Recursively updated least squares based modification term for adaptive control

Girish Chowdhary, Eric Johnson

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

13 Scopus citations

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
PublisherIEEE Computer Society
Pages892-897
Number of pages6
ISBN (Print)9781424474264
DOIs
StatePublished - Jan 1 2010

Publication series

NameProceedings of the 2010 American Control Conference, ACC 2010

All Science Journal Classification (ASJC) codes

  • 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). IEEE Computer Society. https://doi.org/10.1109/acc.2010.5530475