Nonlinear IoT-Based control and optimization for permanent magnet synchronous motors

Abstract

With the rapid development of industrial automation and Internet of Things technologies, permanent magnet synchronous motors are more and more widely used in fields of intelligent manufacturing and energy management. However, due to the inherent nonlinear characteristics of permanent magnet synchronous motors, the performance of traditional control methods under complex working conditions is limited. Therefore, this study proposes an IoT control method of permanent magnet synchronous motor based on nonlinear modeling, and optimizes its performance. Firstly, this paper introduces the basic operation principle of permanent magnet synchronous motor (PMSM), and introduces an improved nonlinear control model to comprehensively model the torque, speed and position control of the motor. In the experimental part, we construct a typical IoT control platform and experimentally verify the motor performance under different working conditions. The results show that the improved nonlinear model outperforms the traditional model in terms of transient response, steady-state error and energy efficiency. Under three typical working conditions, the optimized control scheme improves the energy efficiency of the motor system by 12.5%, reduces the steady-state error to 0.8%, and shortens the response time by 15.3%. These data show that the optimization of nonlinear model can significantly improve control performance of permanent magnet synchronous motor, which provides strong support for the further development of intelligent motor control system.