Research On Improved Sliding Mode PMSM Control System Based On Artificial Intelligence Algorith

With the rapid development of permanent magnet materials,modern control theory and microcontrollers,permanent magnet synchronous motors have been widely used in various fields.However,since the PMSM is a multivariable,strong coupling,and nonlinear control object,when the motor control system is subject to internal parameter changes and load disturbances,the conventional control strategies are not robust enough to achieve high-performance control.As a nonlinear variable structure control,sliding mode control has good anti-disturbance ability and robustness to the changes of internal parameters of the system and external disturbances.However,chattering and parameter tuning problems exist in traditional sliding mode control.Therefore,in order to solve the above problems,this paper is mainly based on sliding mode control theory,and conducts in-depth research from two perspectives of permanent magnet synchronous motor speed control and sensorless control.The main research contents are as follows:(1)First,it briefly introduces the basic structure and classification of PMSM;then introduces the mathematical model of PMSM in natural coordinate system,two-phase stationary coordinate system and rotating coordinate system;finally introduces several common vector control,with vector The control principle is analyzed,and the principle and realization process of SVPWM are analyzed in detail.(2)To solve the problems of large chattering and slow response speed of traditional sliding mode control applied to PMSM speed loop,a new reaching law is proposed.This reaching law is improved on the traditional exponential reaching law,and an adaptive factor is introduced into the constant velocity term to solve the contradiction between the rapidity and chattering of the sliding mode control.At the same time,the hyperbolic tangent function is introduced to further reduce the sign The chattering caused by the function switching process is analyzed by using the phase locus diagram to analyze the superiority of the reaching law.Finally,the reaching law is used to design the PMSM sliding mode speed loop controller.(3)An improved PSO-GSA algorithm is proposed in order to solve the difficulty of adjusting the sliding mode control parameters and obtain the optimal parameters of the controller.First,a nonlinear weight function is introduced to improve the algorithm,so that the algorithm has strong global search ability and local exploration ability in the early and late stages of optimization.Then,using 6 basic functions for testing,the superiority of the algorithm is verified.Finally,the algorithm is used to tune the parameters of the sliding mode speed loop controller designed in Chapter 3,and the simulation verifies the effectiveness of the proposed control strategy.(4)Based on the sliding mode speed loop,an improved sliding mode observer is proposed to solve the problems of chattering and phase delay in the estimation of the rotational speed and rotor position of the surface-mounted permanent magnet synchronous motor by the traditional sliding mode observer.Permanent magnet synchronous motor vector control strategy.In order to reduce the observation chattering problem,a variable-speed approach law is designed to replace the constant-speed approach rate,so that the control gain is no longer a constant.At the same time,the phase-locked loop is used to estimate the rotor position and speed to improve the estimation accuracy.The simulation verifies that the improved sliding mode observer can effectively suppress the inherent chattering of the system and ensure the stable operation of the system.