Recursively updated least squares based modification term for adaptive control

Girish Chowdhary, Eric Johnson

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

Abstract

We present an approach for combining standard recursive least squares based regression with proven direct model reference adaptive control using a recursively updated modification term. This approach is applicable to adaptive control problems where the uncertainty can be linearly parameterized. The combined training law drives the adaptive weights smoothly to a recursively updated least squares estimate of the ideal weights and is shown to have a stability proof. Expected improvement in performance of the adaptive law is validated through simulation.

Original languageEnglish (US)
Title of host publicationProceedings of the 2010 American Control Conference, ACC 2010
Pages892-897
Number of pages6
StatePublished - Oct 15 2010
Externally publishedYes
Event2010 American Control Conference, ACC 2010 - Baltimore, MD, United States
Duration: Jun 30 2010Jul 2 2010

Publication series

NameProceedings of the 2010 American Control Conference, ACC 2010

Other

Other2010 American Control Conference, ACC 2010
CountryUnited States
CityBaltimore, MD
Period6/30/107/2/10

ASJC Scopus subject areas

  • Control and Systems Engineering

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  • Cite this

    Chowdhary, G., & Johnson, E. (2010). Recursively updated least squares based modification term for adaptive control. In Proceedings of the 2010 American Control Conference, ACC 2010 (pp. 892-897). [5530475] (Proceedings of the 2010 American Control Conference, ACC 2010).