Research On Disturbance Rejection Control Method For Permanent Magnet Linear Synchronous Motor

Since the industrial intelligence,numerical control industrial technology has gradually developed towards high efficiency,high precision,high intelligence,and other directions.The linear motor,which removes the intermediate links,has the advantages of fast response speed,high positioning accuracy,high sensitivity,low noise,etc.At the same time,it also has a larger acceleration,reducing system response time.In terms of control performance,the linear motor is superior to the rotary motor.Nowadays,permanent magnet linear synchronous motors(PMLSMs)have been widely used in vehicle control systems,aerospace,industrial robots,automatic control systems,power equipment,and other fields.However,due to its special mechanical structure,it is easily affected by external uncertain factors,such as changes in system parameters and load disturbances.In order to improve the dynamic response performance and robustness of the system,this article studies and designs the controller of the PMLSM servo system based on the sliding mode variable structure control algorithm.First,briefly explain the basic structure,working principle,and characteristics of PMLSM,and analyze the mathematical model of PMLSM in two rotating coordinate systems using coordinate transformation formula to obtain the electromagnetic thrust expression.Analyze the generation and impact of uncertainty in the PMLSM servo system.Briefly describe the principle of PMLSM magnetic field orientation vector control,and analyze the working process of PMLSM based on the PMLSM servo system block diagram.Secondly,briefly introduce the working principle of radial basis function neural network(RBFNN),and introduce the parameter adaptive RBFNN(PARBFNN).Combined with the PMLSM system model,the sliding mode controller based on PARBFNN is derived.The Fal function is used to optimize the shaking problem in the approaching sliding mode stage of the traditional power-law approaching law,making the approaching mode smoother and improving the dynamic convergence quality of the PMLSM servo system.In order to verify the feasibility of the control scheme,simulation is carried out on the Matlab/Simulink simulation platform,and the simulation results prove the effectiveness of the scheme.Thirdly,in order to further improve the dynamic response quality of PMLSM,disturbance observer is used to observe the total uncertainty of the system,and the observation value is compensated into the controller design.For the problems of insufficient tracking accuracy,slow convergence speed,and long time in traditional terminal sliding mode position tracking,this article designs a fractional-order non-singular terminal sliding mode.The fractional calculus theory is added to the traditional terminal sliding mode control,increasing the degree of freedom of the controllable parameters of the sliding mode surface,which lays a foundation for improving the system’s dynamic response speed and improving control performance.Simulation results verify the effectiveness of the control scheme.Finally,considering the complex operating environment of PMLSM,the exponential approaching disturbance observer cannot meet the requirements of the use cases where the amplitude of total disturbance changes greatly.Therefore,this article proposes to combine the generalized super-twisting observer with the fractional-order non-singular terminal sliding mode for PMLSM position tracking control.The generalized super-twisting observer is used to compensate for the total uncertainty of the system in real-time,and the super-twisting approaching law is used to optimize the approaching mode of the system state trajectory,further improving the control performance of the fractional-order sliding mode control system.Simulation results show that the fractional-order super-twisting controller based on the generalized super-twisting observer has further improvement in convergence time and convergence accuracy.