Adaptive Event-Triggered Fault Detection Scheme for Semi-Markovian Jump Systems with Output Quantization

Linchuang Zhang, Hongjing Liang, Yonghui Sun, Choon Ki Ahn

Research output: Contribution to journalArticlepeer-review

90 Citations (Scopus)

Abstract

This paper examines the adaptive event-triggered fault detection problem of semi-Markovian jump systems (S-MJSs) with output quantization. First, we develop an adaptive event-triggered scheme for S-MJSs that is more effective than conventional event-triggered strategy for decreasing network transmission information. Meanwhile, we design a new adaptive law that can dynamically adjust the event-triggered threshold. Second, we consider output signal quantization and transmission delay in the proposed fault detection scheme. Moreover, we establish novel sufficient conditions for the stochastic stability in the proposed fault detection scheme with an H_{\infty } performance with the help of linear matrix inequalities (LMIs). Finally, we provide simulation results to demonstrate the usefulness of the developed theoretical results.

Original languageEnglish
Article number8708964
Pages (from-to)2370-2381
Number of pages12
JournalIEEE Transactions on Systems, Man, and Cybernetics: Systems
Volume51
Issue number4
DOIs
Publication statusPublished - 2021 Apr

Keywords

  • Adaptive event-triggered scheme
  • fault detection
  • output quantization
  • semi-Markovian jump systems (S-MJSs)

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering

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