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Average Cost Markov Decision Processes with Semi-Uniform Feller Transition Probabilities Read chapter Read first chapter

2021 | OriginalPaper | Chapter

Control of Continuous-Time Markov Jump Linear Systems with Partial Information

Authors : André Marcorin de Oliveira, Oswaldo Luiz do Valle Costa

Published in: Modern Trends in Controlled Stochastic Processes:

Publisher: Springer International Publishing

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Abstract

In this paper we study the \(H_2\) state-feedback control of continuous-time Markov jump linear systems considering that the mode of operation cannot be directly measured. Instead we assume that there is a detector that provides the only information concerning the main jump process, so that the jump processes are modelled by a continuous-time exponential hidden Markov model. We present a new convex design condition for calculating a state-feedback controller depending only on the detector which guarantees stability in the mean-square sense of the closed-loop system, as well as a suitable bound on its \(H_2\) norm. We present an illustrative example in the context of systems subject to faults and compare our results with the current literature.

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previous chapter Optimal Stopping Problems for a Family of Continuous-Time Markov Processes
next chapter Q-Learning for Distributionally Robust Markov Decision Processes
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Metadata
Title
Control of Continuous-Time Markov Jump Linear Systems with Partial Information
Authors
André Marcorin de Oliveira
Oswaldo Luiz do Valle Costa
Copyright Year
2021
Book
Modern Trends in Controlled Stochastic Processes:

Print ISBN: 978-3-030-76927-7

Electronic ISBN: 978-3-030-76928-4

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-76928-4_5

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