Research On Composite Sliding Mode Control Of Permanent Magnet Synchronous Linear Motor

Permanent Magnet Linear Synchronous Motor(PMLSM)uses point-to-point direct transmission technology,which eliminates the transmission error of the conversion mechanism in the application of rotating electrical machines,so it has the characteristics of fast response,large thrust,and strong maneuverability,it is used in the processing field with high precision requirements.However,because there is no buffering process in the transmission,the influence of internal and external disturbances in the system is directly reflected in the motion control of the motor,which limits the processing accuracy.Therefore,it is of great significance to improve the anti-interference and stability of linear motor for its direct drive characteristics.In order to improve the overall control performance of the motor and meet the high-precision and high-stable processing requirements of PMLSM in the industrial field,this paper is based on the sliding mode variable structure control system,researching on the chattering in the control system,the disturbance caused by the perturbation of internal parameters in complex environments,and the instability in operation.The specific aspects are as follows:First,introduce the current research status of sliding mode variable structure control at home and abroad,and then describe the mathematical model of PMLSM,vector coordinate transformation,SVPWM principle and the overall structure of the vector control system of sliding mode variable structure control.Secondly,based on the analysis of the existing motor control methods,this paper proposes two solutions to the chatter in the motor and the instability in complex environments.Firstly,based on the general exponential reaching law,a new improved reaching law including index terms,system state variables and terminal terms is established,which solves the the problem of incompatibility between reducing chattering and increasing the response speed of the system in the traditional reaching law.Considering the system chatter caused by sudden load,an improved disturbance observer is added on the basis of the reaching law.The simulation results prove that the proposed new improved reaching law and improved disturbance observer control strategy not only improves the anti-interference of the system but also meets the control system's requirements for high precision control.Finally,considering that the motor is running in a complex environment,its internal parameter perturbation and model uncertainty disturbance seriously affect the operation stability and control performance of the motor.This paper also proposes an adaptive law combined with an improved second-order extended state observer to improve its control performance.By introducing adaptive law in the current loop,the internal parameter perturbation and model uncertainty disturbance in the control system under complex environment can be estimated in time to improve the current loop's current change response ability,track performance,and meet the thrust required by the system in a complex environment improves its anti-interference performance.The adaptive law mainly replaces the conventional sign function with the sat2 function to weaken the breakpoint chatter caused by the discontinuous function and improve the stability of the control system.At the same time,the proposed new sigfal function is used to improve the second-order extended state observer to solve the problem of buffeting of the traditional fal function due to the inflection breakpoint.By predicting the load of the system and feeding the value to the current loop to compensate it,reducing the sliding mode control gain,improve prediction accuracy and stability.Simulation results prove that the proposed method can ensure the anti-disturbance of the permanent magnet synchronous linear motor drive system and can improve the current and speed tracking performance.Finally,by proposing a comparison between the two algorithms,analyzing their respective characteristics,and comparing the advantages of the algorithm under different conditions.