Design and stability of moving horizon estimator for Markov jump linear systems

Sun, Q.; Lim, C.; Shi, P.; Liu, F.

Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/118941

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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 1558-2523
Statement of Responsibility:	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 http://www.ieee.org/publications standards/publications/rights/index.html for more information.
DOI:	10.1109/TAC.2018.2816102
Grant ID:	http://purl.org/au-research/grants/arc/DP170102644
Published version:	http://dx.doi.org/10.1109/tac.2018.2816102
Appears in Collections:	Aurora harvest 8 Electrical and Electronic Engineering publications

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