Iterative Learning Control For Permanent Magnet Linear Synchronous Motor Servo System

Compared with the traditional "rotating motor plus ball screw", permanent magnet linear synchronous motor(PMLSM) adopts a direct driving mode. It can obtain higher speed and acceleration as there is no conversion in between, which has been widely applied in the industrial field in recent years. At present, there is few research on PMLSM high precision control, and PID is generally used to control PMLSM, however, due to its poor stability and low accuracy control, it is difficult to apply PID to circumstances where higher accuracy is required. In regard to systems that perform repetitive tasks, iterative learning control(ILC) can track wholly theoretically without the exact mathematical model of the object. Therefore, the thesis conducted research on the control of PMLSM by applying improved ILC scheme to enhance the tracking accuracy of PMLSM servo system and the robustness of the system.Firstly, the mathematical model and state equation of PMLSM are established, and the influence of the end effect, friction, and the cogging force disturbance that exist in PMLSM servo system are analyzed. On the basis of PMLSM vector control theory, PMLSM vector control system is established. To solve the repetitive disturbances, such as the end effect, the cogging force, etc., and the non-repetitive measurement disturbances, adaptive PD type ILC, is designed in order to improve the tracking performance of the system. In order to further improve the performance of the system, on the basis of adaptive PD type ILC, adaptive filtering ILC is designed. The simulation results demonstrate that the p roposed method can speed up the convergence rate, reduce the tracking error to some exte nt with adaptive ILC and reduce greatly the tracking error with adaptive filtering ILC, which enhance the robustness of the system.Secondly, robust ILC based on Smith predictor and performance weighting function is proposed to solve the time delay of PMLSM servo system, which has proved the convergence and robustness of the control algorithm theoretically. The simulation results reveal that robust ILC can compensate for the time delay, so that the system can quickly converge to a stable state, which greatly improve the tracking accuracy of the system, and enhance the robustness of the system.Finally, to tackle the poor performance of PMLSM servo system based on ILC running at a time, the thesis designs a high precision control of PMLSM based on extended PID type ILC and FIR filter, to improve the performance of non-repetitive tasks. It can preserve ILC information to devise FIR filter, which is used to replace ILC in the ILC system, with sliding mode variable structure control(SMC) as a complement. Simulation results illustrate that the proposed scheme can reduce the tracking error of the non-repetitive tasks, and has strong robustness.