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Type: Journal article
Title: Design and stability of moving horizon estimator for Markov jump linear systems
Author: Sun, Q.
Lim, C.
Shi, P.
Liu, F.
Citation: IEEE Transactions on Automatic Control, 2019; 64(3):1109-1124
Publisher: Institute of Electrical and Electronics Engineers
Issue Date: 2019
ISSN: 0018-9286
Statement of
Qing Sun, Cheng-Chew Lim, Peng Shi and Fei Liu
Abstract: This paper presents a moving horizon algorithm with mode detection for state estimation in Markov jump systems with Gaussian noise. This state estimation scheme is a combination of the maximum-likelihood algorithm and the moving horizon approach. The maximum-likelihood algorithm provides optimal estimate of the mode sequence within a moving fixed-size horizon, and the moving horizon estimation is an optimization-based solution. As a result, a mode detection-moving horizon estimator design method is proposed. Through the stochastic observability properties of the Markov jump linear systems, sufficient conditions for stability are established.
Keywords: Markov jump systems; maximum-likelihood algorithm; moving horizon approach; state estimation
Rights: © 2018 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See standards/publications/rights/index.html for more information.
DOI: 10.1109/TAC.2018.2816102
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