Kybernetika 50 no. 4, 580-595, 2014

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

Mouquan Shen, Guangming Zhang, Yuhao Yuan and Lei MeiDOI: 10.14736/kyb-2014-4-0580

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.

Keywords:

Markov jump linear system, sampled data $H_\infty $ filtering, linear matrix equality

Classification:

93E12, 62A10

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