Least squares based modification for adaptive control

Girish Chowdhary, Eric Johnson

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

9 Scopus citations

Abstract

A least squares modification is presented to adaptive control problems where the uncertainty can be linearly parameterized. The modified weight training law uses an estimate of the ideal weights formed online by solving a least squares problem using recorded and current data concurrently. The modified adaptive law guarantees the exponential convergence of adaptive weights to their ideal values subject to a verifiable condition on linear independence of the recorded data. This condition is found to be less restrictive and easier to monitor than a condition on persistency of excitation of the reference signal.

Original languageEnglish (US)
Title of host publication2010 49th IEEE Conference on Decision and Control, CDC 2010
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1767-1772
Number of pages6
ISBN (Print)9781424477456
DOIs
StatePublished - 2010
Event49th IEEE Conference on Decision and Control, CDC 2010 - Atlanta, United States
Duration: Dec 15 2010Dec 17 2010

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Conference

Conference49th IEEE Conference on Decision and Control, CDC 2010
Country/TerritoryUnited States
CityAtlanta
Period12/15/1012/17/10

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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