• 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