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Control of singularly perturbed Markov chains: A numerical study

Published online by Cambridge University Press:  17 February 2009

H. Yang
Affiliation:
Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN 55455, USA; e-mail: hyang@ece.umn.edu.
G. Yin
Affiliation:
Department of Mathematics, Wayne State University, Detroit, MI 48202, USA; e-mail: gyin@math.wayne.edu.
K. Yin
Affiliation:
Department of Wood and Paper Science, University of Minnesota, St. Paul, MN 55108, USA.
Q. Zhang
Affiliation:
Department of Mathematics University of Georgia, Athens, GA 30602, USA.
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Abstract

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This work is devoted to numerical studies of nearly optimal controls of systems driven by singularly perturbed Markov chains. Our approach is based on the ideas of hierarchical controls applicable to many large-scale systems. A discrete-time linear quadratic control problem is examined. Its corresponding limit system is derived. The associated asymptotic properties and near optimality are demonstrated by numerical examples. Numerical experiments for a continuous-time hybrid linear quadratic regulator with Gaussian disturbances and a discrete-time Markov decision process are also presented. The numerical results have not only supported our theoretical findings but also provided insights for further applications.

Type
Research Article
Copyright
Copyright © Australian Mathematical Society 2003

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