Research On Precision Control And Optimization Strategy Of Permanent Magnet Synchronous Motor

Permanent magnet synchronous motors are widely used in various servo control occasions with their precise speed regulation performance and high efficiency motor efficiency.In view of the insufficient control accuracy of traditional control algorithms,it is difficult to meet the requirements of high-performance servo motors.This article will conduct in-depth research on control algorithms and optimization measures.First,by means of coordinate transformation,the permanent magnet synchronous mathematical model under the static and synchronous rotating coordinate system is established,and the vector control strategy and the principle of voltage space pulse width modulation are analyzed.At the same time,the PI parameter tuning methods of the speed outer loop and the current inner loop are analyzed,and the basic construction of the permanent magnet synchronous motor vector control system is completed,which will serve as the theoretical basis for the subsequent establishment of the permanent magnet synchronous motor predictive model.Secondly,the principle of predictive control under parametric and non-parametric models is analyzed,and a speed predictive controller using discrete transfer function as a model and a current predictive controller using space state equation as a mathematical model are designed to replace the PI adjustment in traditional control algorithms.It realizes the model predictive control of permanent magnet synchronous motor.Model predictive control makes full use of its multi-input,multi-constraint,and multi-output characteristics.It can output 6 switch variables to realize the direct drive of the three-phase two-level inverter,eliminating the need for complex coordinate transformation and space pulse width modulation,simplifying The system control method.The simulation experiment verifies the correctness of the model predictive controller design and the feasibility of the predictive control algorithm in the field of motor control.In order to improve the anti-interference ability and parameter robustness of the permanent magnet synchronous motor under predictive control,the realization principle of the Kalman filter is analyzed,the Kalman filter is designed to observe the load disturbance in the system,and the observed value is taken as the front of the quadrature axis current.Feed compensation realizes suppression of load disturbance.Both the current controller and the speed controller are designed with parameters as internal models.Uncertain changes in parameters will cause inaccurate predictions,which will affect the overall control performance of the system.Based on this,a self-calibration strategy for inductance parameters is proposed,which effectively suppresses the fluctuation of current and speed,and improves the robustness of parameters.Through simulation experiments,the control performance before and after the feedforward compensation and parameter correction are compared.Finally,a comparative analysis of vector control and model predictive control from three aspects of speed tracking performance,current and speed fluctuations,verifies the superiority of predictive control in improving the precise control of the motor.At the same time,complete the software and hardware design of the permanent magnet synchronous motor control,build an experimental platform,and verify the feasibility and effectiveness of the control algorithm.