Genetic algorithm and particle swarm optimization tuned fuzzy PID controller on direct torque control of dual star induction motor

Abstract

This study presents analysis, control and comparison of three hybrid approaches for the direct torque control (DTC) of the dual star induction motor (DSIM) drive. Its objective consists of combining three different heuristic optimization techniques including PID-PSO, Fuzzy-PSO and GA-PSO to improve the DSIM speed controlled loop behavior. The GA and PSO algorithms are developed and implemented into MATLAB. As a result, fuzzy-PSO is the most appropriate scheme. The main performance of fuzzy-PSO is reducing high torque ripples, improving rise time and avoiding disturbances that affect the drive performance.

Keywords

dual star induction motor drive / direct torque control / particle swarm optimization (PSO) / fuzzy logic control / genetic algorithms

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