FUZZY INTELLIGENT-BASED TORQUE CONTROL SYSTEM FOR THREE-PHASE INDUCTION MOTOR

Abstract

This study presents the design and implementation of a hybrid Fuzzy-Proportional Integral Derivative (Fuzzy-PID) controller for effective torque control of a three-phase induction motor. The motivation for this work arises from the limitations of conventional control techniques, particularly in handling nonlinearities, parameter variations, and load disturbances inherent in induction motor systems. A mathematical model of the motor is developed using the d–q axis transformation to accurately represent its dynamic behavior. The proposed control strategy integrates the adaptability of fuzzy logic with the precision of PID control to enhance torque regulation performance. The system is implemented in a closed-loop configuration and simulated using MATLAB/Simulink under various operating conditions, including no-load, constant load, and varying load torque scenarios. Performance evaluation is carried out based on key transient response parameters such as rise time, settling time, overshoot, and steady-state error. The simulation results demonstrate that the Fuzzy-PID controller outperforms conventional PID and standalone fuzzy controllers by providing faster response, reduced oscillations, and improved robustness against disturbances. Additionally, the proposed controller effectively minimizes torque ripple and ensures stable operation under dynamic conditions. These findings indicate that the hybrid Fuzzy-PID approach offers a reliable and efficient solution for high-performance torque control in induction motor drive systems, making it suitable for industrial applications requiring precision and stability.