DocumentCode :
435178
Title :
Optimal control for a class of stochastic hybrid systems
Author :
Shi, Ling ; Abate, Alessandro ; Sastry, Shankar
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley, CA, USA
Volume :
2
fYear :
2004
fDate :
14-17 Dec. 2004
Firstpage :
1842
Abstract :
In this paper, an optimal control problem over a "hybrid Markov chain" (HMC) is studied. An HMC can be thought of as a traditional MC with continuous time dynamics pertaining to each node; from a different perspective, it can be regarded as a class of hybrid system with random discrete switches induced by an embedded MC. As a consequence of this setting, the index to be maximized, which depends on the dynamics, is the expected value of a nondeterministic cost function. After obtaining a closed form for the objective function, we gradually suggest how to device a computationally tractable algorithm to get to the optimal value. Furthermore, the complexity and rate of convergence of the algorithm is analyzed. Proofs and simulations of our results are provided; moreover, an applicative and motivating example is introduced.
Keywords :
Markov processes; convergence; optimal control; stochastic systems; algorithm convergence; computationally tractable algorithm; continuous time dynamics; hybrid Markov chain; hybrid system; nondeterministic cost function; optimal control; random discrete switches; stochastic hybrid systems; Algorithm design and analysis; Computational modeling; Convergence; Cost function; Differential equations; Linear systems; Optimal control; Stochastic processes; Stochastic systems; Switches;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 2004. CDC. 43rd IEEE Conference on
ISSN :
0191-2216
Print_ISBN :
0-7803-8682-5
Type :
conf
DOI :
10.1109/CDC.2004.1430315
Filename :
1430315
Link To Document :
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