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

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