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Title: Non-fragile sampled data $H_\infty $ filtering of general continuous Markov jump linear systems (English)
Author: Shen, Mouquan
Author: Zhang, Guangming
Author: Yuan, Yuhao
Author: Mei, Lei
Language: English
Journal: Kybernetika
ISSN: 0023-5954 (print)
ISSN: 1805-949X (online)
Volume: 50
Issue: 4
Year: 2014
Pages: 580-595
Summary lang: English
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Category: math
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Summary: 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. (English)
Keyword: Markov jump linear system
Keyword: sampled data $H_\infty $ filtering
Keyword: linear matrix equality
MSC: 60J27
MSC: 62A10
MSC: 93E12
idZBL: Zbl 06386428
idMR: MR3275086
DOI: 10.14736/kyb-2014-4-0580
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Date available: 2014-11-06T15:03:47Z
Last updated: 2016-01-03
Stable URL: http://hdl.handle.net/10338.dmlcz/143985
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