Dual self-tuning parameter-robust minimax output regulation of a first-order process with ellipsoidal uncertainty

P. Lohnberg*, Jan W. Polderman, R. Eisenberg

*Corresponding author for this work

    Research output: Contribution to journalConference articleAcademicpeer-review

    Abstract

    The parameters of a first-order process with known disturbance bounds are known to lie in an ellipsoidal region. At each sample, a static output feedback is designed which minimizes the maximum absolute output over the disturbance and parameter ranges. Then from the resulting measurements, the ellipsoid is updated according to a specific criterion. This criterion should be chosen for adequate performance of the resulting selftuning regulator. It is shown that a dual criterion minimizing a weighted sum of ellipsoidal volume and control performance outperforms these separate criteria.
    Original languageEnglish
    Pages (from-to)1489-1494
    Number of pages6
    JournalIFAC proceedings volumes
    Volume30
    Issue number11
    DOIs
    Publication statusPublished - 8 Jul 1997
    EventIFAC Symposium on System Identification, SYSID 1997 - Kitakyushu, Fukuoka, Japan
    Duration: 8 Jul 199711 Jul 1997

    Keywords

    • Self-tuning regulator
    • Bounded disturbance
    • Constrained parameters
    • Membership functions
    • Robust control
    • Closed-loop identification
    • Optimal estimation
    • Duality
    • Convergence analysis

    Fingerprint Dive into the research topics of 'Dual self-tuning parameter-robust minimax output regulation of a first-order process with ellipsoidal uncertainty'. Together they form a unique fingerprint.

  • Cite this