Finding an LFT uncertainty model with minimal uncertainty

    Tutkimustuotos: Artikkeli kirjassa/raportissa/konferenssijulkaisussaKonferenssiartikkeliTieteellinenvertaisarvioitu

    1 Lataukset (Pure)

    Abstrakti

    In this paper, we present a procedure for finding the best LFT uncertainty model by minimizing the H-infinity norm of the uncertainty set with respect to a nominal model subject to known input-output data. The main problem is how to express the data-matching constraints for convenient use in the optimization problem. For some uncertainty structures, they can readily be formulated as a set of linear matrix inequalities (LMIs), for some other structures, LMIs are obtained after certain transformations. There are also cases, when the constraints result in bilinear matrix inequalities (BMIs), which can be linearized to enable an efficient iterative solution. Essentially all LFT uncertainty structures are considered. An application to distillation modeling is included.

    AlkuperäiskieliEi tiedossa
    Otsikko2013 European Control Conference (ECC)
    KustantajaIEEE
    Sivut1107–1113
    ISBN (elektroninen)978-3-033-03962-9
    ISBN (painettu)978-3-9524173-4-8
    DOI - pysyväislinkit
    TilaJulkaistu - 2013
    OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
    TapahtumaEuropean Control Conference (ECC) - 2013 European Control Conference
    Kesto: 17 heinäkuuta 201319 heinäkuuta 2013

    Konferenssi

    KonferenssiEuropean Control Conference (ECC)
    Ajanjakso17/07/1319/07/13

    Keywords

    • Data models
    • Linear matrix inequalities
    • Mathematical model
    • Optimization
    • Transfer functions
    • Uncertainty

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