Genetic and particle swarm optimization algorithms based direct torque control for torque ripple attenuation of induction motor

Elgbaily, Mohamed, Anayi, Fatih ORCID: https://orcid.org/0000-0001-8408-7673 and Packianather, Michael ORCID: https://orcid.org/0000-0002-9436-8206 2022. Genetic and particle swarm optimization algorithms based direct torque control for torque ripple attenuation of induction motor. Materials Today: Proceedings 67 (4) , pp. 577-590. 10.1016/j.matpr.2022.08.293

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Abstract

This paper introduces analysis, control, and comparison of two benchmarking optimization approaches called Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for Direct Torque Control (DTC) of a three-phase Induction Motor (IM). This study aims to determine the most efficient and robust of the two different metaheuristic optimization techniques including PID-PSO and PID-GA for DTC of IM. The purpose of the proposed control technique that has been presented is to get over the most significant drawback of DTC, which is a high level of torque output. The issue of torque ripples needs to be reduced to a significant amount using the two proposed control methods PSO-DTC and GA-DTC. As a result, PSO-DTC is the most applicable scheme. The proposed PID-PSO of DTC provided an excellent work performance for IM system drive. The comparison results of the suggested control methods showed a significant improvement of the control system compared to the classical DTC. The result is a high fidelity estimate of electromagnetic torque and speed for computation of motor parameters. A high ripple suppression capability was achieved by the PSO-DTC, which was measured at 22.5 % out of 47.28 % for the traditional approach. Both proposed control schemes were implemented using MATLAB/Simulink platform.

Item Type:	Article
Date Type:	Published Online
Status:	Published
Schools:	Engineering
Publisher:	Elsevier
ISSN:	2214-7853
Date of First Compliant Deposit:	27 September 2022
Last Modified:	26 May 2023 02:37
URI:	https://orca.cardiff.ac.uk/id/eprint/152344

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