Stochastic adaptive switching control based on multiple models

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

It is well known that the transient behaviors of the traditional adaptive control may be very poor in general, and that the adaptive control designed based on switching between multiple models is an intuitively appealing and practically feasible approach to improve the transient performances. This paper proves that for a typical class of linear systems disturbed by white noises, the multiple model based least-squares (LS) adaptive switching control is stable and convergent, and has the same convergence rate as that established for the standard least-squares-based self-tuning regulators. Moreover, the mixed case combining adaptive models with fixed models is also considered.

Original languageEnglish
Title of host publicationIFAC Proceedings Volumes (IFAC-PapersOnline)
EditorsGabriel Ferrate, Eduardo F. Camacho, Luis Basanez, Juan. A. de la Puente
PublisherIFAC Secretariat
Pages91-96
Number of pages6
Edition1
ISBN (Print)9783902661746
DOIs
Publication statusPublished - 2002
Externally publishedYes
Event15th World Congress of the International Federation of Automatic Control, 2002 - Barcelona, Spain
Duration: 21 Jul 200226 Jul 2002

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
Number1
Volume15
ISSN (Print)1474-6670

Conference

Conference15th World Congress of the International Federation of Automatic Control, 2002
Country/TerritorySpain
CityBarcelona
Period21/07/0226/07/02

Keywords

  • Adaptive control
  • Convergence rate
  • Least-Squares
  • Multiple models
  • Optimality
  • Switching

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