Stochastic disturbance rejection in model predictive control by randomized algorithms

Ivo Batina, Antonie Arij Stoorvogel, Siep Weiland

    Research output: Contribution to conferencePaper

    19 Citations (Scopus)
    55 Downloads (Pure)

    Abstract

    In this paper we consider model predictive control with stochastic disturbances and input constraints. We present an algorithm which can solve this problem approximately but with arbitrary high accuracy. The optimization at each time step is a closed loop optimization and therefore takes into account the effect of disturbances over the horizon in the optimization. Via an example it is shown that this gives a clear improvement of performance although at the expense of a large computational effort.
    Original languageEnglish
    Pages732-737
    Number of pages6
    DOIs
    Publication statusPublished - 2001
    Event2001 American Control Conference, ACC 2001 - Arlington, United States
    Duration: 25 Jun 200127 Jun 2001

    Conference

    Conference2001 American Control Conference, ACC 2001
    Abbreviated titleACC
    CountryUnited States
    CityArlington
    Period25/06/0127/06/01

    Keywords

    • EWI-16638
    • IR-68911

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  • Cite this

    Batina, I., Stoorvogel, A. A., & Weiland, S. (2001). Stochastic disturbance rejection in model predictive control by randomized algorithms. 732-737. Paper presented at 2001 American Control Conference, ACC 2001, Arlington, United States. https://doi.org/10.1109/ACC.2001.945802