Optimal control for a class of stochastic hybrid systems

Ling Shi*, Alessandro Abate, Shankar Sastry

*Corresponding author for this work

Research output: Contribution to journalConference article published in journalpeer-review

8 Citations (Scopus)

Abstract

In this paper, an optimal control problem over a "hybrid Markov Chain" (hMC) is studied. A 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 non deterministic 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.

Original languageEnglish
Article numberWeB01.1
Pages (from-to)1842-1847
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
Volume2
Publication statusPublished - 2004
Externally publishedYes
Event2004 43rd IEEE Conference on Decision and Control (CDC) - Nassau, Bahamas
Duration: 14 Dec 200417 Dec 2004

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