Study On The Anticipatory Iteration Learning Control For Linear Motor

The study on motor control is of great significance in industrial and academic circles,among which the motor position tracking control is one of the key technologies at present.In this study,the servo system of Permanent Magnet Linear Synchronous Motor(PMLSM)is taken as the study object,and the motor position tracking control is studied.For the motor position tracking control,the main work of this study is as follows:Firstly,the mathematical model of PMLSM is studied,and the basic structure and operating principle of PMLSM and the mathematical model of PMLSM are introduced in detail.In addition,the relationship between linear motor and rotary motor in structure and operating principle is explained and compared,and the necessity of selecting PMLSM as servo system is also explained.Secondly,for the position tracking control of linear motor,a double closed-loop motor tracking control strategy is established in this paper,with the velocity loop adopting PID control and the position loop adopting the Iterative Learning Control.Considering the slow convergence speed of ILC and the large error at the initial stage of the iteration,this study makes further improvements and forms AILC-PID control strategy by using Anticipatory Iteration Learning Control as the position tracking control loop,and combining it with PID control.Through the modeling and simulation in MATLAB/Simulink,the results show that the AILC-PID control strategy can effectively compensate the trajectory error of the system at the initial stage of iteration,with the characteristics of faster convergence speed than that of the ILC-PID control strategy.Thirdly,given that tracking errors may be caused due to the interference of external environment and the nonlinear factors of motor itself during the working process of the motor,and Auto Disturbance Rejection Control is widely used in anti-interference control,Auto Disturbance Rejection Control is used in this study to replace the PID control of the velocity loop,and then is combined with AILC to form the AILC-ADRC control strategy,so as to control the motor position.Through the modeling and simulation in MATLAB/Simulink,the results show that the proposed AILC-ADRC control strategy can well resist the external uncertainties.Finally,in view of the strong experiential factors in the parameter design of the ADRC controller,in this study,the Improved Particle Swarm Optimization is used to optimize the parameters of ADRC controller quickly,so as to find the best control parameters.The designed control system is modeled and simulated through MATLAB/Simulink,and the results show that the optimized AILC-ADRC control strategy can resist the unknown external interference more effectively.