State estimation for discrete-time markov jump linear systems based on orthogonal projective theorem

In this paper, state estimation problem for discrete-time Markov jump linear systems is considered. Based on orthogonal projective theorem, a novel suboptimal algorithm for state estimate of discrete-time Markov jump linear systems in the sense of minimum mean square error estimate is proposed. The...

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Bibliographic Details
Published in:International journal of control, automation, and systems 2012, Automation, and Systems, 10(5), , pp.1049-1054
Main Authors: Liu, Wei, Zhang, Huaguang, Wang, Zhanshan, Sun, Qiuye
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Automation
Control
Control systems
Control theory
Engineering
Estimates
Hypotheses
Information science
Kalman filters
Linear systems
Load
Markov analysis
Markov processes
Mean square errors
Mechatronics
Noise
Performance evaluation
Recursion theory
Recursive
Robotics
State estimation
Studies
Theorems
제어계측공학
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Summary:In this paper, state estimation problem for discrete-time Markov jump linear systems is considered. Based on orthogonal projective theorem, a novel suboptimal algorithm for state estimate of discrete-time Markov jump linear systems in the sense of minimum mean square error estimate is proposed. The proposed suboptimal algorithm is recursive and finite-dimensionally computable. Computer simulations are carried out to evaluate the performance of the proposed suboptimal algorithm.
ISSN:1598-6446
2005-4092
DOI:10.1007/s12555-012-0523-1