Dynamic Analysis of Vector Controlled PMSM with Constant Torque Angle Control Strategy Using Artificial Neural Network

This paper proposes an AI approach to enhance the PMSM drive systems through an ANN based speed controller. Due to its great efficiency and precise control capabilities, PMSM drives are broadly used in industrial applications. However, achieving optimal speed control remains a challenging task, especially under varying operating conditions and disturbances. To address this, the proposed ANN-based speed controller utilizes to approximate the complex nonlinear relationship between motor torque and control input. Through adaptive learning, the controller effectively adapts to changing system dynamics, uncertainties, and disturbances, resulting in improved speed tracking accuracy, disturbance rejection, and robustness. Simulation results shows the better performance of the ANN controller compared to conventional techniques, making it a promising solution for enhancing PMSM drive system performance in various industrial applications.