Vector Control of the Induction Motor Based on Whale Optimization Algorithm

Abstract

This paper presents the Whale Optimizing Algorithm (WOA) to improve the performance of the induction motors through vector control (VC). The optimization algorithm is utilized to tune the proportional-integral (PI) controllers in both the outer and inner controlling loops. The parameters of these controllers are crucial components of the control system. The WOA is inspired by the social behavior of humpback whales, which is a powerful meta-heuristic algorithm as compared to other techniques. The controlling system and the WOA are implemented using MATLAB-SIMULINK environments. Simulation results demonstrate that this approach significantly improves both dynamic and steady-state responses of the induction motor compared to other optimization techniques. Simultaneously, the success of the WOA in reaching the global optimal parameters can be realized by the significant reduction in computation time and iterations as compared to other methods. The results show a considerable enhancement of about 2% in rise time, 30% in overshoot, and 60% in settling time in accelerating mode in conjunction with a reference case. Also, it gives an improvement of about 9% in rise time, 11% in overshoot, and 64% in settling time in step response. This research contributes to the field of motor control by providing an efficient and reliable optimization method for enhancing the performance of induction motors for various industrial applications.