constructed in a multi-channel paradigm with a time-varying mismatch degree. Then, the remote reduce-order filter is designed to be both fuzzy-rule and mode-dependent. By adopting Finsler’s Lemma and the vertex separation method, sufficient conditions are derived in terms of form matrix inequalities. At last, the effectiveness of the proposed method is demonstrated by a tunnel diode circuit.

Original languageEnglish
Pages (from-to)10639-10649
Number of pages11
JournalIEEE Transactions on Automation Science and Engineering
Volume22
DOIs
StatePublished - 2025

Keywords

  • event-triggered sampling
  • fuzzy systems
  • Markov jump systems
  • quantized filtering

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