Input design to maximize information for identification of MIMO systems

    Research output: Chapter in Book/Conference proceedingConference contributionScientificpeer-review

    2 Citations (Scopus)

    Abstract

    A new input design method for identification of multiple-input multiple-output (MIMO) systems is introduced. The method is completely data based as opposed to previous model-based methods. The data are obtained from one or more experiments with the system to be identified. These experiments do not require any MIMO input design. The design objective is to generate maximally informative data when a new experiment based on MIMO input design is done. The data are considered to be maximally informative when the outputs have maximal variance, subject to some constraints, and no correlation. Since the input design, with given type of perturbation signal, is not unique, it is possible to optimize some additional property, such as minimization of input or output peak value. The various design options are illustrated by application to a system with three inputs and three outputs.

    Original languageUndefined/Unknown
    Title of host publication2019 12th Asian control conference (ASCC)
    PublisherIEEE
    Pages1323–1328
    ISBN (Electronic)978-4-88898-300-6
    ISBN (Print)978-1-7281-0263-4
    Publication statusPublished - 2019
    MoE publication typeA4 Article in a conference publication
    EventAsian Control Conference - 12th Asian Control Conference (ASCC 2019)
    Duration: 9 Jun 201912 Jun 2019

    Conference

    ConferenceAsian Control Conference
    Period09/06/1912/06/19

    Keywords

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

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