Speed Sensorless Control Of Permanent Magnet Synchronous Motor Based On Improved Extended Kalman Filter

Permanent Magnet Synchronous Motor(PMSM)has become the most common electric power transmission device today due to its small size,simple internal structure,and low cost.Aiming at the problem that the traditional extended Kalman filter speedless sensor has deviations in the observation results under sudden changes in load,speed,and temperature.A speed sensorless control method based on model reference adaptive identification and improved extended Kalman filtering is proposed.First,the classification and characteristics of the permanent magnet synchronous motor are introduced.The basic mathematical model of the permanent magnet synchronous motor is established.The mathematical model is established in a two-phase rotating coordinate system through coordinate transformation.At the same time,the different control methods of vector control are analyzed and the vector control of permanent magnet synchronous motor is simulated.Secondly,the relevant knowledge of Kalman filter and extended Kalman filter is elaborated,and the process of establishing the extended Kalman filter mathematical model is deduced and analyzed.The influence of the extended Kalman filter speed characteristics and the changes of system structural parameters on the extended Kalman filter is verified by using MATLAB simulation.At the same time,the results also show that the extended Kalman filter can better observe the motor speed and rotation angle position,and has good estimation performance.Then,in order to improve the influence of the change of the key parameters of the motor on the observation results of the extended Kalman filter,the extended Kalman filter is improved by using model reference adaptive identification,and the extended Kalman filter is improved by the least square method for comparison experiments.The simulation results show that the model reference The self-adaptive identification and optimization results are ideal with high accuracy.Finally,in order to improve the anti-interference ability and fast response ability of the overall speed regulation system,the fuzzy reference PI control algorithm was added to the model reference adaptive identification to improve the extended Kalman filter control system.The simulation results prove that the improved scheme is adopted for the overall speed regulation system.The anti-jamming ability and fast response ability have been significantly improved,there is almost no overshoot,and the control effect is better.