Average optimal stationary policies: convexity and convergence conditions in linear stochastic control systems

Author

Vargas, Alessandro N. ; Val, João B R do

Author_Institution

Univ. Tecnol. Fed. do Parana, Cornelio Procopio, Brazil

fYear

2009

fDate

15-18 Dec. 2009

Firstpage

3388

Lastpage

3393

Abstract

This paper provides a set of conditions for the existence of an optimal stationary policy in the long-run average cost control problem of linear stochastic systems. The main conditions are based on convexity of the cost by stage and convergence of trajectories. The discrete-time system is assumed to be linear with respect to the state but the controls take an abstract state-feedback structure, possibly a nonlinear one. An application is considered to illustrate the derived theory.

Keywords

convergence; discrete time systems; linear systems; state feedback; stochastic systems; abstract state-feedback structure; average optimal stationary policies; convergence condition; convexity condition; discrete-time system; linear stochastic control systems; long-run average cost control problem; Control systems; Controllability; Convergence; Cost function; Covariance matrix; Nonlinear control systems; Optimal control; Stability; Stochastic systems; Symmetric matrices; Markov processes; discrete-time systems; feedback control; optimal stochastic control;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on

Conference_Location

Shanghai

ISSN

0191-2216

Print_ISBN

978-1-4244-3871-6

Electronic_ISBN

0191-2216

Type

conf

DOI

10.1109/CDC.2009.5400501

Filename

5400501