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

Mouquan Shen; Guangming Zhang; Yuhao Yuan; Lei Mei

Kybernetika (2014)

  • Volume: 50, Issue: 4, page 580-595
  • ISSN: 0023-5954

Abstract

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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.

How to cite

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Shen, Mouquan, et al. "Non-fragile sampled data $H_\infty $ filtering of general continuous Markov jump linear systems." Kybernetika 50.4 (2014): 580-595. <http://eudml.org/doc/261996>.

@article{Shen2014,
abstract = {This paper is concerned with the non-fragile sampled data $H_\infty $ 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_\infty $ filter to ensure both the robust stochastic stability and a prescribed level of $H_\infty $ 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.},
author = {Shen, Mouquan, Zhang, Guangming, Yuan, Yuhao, Mei, Lei},
journal = {Kybernetika},
keywords = {Markov jump linear system; sampled data $H_\infty $ filtering; linear matrix equality; Markov jump linear system; sampled data filtering; linear matrix equality},
language = {eng},
number = {4},
pages = {580-595},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Non-fragile sampled data $H_\infty $ filtering of general continuous Markov jump linear systems},
url = {http://eudml.org/doc/261996},
volume = {50},
year = {2014},
}

TY - JOUR
AU - Shen, Mouquan
AU - Zhang, Guangming
AU - Yuan, Yuhao
AU - Mei, Lei
TI - Non-fragile sampled data $H_\infty $ filtering of general continuous Markov jump linear systems
JO - Kybernetika
PY - 2014
PB - Institute of Information Theory and Automation AS CR
VL - 50
IS - 4
SP - 580
EP - 595
AB - This paper is concerned with the non-fragile sampled data $H_\infty $ 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_\infty $ filter to ensure both the robust stochastic stability and a prescribed level of $H_\infty $ 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.
LA - eng
KW - Markov jump linear system; sampled data $H_\infty $ filtering; linear matrix equality; Markov jump linear system; sampled data filtering; linear matrix equality
UR - http://eudml.org/doc/261996
ER -

References

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