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    Optimal discrete-valued control computation

    199826_199826.pdf (182.9Kb)
    Access Status
    Open access
    Authors
    Yu, Changjun
    Li, B.
    Loxton, Ryan
    Teo, Kok Lay
    Date
    2013
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Yu, C. and Li, B. and Loxton, R. and Teo, K.L. 2013. Optimal discrete-valued control computation. Journal of Global Optimization. 56 (2): pp. 503-518.
    Source Title
    Journal of Global Optimization
    DOI
    10.1007/s10898-012-9858-7
    ISSN
    09255001
    School
    Department of Mathematics and Statistics
    Remarks

    The final publication is available at Springer via http://doi.org/10.1007/s10898-012-9858-7

    NOTICE: This is the author’s version of a work in which changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication.

    URI
    http://hdl.handle.net/20.500.11937/26225
    Collection
    • Curtin Research Publications
    Abstract

    In this paper, we consider an optimal control problem in which the control takes values from a discrete set and the state and control are subject to continuous inequality constraints. By introducing auxiliary controls and applying a time-scaling transformation, we transform this optimal control problem into an equivalent problem subject to additional linear and quadratic constraints. The feasible region defined by these additional constraints is disconnected, and thus standard optimization methods struggle to handle these constraints. We introduce a novel exact penalty function to penalize constraint violations, and then append this penalty function to the objective. This leads to an approximate optimal control problem that can be solved using standard software packages such as MISER. Convergence results show that when the penalty parameter is sufficiently large, any local solution of the approximate problem is also a local solution of the original problem. We conclude the paper with some numerical results for two difficult train control problems.

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