Adaptive control of a DC motor based on swarm intelligence

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1 Scopus citations

Abstract

The effect of uncertainties in the stabilization of the velocity control of a DC motor is compensated by proposing an adaptive control based on Particle Swarm Optimization (ACPSO). The ACPSO is based on an on-line dynamic optimization problem with dynamic constraints. The empirical analysis based on modifying the inertia weight of the ACPSO indicates that it can effectively regulate the motor's velocity and hence the ACPSO can be another alternative to control the DC motor under parametric uncertainties. Simulation results verify the proposed approach.

Original languageEnglish
Title of host publicationProceedings - 2015 International Conference on Computational Science and Computational Intelligence, CSCI 2015
EditorsQuoc-Nam Tran, Leonidas Deligiannidis, Hamid R. Arabnia
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages192-197
Number of pages6
ISBN (Electronic)9781467397957
DOIs
StatePublished - 2 Mar 2016
EventInternational Conference on Computational Science and Computational Intelligence, CSCI 2015 - Las Vegas, United States
Duration: 7 Dec 20159 Dec 2015

Publication series

NameProceedings - 2015 International Conference on Computational Science and Computational Intelligence, CSCI 2015

Conference

ConferenceInternational Conference on Computational Science and Computational Intelligence, CSCI 2015
Country/TerritoryUnited States
CityLas Vegas
Period7/12/159/12/15

Keywords

  • Adaptive control
  • DC motor
  • Heuristic algorithms
  • Particle swarm optimization

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