Partially mode-dependent H∞ filtering for discrete-time Markovian jump systems with partly unknown transition probabilities

Authors:
Guoliang Wang;Qingling Zhang;Victor Sreeram
Affiliations:
Institute of Systems Science, Northeastern University, Shenyang, Liaoning 110004, PR China and Key Laboratory of Integrated Automation of Process Industry, Ministry of Education, Northeastern Univ ...;Institute of Systems Science, Northeastern University, Shenyang, Liaoning 110004, PR China and Key Laboratory of Integrated Automation of Process Industry, Ministry of Education, Northeastern Univ ...;Department of Electrical and Electronic Engineering, University of Western Australia, 35 Stirling Highway Crawley, Western Australia 6009, Australia
Venue:
Signal Processing
Year:
2010

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Abstract

This paper is concerned with the partially mode-dependent H"~ filtering problem for discrete-time Markovian jump systems with partly unknown transition probabilities via different techniques, where the unknown elements are estimated. New version of bounded real lemma for discrete-time Markovian jump systems with partly unknown transition probabilities is presented. Based on the obtained criterion and via a stochastic variable satisfying Bernoulli random binary distribution, new H"~ filter with partially mode-dependent characterization is established in terms of linear matrix inequalities (LMIs). Finally, numerical examples are given to show the effectiveness of the proposed design method.