Robust LMIs with polynomial dependence on the uncertainty

F. Dabbene, C. Feng, C. Lagoa

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

    1 Scopus citations

    Abstract

    Solving robust Linear Matrix Inequalities (LMIs) has long been recognized as an important problem in robust control. Although the solution to this problem is well-known for the case of affine dependence on the uncertainty, to the best of our knowledge, results for other types of dependence are limited. In this paper we address the the problem of solving robust LMIs for the case of polynomial dependence on the uncertainty. More precisely, results from numerical integration of polynomial functions are used to develop procedures to minimize the volume of the set of uncertain parameters for which the LMI condition is violated.

    Original languageEnglish (US)
    Title of host publicationProceedings of the 46th IEEE Conference on Decision and Control 2007, CDC
    Pages5646-5651
    Number of pages6
    DOIs
    StatePublished - Dec 1 2007
    Event46th IEEE Conference on Decision and Control 2007, CDC - New Orleans, LA, United States
    Duration: Dec 12 2007Dec 14 2007

    Publication series

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

    Other

    Other46th IEEE Conference on Decision and Control 2007, CDC
    CountryUnited States
    CityNew Orleans, LA
    Period12/12/0712/14/07

    All Science Journal Classification (ASJC) codes

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

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  • Cite this

    Dabbene, F., Feng, C., & Lagoa, C. (2007). Robust LMIs with polynomial dependence on the uncertainty. In Proceedings of the 46th IEEE Conference on Decision and Control 2007, CDC (pp. 5646-5651). [4434526] (Proceedings of the IEEE Conference on Decision and Control). https://doi.org/10.1109/CDC.2007.4434526