Development of a recursive algorithm for parameter uncertainty interval estimation

Antonios Tzes, Qingyang Hu, Ke Le

    Research output: Contribution to journalConference article

    Abstract

    This article addresses the problem of recursively estimating the parameter uncertainty intervals for a linear discrete system, whose output measurements are contaminated with noise. The estimator provides the maximally tight bounding rectangular hyperparallepiped, whose vertices are computed in an optimal manner so as to contain all parameter values consistent with the system structure and the l1 norm of the error bounds. The proposed method relies on a recursive formulation of the underlying posed linear programming problem in [1], by exploring its distinct structure. The computational effort associated with the finding of this optimal outer box is minimal. A recursive algorithm is presented for the cases of an increasing, and a fixed size sample time-sliding window. Simulation studies are included to highlight the algorithm's performance.

    Original languageEnglish (US)
    Pages (from-to)3010-3015
    Number of pages6
    JournalProceedings of the IEEE Conference on Decision and Control
    Volume3
    StatePublished - Dec 1 1995
    EventProceedings of the 1995 34th IEEE Conference on Decision and Control. Part 1 (of 4) - New Orleans, LA, USA
    Duration: Dec 13 1995Dec 15 1995

    Fingerprint

    Uncertainty Estimation
    Interval Estimation
    Recursive Algorithm
    Parameter Uncertainty
    L1-norm
    Sliding Window
    Time Windows
    Discrete Systems
    Linear programming
    Error Bounds
    Sample Size
    Linear Systems
    Simulation Study
    Distinct
    Estimator
    Interval
    Formulation
    Output
    Uncertainty

    ASJC Scopus subject areas

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

    Cite this

    Development of a recursive algorithm for parameter uncertainty interval estimation. / Tzes, Antonios; Hu, Qingyang; Le, Ke.

    In: Proceedings of the IEEE Conference on Decision and Control, Vol. 3, 01.12.1995, p. 3010-3015.

    Research output: Contribution to journalConference article

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