Geodesic
Non-fragile sampled data $H_\infty $ filtering of general continuous Markov jump linear systems
Kybernetika, Tome 50 (2014) no. 4, pp. 580-595
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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.
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.
DOI : 10.14736/kyb-2014-4-0580
Classification : 60J27, 62A10, 93E12
Keywords: Markov jump linear system; sampled data $H_\infty $ filtering; linear matrix equality 
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Shen, Mouquan; Zhang, Guangming; Yuan, Yuhao; Mei, Lei. Non-fragile sampled data $H_\infty $ filtering of general continuous Markov jump linear systems. Kybernetika, Tome 50 (2014) no. 4, pp. 580-595. doi: 10.14736/kyb-2014-4-0580

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