An algorithm for generating transfer functions uniformly distributed over H balls

Constantino Manuel Lagoa, Mario Sznaier, B. Ross Barmish

    Research output: Contribution to journalConference article

    18 Scopus citations

    Abstract

    Probabilistic methods have recently been the subject of considerable attention in the context of robust performance assessment. However, in spite of their potential, these methods have been limited to the case of parametric uncertainty; the problem of sampling causal bounded operators is largely open. In this paper, we take steps towards removing this limitation by providing a computationally efficient algorithm aimed at uniform sampling over balls contained in suitably chosen proper subspaces of H. As shown in the paper, samples generated from these balls can be used, for instance by Monte Carlo methods, to assess robust performance for uncertainty models involving the H norm.

    Original languageEnglish (US)
    Pages (from-to)5038-5043
    Number of pages6
    JournalProceedings of the IEEE Conference on Decision and Control
    Volume5
    StatePublished - Dec 1 2001
    Event40th IEEE Conference on Decision and Control (CDC) - Orlando, FL, United States
    Duration: Dec 4 2001Dec 7 2001

    All Science Journal Classification (ASJC) codes

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

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