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Transfer Function Parameter Interval Estimation Using Recursive Least Squares in the Time and Frequency Domains

In: Bounding Approaches to System Identification

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  • P.-O. Gutman

    (Technion—Israel Institute of Technology, Faculty of Agricultural Engineering)

Abstract

A bank of recursive least squares (RLS) estimators is proposed for the estimation of the uncertainty intervals of the parameters of an equation error model (or RLS model), where the equation error is assumed to lie between a known upper and lower bound. It is shown that the off-line least squares method gives the maximum and minimum parameter values that could have produced the recorded input-output sequence. By modifying the RLS estimator in two ways, it is possible to recursively compute inner and outer bounds of the uncertainty intervals. It is shown that the inner bound is asymptotically tight. It is demonstrated that transfer function parameter intervals can also be estimated, by applying the method to measured frequency function data.

Suggested Citation

  • P.-O. Gutman, 1996. "Transfer Function Parameter Interval Estimation Using Recursive Least Squares in the Time and Frequency Domains," Springer Books, in: Mario Milanese & John Norton & Hélène Piet-Lahanier & Éric Walter (ed.), Bounding Approaches to System Identification, chapter 7, pages 101-118, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4757-9545-5_7
    DOI: 10.1007/978-1-4757-9545-5_7
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