Research On Force Ripple Modeling And Suppression In PMLSM

Permanent magnetic linear synchronous motor has such excellent characteristics as high speed, high accuracy, high thrust, and so on. Therefore, it plays a significant role in precision and ultra-precision motion stage. How to suppress force ripple and improve the tracking precision of PMLSM is a crucial problem, and this will greatly improve precision and ultra-precision motion stage's performance.In this dissertation, according to the structure of PMLSM, force ripple is firstly analyzed. And a method of modeling the force ripple based on velocity and position is proposed. Through analyzing the relationship between force ripple and trajectory tracking error, the harmonic components contained in force ripple is calculated. Then a mathematical model of force ripple is established, hence a feedforward compensator based on this model is designed. Experiment results indicate that this method can effectively solve the force ripple problem under different velocities and improve PMLSM's dynamic performance.Secondly, against the repetitive characteristic of force ripple, two iterative learning control (ILC) methods are designed. One approach applies last time's trajectory tracking error to revise the error output of the controlling system and feeds it to the controller. While the other one uses this error to revise controller's output as a feedforward compensator. Simulation experiments are carried out to evaluate these two methods, and the convergence speed and convergence accuracy are taken as the main comparison items to pick up the more excellent approach. Experiment results indicate that ILC can efficiently suppress force and improve PMLSM's trajectory tracking performance.Finally, to solve the impact on ILC caused by trajectory changes, a method called cogging compensation piecewise iterative learning control (CCPILC) is proposed. This approach divides the learning feedforward into three pieces: acceleration part, constant velocity part and deceleration part. Constant velocity part signal is filtered by a wavelet filter. Then a model based on position that relates to force ripple is constructed. Using this model and combining the acceleration and deceleration part learning feedforward, force ripple could be compensated perfectly with changed trajectory. Test results confirm that CCPILC can efficiently solve the impact on ILC caused by trajectory changes and suppress changed force ripple caused by varied trajectory.