| Permanent Magnet Synchronous Motor(PMSM)has a wide range of applications in various industrial processes and control equipment fields due to its high efficiency,low loss,and simple structure.In the traditional PMSM control,in order to improve the accuracy and control ability of the permanent magnet synchronous motor,it is necessary to install a position sensor and a rotation speed sensor on the motor.This will not only increase the weight and volume of the synchronous motor,but also reduce the robustness of its control system.Greatness,limiting the scope of use of PMSM.Therefore,in this context,this article has carried out research on the speed and position control of permanent magnet synchronous motors.First of all,this thesis classifies PMSM,derives the PMSM mathematical model in various coordinate systems,and the synthesis principle and realization of SVPWM algorithm,which provides a theoretical basis for sliding mode control strategy.Secondly,to solve the problems of slow response speed and large overshoot when the PMSM sliding mode speed control system runs at rated speed,a sliding mode speed controller based on second-order integral is proposed.Compared with the simulation test of the traditional first-order sliding mode speed control system,the algorithm can not only speed up the response time of the rated speed,but also reduce the overshoot at the rated speed.Then,to solve the problems of serious system chattering and poor robustness in the permanent magnet synchronous motor positionless control system,a sliding mode observer based on piecewise power function is proposed on the second-order sliding mode speed controller.Compared with the simulation analysis of the traditional sliding mode control system,it is proved that the new sliding mode control system converges quickly,has high control performance,weakens the inherent chattering problem in the permanent magnet synchronous motor,and has better robustness.Finally,the RT-LAB real-time simulation platform is introduced,and the traditional sliding mode control system and the new sliding mode control strategy are analyzed and verified experimentally using this platform to ensure the feasibility and correctness of the proposed algorithm. |