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
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;
Conference_Titel :
American Control Conference, 2009. ACC '09.
Conference_Location :
St. Louis, MO
Print_ISBN :
978-1-4244-4523-3
Electronic_ISBN :
0743-1619
DOI :
10.1109/ACC.2009.5160687
