• DocumentCode
    836988
  • Title

    Perturbation analysis of a system of quasi-variational inequalities for optimal stochastic scheduling

  • Author

    Hopkins, William E., Jr. ; Blankenship, Gilmer L.

  • Author_Institution
    University of Maryland, College Park, MD, USA
  • Volume
    26
  • Issue
    5
  • fYear
    1981
  • fDate
    10/1/1981 12:00:00 AM
  • Firstpage
    1054
  • Lastpage
    1070
  • Abstract
    Optimal scheduling of continuously evolving dynamical systems involves the analysis of certain partial differential inequalities on solution dependent domains. These are the "quasi-variatlonai inequalities" (QVI\´s) introduced for such problems by A. Bensoussan and J. L. Lions. They arise naturally in such applications as inventory control and unit commitment scheduling in electric energy systems. QVI\´s are, in these contexts, the analog of the dynamic programming partial differential equations of R. Bellman for continuous control problems. Analytical treatment of QVI\´s involves not only the solution of partial differential inequalities, but also the simultaneous analysis of the "free" boundaries of the domain of the solution. In effect, the optimal return function is the solution of the inequalities, and the optimal control/switching policy is defined by the free boundaries. This paper considers a system of two singularly perturbed, second-order, quasi-variational inequalities with a turning point in a bounded domain in R1. Asymptotic approximations for the free boundaries are derived using standard perturbation analysis for boundary value problems. Also, local regularity properties of the limit solution are obtained. The results are illustrated by a parametric study of a simple model of commitment scheduling for a single unit in a power generation system.
  • Keywords
    Optimal stochastic control; Perturbation methods; Scheduling; Singularly perturbed systems; Stochastic optimal control; Switched systems; Variational methods; Boundary value problems; Dynamic programming; Inventory control; Optimal control; Optimal scheduling; Parametric study; Partial differential equations; Power system modeling; Stochastic systems; Turning;
  • fLanguage
    English
  • Journal_Title
    Automatic Control, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9286
  • Type

    jour

  • DOI
    10.1109/TAC.1981.1102779
  • Filename
    1102779