Asymptotic performance guarantees in adaptive control

Konstantinos Tsakalis, Suttipan Limanond

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

In this paper we address the problem of improving the asymptotic performance guarantees of a class of model reference adaptive controllers under insufficient excitation and in the presence of perturbations such as non‐parametric uncertainty and bounded disturbances. We show that for a class of perturbations whose normalized effect is bounded by an a priori known function of time an estimate of the parametric uncertainty set can be obtained on‐line via a set membership estimator. Furthermore, by incorporating this estimate as an additional constraint in the adaptive law generating the controller parameters, we show that the resulting adaptive controller offers dead‐zone‐like performance guarantees in the lim‐sup sense while preserving the desirable root‐mean‐square performance guarantees of gradient‐based algorithms.

Original languageEnglish (US)
Pages (from-to)173-199
Number of pages27
JournalInternational Journal of Adaptive Control and Signal Processing
Volume8
Issue number2
DOIs
StatePublished - 1994

Keywords

  • Lim‐sup performance
  • Model reference adaptive control
  • Parameter projection
  • Root‐mean‐square performance
  • Set membership estimation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Electrical and Electronic Engineering

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