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

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

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.

OriginalspracheEnglisch
Titel2021 23rd European Conference on Power Electronics and Applications, EPE 2021 ECCE Europe
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
ISBN (elektronisch)9789075815375
DOIs
PublikationsstatusVeröffentlicht - 6 Sept. 2021
Veranstaltung23rd European Conference on Power Electronics and Applications, EPE 2021 ECCE Europe - Ghent, Belgien
Dauer: 6 Sept. 202110 Sept. 2021

Publikationsreihe

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

Konferenz

Konferenz23rd European Conference on Power Electronics and Applications, EPE 2021 ECCE Europe
Land/GebietBelgien
OrtGhent
Zeitraum6/09/2110/09/21

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