Non-fragile sampled data H filtering of general continuous Markov jump linear systems

Mouquan Shen, Guangming Zhang, Yuhao Yuan, Lei Mei

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

This paper is concerned with the non-fragile sampled data H filtering problem for continuous Markov jump linear system with partly known transition probabilities (TPs). The filter gain is assumed to have additive variations and TPs are assumed to be known, uncertain with known bounds and completely unknown. The aim is to design a non-fragile H filter to ensure both the robust stochastic stability and a prescribed level of H performance for the filtering error dynamics. Sufficient conditions for the existence of such a filter are established in terms of linear matrix inequalities (LMIs). An example is provided to demonstrate the effectiveness of the proposed approach.

Original languageEnglish
Pages (from-to)580-595
Number of pages16
JournalKybernetika
Volume50
Issue number4
DOIs
StatePublished - 2014

Keywords

  • Linear matrix equality
  • Markov jump linear system
  • Sampled data H filtering

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