Comprehensive Review on Intelligent controller for Permanent Magnet Synchronous motor

Abstract

The energy-saving permanent magnet synchronous motor (PMSM) is a very effective device. In many industrial applications, PMSMs are progressively taking the place of AC induction motors due to their high efficiency, strong heat radiation capabilities, and simple structural features. A PMSM basically needs a intelligent controller to provide precise speed monitoring, little overshoot, and strong disturbance repulsion in order to operate at an excessive level. This paper presents a comprehensive review of control strategies for PMSMs, focusing on both traditional and intelligent control methods. Traditional control techniques such as Proportional-Integral-Derivative (PID), Direct Torque Control (DTC), and Field-Oriented Control (FOC) are examined for their efficacy and applications in PMSM systems. Additionally, the paper explores advanced intelligent control methodologies including Artificial Neural Networks (ANN), Fuzzy Logic Control, Adaptive Neuro-Fuzzy Inference System (ANFIS), Model Predictive Control (MPC), and Sliding Mode Control (SMC). The review also highlights the tuning of PI controllers using various optimization procedures, providing a detailed comparison of these methods in terms of performance, robustness, and implementation complexity. Through this analysis, the paper aims to offer valuable insights into the advancements in control strategies for PMSMs, guiding future research and development in this field.