Stochastic extremum seeking in the presence of constraints

Fernando José Almeida Vieira do Coito, João M. Lemos, S. S. Alves

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9 Citations (Scopus)

Abstract

The problem of adaptive minimization of globally unknown functions under constraints on the independent variable is considered in a stochastic framework. The main contribution of this paper consists in the extension of the CAM algorithm to vector problems. By resorting to the ODE analysis for analyzing stochastic algorithms and singular perturbation methods, it is shown that the only possible convergence points in the vector case are the constrained local minima. Simulations for dimension 2 problems illustrate this result.

Original languageEnglish
Title of host publicationProceedings of the 16th IFAC World Congress, IFAC 2005
PublisherIFAC Secretariat
Pages276-281
Number of pages6
Edition1
ISBN (Print)008045108X, 9780080451084
DOIs
Publication statusPublished - 2005
Event16th Triennial World Congress of International Federation of Automatic Control, IFAC 2005 - Prague, Czech Republic
Duration: 3 Jul 20058 Jul 2005

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
Number1
Volume38
ISSN (Print)1474-6670

Conference

Conference16th Triennial World Congress of International Federation of Automatic Control, IFAC 2005
Country/TerritoryCzech Republic
CityPrague
Period3/07/058/07/05

Keywords

  • Adaptive control
  • Constraint satisfaction
  • Convergence analysis
  • Optimal search techniques
  • Singular perturbation method

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