A model predictive control approach for stochastic networked control systems

D. Bernardini, M.C.F. Donkers, A. Bemporad, W.P.M.H. Heemels

    Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

    8 Citaten (Scopus)
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    Samenvatting

    In this paper we present a stochastic model predictive control (SMPC) approach for networked control systems (NCSs) that are subject to time-varying sampling intervals and timevarying transmission delays. These network-induced uncertain parameters are assumed to be described by random processes, having a bounded support and an arbitrary continuous probability density function. Assuming that the controlled plant can be modeled as a linear system, we present a SMPC formulation based on scenario enumeration and quadratic programming that optimizes a stochastic performance index and provides closed-loop stability in the mean-square sense. Simulation results are shown to demonstrate the performance of the proposed approach.
    Originele taal-2Engels
    TitelProceedings of the 2nd IFAC Workshop on Estimation and Control of Networked Systems
    Plaats van productieFrance, Annecy
    Pagina's7-12
    StatusGepubliceerd - 2010

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  • Citeer dit

    Bernardini, D., Donkers, M. C. F., Bemporad, A., & Heemels, W. P. M. H. (2010). A model predictive control approach for stochastic networked control systems. In Proceedings of the 2nd IFAC Workshop on Estimation and Control of Networked Systems (blz. 7-12).