Title
State-feedback control of Markov jump linear systems with hidden-Markov mode observation.
Abstract
In this paper, we study state-feedback control of Markov jump linear systems with partial information about the mode signal responsible for switching between dynamic modes. We assume that the controller can only access random samples of the mode signal according to a hidden-Markov observation process. Our formulation provides a novel framework to analyze and design feedback control laws for various Markov jump linear systems previously studied in the literature, such as the cases of (i) clustered observations, (ii) detector-based observations, and (iii) periodic observations. We present a procedure to transform the closed-loop system with hidden-Markov observations into a standard Markov jump linear system while preserving stability, H2 norm, and H∞ norm. Furthermore, based on this transformation, we propose a set of Linear Matrix Inequalities (LMI) to design feedback control laws for stabilization, H2 suboptimal control, and H∞ suboptimal control of discrete-time Markov jump linear systems under hidden-Markov observations of the mode signals. We conclude by illustrating our results with some numerical examples.
Year
DOI
Venue
2018
10.1016/j.automatica.2017.11.022
Automatica
Keywords
Field
DocType
Markov chains,State-feedback control,Stabilization, H2 control, H∞ control
Control theory,Matrix (mathematics),Control theory,Mode (statistics),Markov chain,Norm (mathematics),Hidden Markov model,Detector,Periodic graph (geometry),Mathematics
Journal
Volume
Issue
ISSN
89
1
0005-1098
Citations 
PageRank 
References 
6
0.45
9
Authors
4
Name
Order
Citations
PageRank
Masaki Ogura14413.38
Ahmet Cetinkaya29213.36
Tomohisa Hayakawa338043.05
Victor M. Preciado420529.44