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Design of adaptive laws for discrete-time systems based on Particle Swarm Optimization

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

1 Scopus citations

Abstract

A wide variety of linear/nonlinear adaptive systems in continuous/discrete time can be represented by error models, thus facilitating their analysis. The solution obtained for a given error model can be applied to different systems represented by the error model. This paper presents a methodology for adjusting the parameters of a discrete-time adaptive system represented by a Type 1 Error Model, which is based on Particle Swarm Optimization (PSO) and that allows using it in on-line applications. The performance of the proposed methodology is compared with the traditional gradient and least squares methods through simulations.

Original languageEnglish
Title of host publication2011 9th IEEE International Conference on Control and Automation, ICCA 2011
Pages883-888
Number of pages6
DOIs
StatePublished - 2011
Externally publishedYes
Event9th IEEE International Conference on Control and Automation, ICCA 2011 - Santiago, Chile
Duration: 19 Dec 201121 Dec 2011

Publication series

NameIEEE International Conference on Control and Automation, ICCA
ISSN (Print)1948-3449
ISSN (Electronic)1948-3457

Conference

Conference9th IEEE International Conference on Control and Automation, ICCA 2011
Country/TerritoryChile
CitySantiago
Period19/12/1121/12/11

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