Optimized Angular Position Control of Brushless DC Motor Using Imperialist Competitive Algorithm Based on FOC and Trapezoidal Control

Mohammad Vedadi, Ahmed Ibrahim Soliman, Ralph Kennel

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

Abstract

In this study, the Imperialist Competitive Algorithm (ICA) is used to optimize the gains of the cascaded position controller. Brushless DC (BLDC) motor drives with FOC and trapezoidal control structure are implemented in Simulink environment to provide an evaluation function of ICA. In this paper, a brief discussion has been conducted regarding the selection of settings and coefficients of ICA. Simulation results show that the optimized speed and position controller tracks the target speed and target position appropriately. Also, the effectiveness of ICA is verified by performance comparison of ICA, PSO, and GA in this paper.

Original languageEnglish
Title of host publication2021 23rd European Conference on Power Electronics and Applications, EPE 2021 ECCE Europe
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9789075815375
DOIs
StatePublished - 6 Sep 2021
Event23rd European Conference on Power Electronics and Applications, EPE 2021 ECCE Europe - Ghent, Belgium
Duration: 6 Sep 202110 Sep 2021

Publication series

Name2021 23rd European Conference on Power Electronics and Applications, EPE 2021 ECCE Europe

Conference

Conference23rd European Conference on Power Electronics and Applications, EPE 2021 ECCE Europe
Country/TerritoryBelgium
CityGhent
Period6/09/2110/09/21

Keywords

  • Artificial intelligence
  • Brushless drive
  • Control of drive
  • Electrical drive
  • Motion control

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