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		Wei LIU,Huaguang ZHANG,Jie FU,Zhanshan WANG.[en_title][J].Control Theory and Technology,2011,9(2):148~154.[Copy]

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WeiLIU,HuaguangZHANG,JieFU,ZhanshanWANG
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Received:October 17, 2009Revised:February 01, 2010

基金项目:This work was supported by the National Natural Science Foundation of China (No. 50977008, 60521003, 60774048).

A novel suboptimal algorithm for state estimation of Markov jump linear systems

Wei LIU,Huaguang ZHANG,Jie FU,Zhanshan WANG

(School of Information Science and Engineering, Northeastern University)

Abstract:

This paper is concerned with state estimation problem for Markov jump linear systems where the disturbances involved in the systems equations and measurement equations are assumed to be Gaussian noise sequences. Based on two properties of conditional expectation, orthogonal projective theorem is applied to the state estimation problem of the considered systems so that a novel suboptimal algorithm is obtained. The novelty of the algorithm lies in using orthogonal projective theorem instead of Kalman filters to estimate the state. A numerical comparison of the algorithm with the interacting multiple model algorithm is given to illustrate the effectiveness of the proposed algorithm.

Key words: State estimation Markov jump Linear systems Orthogonal projective theorem