An efficient atomic norm minimization approach to identification of low order models

B. Yilmaz, C. Lagoa, M. Sznaier

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    11 Scopus citations

    Abstract

    Many practical situations involve synthesizing controllers for systems where a priori models are not available and thus must be identified from experimental data. In these cases it is of interest to identify the simplest model compatible with the available information, since the order of the model is usually reflected in the order of the resulting controllers. The main result of this paper is a computationally efficient algorithm to identify low order models from mixed time/frequency domain data. We propose two algorithms: one deterministic, based on semi-algebraic optimization, and the second based on a randomized approach. As shown here, both algorithms are guaranteed to converge to the optimum. A salient feature of the proposed approach is its ability to accommodate mixed time/frequency domain data without the need to resort to finite truncations or enforcing interpolation type constraints.

    Original languageEnglish (US)
    Title of host publication2013 IEEE 52nd Annual Conference on Decision and Control, CDC 2013
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages5834-5839
    Number of pages6
    ISBN (Print)9781467357173
    DOIs
    StatePublished - 2013
    Event52nd IEEE Conference on Decision and Control, CDC 2013 - Florence, Italy
    Duration: Dec 10 2013Dec 13 2013

    Publication series

    NameProceedings of the IEEE Conference on Decision and Control
    ISSN (Print)0191-2216

    Other

    Other52nd IEEE Conference on Decision and Control, CDC 2013
    Country/TerritoryItaly
    CityFlorence
    Period12/10/1312/13/13

    All Science Journal Classification (ASJC) codes

    • Control and Systems Engineering
    • Modeling and Simulation
    • Control and Optimization

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