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Advances in the Control of Markov Jump Linear Systems with No Mode ObservationApproximation of the Optimal Long-Run Average-Cost Control Problem

Advances in the Control of Markov Jump Linear Systems with No Mode Observation: Approximation of... [This chapter presents conditions for which the optimal finite-stage cost, divided by the number of stages, converges to the optimal long-run average cost as the number of stages goes to infinity. The main condition is based on a controllability to the origin property. The discrete-time stochastic system is linear with respect to the system state but the control possess a general structure, possibly nonlinear. To illustrate the effectiveness of the result, an application to the simultaneous state-feedback control problem is considered.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Advances in the Control of Markov Jump Linear Systems with No Mode ObservationApproximation of the Optimal Long-Run Average-Cost Control Problem

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Publisher
Springer International Publishing
Copyright
© The Author(s) 2016. As it is a brief the author retains copyright.
ISBN
978-3-319-39834-1
Pages
35 –46
DOI
10.1007/978-3-319-39835-8_3
Publisher site
See Chapter on Publisher Site

Abstract

[This chapter presents conditions for which the optimal finite-stage cost, divided by the number of stages, converges to the optimal long-run average cost as the number of stages goes to infinity. The main condition is based on a controllability to the origin property. The discrete-time stochastic system is linear with respect to the system state but the control possess a general structure, possibly nonlinear. To illustrate the effectiveness of the result, an application to the simultaneous state-feedback control problem is considered.]

Published: May 28, 2016

Keywords: Control Problem; Markov Decision Process; Average Cost; Optimal Stationary Policy; Average Cost Optimality

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