Optimal Fractional Order Proportional Integral Controller for Dual Star Induction Motor Based on Particle Swarm Optimization Algorithm

Abstract

The purpose of this paper is to improve the performance of the conventional direct torque control (DTC) method of a dual star induction motor (DSIM) by enhancing speed control and reducing the ripples of electromagnetic torque and stator current. To achieve this, we propose a new optimal tuned controller based on the combination of a fractional order proportional integral controller (FOPI) and particle swarm optimization (PSO) algorithm. The aim of this high-performance controller is to reduce the rise time, settling time, steadystate error, and effects of load disturbances in the speed response of the DSIM, as well as minimize oscillations in the torque and stator currents, particularly at low speeds. This strategy named DTC-FOPI-PSO will be investigated, and its performances will be compared with the traditional DTC strategy based on the classical PI controller. Simulation tests using MATLAB/Simulink software are conducted under different operating conditions to demonstrate that the proposed DTC-FOPI-PSO strategy has a direct impact on improving speed dynamic, reducing torque fluctuations, minimizing steady-state error and provides excellent performance for load variation and reference speed inversion.

Enhanced Control of Dual Star Induction Motor via Super Twisting Algorithm: A Comparative Analysis with Classical PI Controllers

“…Electric variable-speed drives have become the backbone of modern industrial systems, enabling precise control over motor functions. Among the various control methods, field-oriented control (FOC) stands out for its ability to emulate the independent control achieved in DC motors by ensuring a decoupling control between flux and torque [1,2]. This study attempts to cope with these challenges and propose potential solutions within the realm of FOC, focusing on its application in DSIM.…”