On the choice of inputs in identification for robust control

A. C. Antoulas*, B. D.O. Anderson

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    25 Citations (Scopus)

    Abstract

    The thesis that noisy identification has close ties to the study of the singular-value decomposition of perturbed matrices is investigated. In particular by assuming an upper bound on the norm of the perturbation, one can obtain a convex parametrization of an uncertain family of systems which contains the system generating the data. In this approach, the second-smallest singular value σ* of an appropriately defined data matrix becomes a quantity of importance as it provides an upper bound for the size of the uncertain family. This yields a new tool leading to the design of input functions which are optimal or persistently exciting from the point of view of identification for robust control.

    Original languageEnglish
    Pages (from-to)1009-1031
    Number of pages23
    JournalAutomatica
    Volume35
    Issue number6
    DOIs
    Publication statusPublished - Jun 1999

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