DocumentCode
2477952
Title
An algorithm for the long run average cost problem for linear systems with non-observed Markov jump parameters
Author
Silva, Carlos A. ; Costa, Eduardo F.
Author_Institution
Depto. de Mat. Aplic. e Estatistica, Univ. de Sao Paulo, Sao Carlos, Brazil
fYear
2009
fDate
10-12 June 2009
Firstpage
4434
Lastpage
4439
Abstract
This paper addresses the problem of long run average cost for linear systems with non-observed Markov jump parameters. We present an algorithm that relies on the approximation of the (infinite horizon) cost via its finite horizon version and uses an evolutionary-based algorithm for the finite horizon cost. A numerical example illustrates the proposed algorithm.
Keywords
Markov processes; discrete time systems; genetic algorithms; infinite horizon; linear systems; minimisation; approximation algorithm; discrete-time linear system; evolutionary-based genetic algorithm; infinite horizon cost; long run average cost minimization problem; nonobserved Markov jump parameter; Additive noise; Approximation algorithms; Control systems; Cost function; Filtering; Genetic algorithms; Infinite horizon; Linear systems; Riccati equations; Stability;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 2009. ACC '09.
Conference_Location
St. Louis, MO
ISSN
0743-1619
Print_ISBN
978-1-4244-4523-3
Electronic_ISBN
0743-1619
Type
conf
DOI
10.1109/ACC.2009.5160687
Filename
5160687
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