Identification of Linear Switching System with Unknown Dimensions

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    2 Citations (Scopus)


    Switching systems have the property that their dynamical behavior may switch between a number of different modes. Identification of switching systems consists of identifying both the individual models which describe the system in the various modes, as well as the time instants when the mode changes have occurred. This soft computing problem therefore consists of numerically demanding coupled parameter identification and clustering problem. In this contribution a method based on sparse optimization techniques is proposed for identification of switching systems. In the two proposed methods, the modes and the associated models are determined one by one by solving linear problems which are sparse with respect to the number of violated epsilon-insensitive constraints and also solving by extending the models with an alternative LP-formulation of the optimization problem. The performance of the identification procedure is demonstrated by simulated examples.
    Original languageUndefined/Unknown
    Title of host publication47th Hawaii International Conference on System Sciences (HICSS)
    PublisherIEEE computer society press
    ISBN (Electronic)978-1-4799-2504-9
    ISBN (Print)978-1-4799-2505-6
    Publication statusPublished - 2014
    MoE publication typeA4 Article in a conference publication
    Eventconference; 2014-01-06; 2014-01-09 - Waikoloa, HI
    Duration: 6 Jan 20149 Jan 2014


    Conferenceconference; 2014-01-06; 2014-01-09


    • linear systems
    • optimisation
    • time-varying systems

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