Event-triggered H filtering of Markov jump systems with general transition probabilities

Mouquan Shen, Dan Ye, Qing Guo Wang

Research output: Contribution to journalArticlepeer-review

69 Citations (Scopus)

Abstract

This paper investigates the H filtering of Markov jump systems with general transition probabilities which are known, uncertain and unknown. The transmission from sensor to filter is determined by a mode-dependent event-triggered scheme. The advantage of the scheme is that no restriction is imposed on a triggering scalar. Employing a zero-order-holder, the resulting filtering error system is expressed by Markov jump systems with time delay. With the aid of a relaxed Lyapunov–Krasovskii functional and the Finlser lemma, the desired H filter gains and the related triggering parameter are solved in a uniformed framework. It is shown that the proposed approach is less conservative than the existing one. Numerical examples are given to verify the validity of the proposed method.

Original languageEnglish
Pages (from-to)635-651
Number of pages17
JournalInformation Sciences
Volume418-419
DOIs
Publication statusPublished - Dec 2017

Keywords

  • Event-triggered control
  • H filtering
  • Markov jump system

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computer Science Applications
  • Information Systems and Management
  • Artificial Intelligence

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