Experiment designs to minimize input peak and crest factor in MIMO system identification

    Tutkimustuotos: Artikkeli kirjassa/raportissa/konferenssijulkaisussaKonferenssiartikkeliTieteellinenvertaisarvioitu

    2 Sitaatiot (Scopus)

    Abstrakti

    The quality of the data for system identification is of utmost of importance. Ideally, the output data should satisfy requirements regarding variance, and in the case of multiple-input multiple-output (MIMO) systems, correlation between the outputs. Usually, it is desired to achieve this by input perturbations with peak values as small as possible. A related measure is the crest factor, which is a measure of the (inverse) power of an input perturbation with given peak value. In this paper, the effect of minimizing the input peak and the crest factor, subject to desired output variances/covariances, is studied for various types of perturbation signals. The design procedure is completely data based; data are obtained by one or more preliminary experiments with the system to be identified. A model of an ill-conditioned distillation column is used for illustration.

    AlkuperäiskieliEi tiedossa
    OtsikkoIEEE CCTA 2019 : 3rd IEEE conference on control technology and applications : August 19-21, 2019, City University of Hong Kong, Hong Kong, China
    KustantajaIEEE
    Sivut499–504
    ISBN (painettu)978-1-7281-2767-5
    DOI - pysyväislinkit
    TilaJulkaistu - 2019
    OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
    TapahtumaIEEE Conference on Control Technology and Applications - 3rd IEEE Conference on Control Technology and Applications (IEEE CCTA 2019)
    Kesto: 19 elokuuta 201921 elokuuta 2019

    Konferenssi

    KonferenssiIEEE Conference on Control Technology and Applications
    Ajanjakso19/08/1921/08/19

    Keywords

    • data-based design
    • experiment design
    • ill-conditioned systems
    • multivariable systems
    • system identification

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