Genetic Algorithm Optimized Direct Torque Control of Mathematically Modeled Induction Motor Drive Using PI and Sliding Mode Controller

Abstract

This research introduces a genetic algorithm optimization control technique to conventional PI controller that merges with the sliding mode control strategy for direct torque control in induction motor drive. This technique controls the rapid variation in motor speed to the optimum reference parameter for smooth operations. Here, genetic algorithm used for the tuning of PI control gains to get faster response toward steady state. Sliding mode controller is used to remove uncertainties due to sudden variations in motor speed which regulated in associated with the PI and GA. This complex controller helps in getting the full control on torque with switching converters and gets accurate outputs with respect to the reference parameters. The model is designed in MATLAB Simulink and genetic algorithm codes. Results indicate that the conventional PI controller gives fast steady state at normal operating conditions but the proposed technique of PI-SMC-GA is more effective and faster in variance and stability. ITAE from the different operating conditions is demonstrated in this paper and the results are compared according to the Simulink results.