Performance limitations of adaptive parameter estimation and system identification algorithms in the absence of excitation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

In this paper we address the problem of fundamental performance limitations in adaptive parameter estimation and system identification, occurring in environments where perturbations are present but there is lack of sufficient excitation. We construct a simple but general bursting scenario to derive an analytical lower bound on the worst-case lim sup performance of a wide class of parameter estimation and system identification algorithms. Our results show that in the absence of any excitation or other input constraints, arbitrarily small perturbations impose a serious limitation on the lim sup performance of these adaptive algorithms, in the sense that the worst-case performance deteriorates proportionally with the size of the parametric uncertainty set. Furthermore, this performance limitation is a consequence of some fairly general properties of adaptive algorithms and independent of their precise form.

Original languageEnglish (US)
Title of host publicationProceedings of the American Control Conference
PublisherAmerican Automatic Control Council
Pages1260-1264
Number of pages5
Volume2
StatePublished - 1994
EventProceedings of the 1994 American Control Conference. Part 1 (of 3) - Baltimore, MD, USA
Duration: Jun 29 1994Jul 1 1994

Other

OtherProceedings of the 1994 American Control Conference. Part 1 (of 3)
CityBaltimore, MD, USA
Period6/29/947/1/94

ASJC Scopus subject areas

  • Control and Systems Engineering

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