Research On Adaptive Nonlinear Sliding Mode Control For Permanent Magnet Linear Synchronous Motor

Permanent magnet linear synchronous motor(PMLSM)is widely used in high-speed precision numerical control,semiconductor manufacturing,precision instruments,medical equipment and other industries because of the advantages of high accuracy,high speed,large thrust,and good heat dissipation.However,because linear motors lack intermediate buffering links,uncertain factors such as system parameter changes,external disturbances,and non-linear frictional forces act directly on the motor mover,thereby increasing the difficulty of control.Therefore,a control scheme combining nonlinear sliding mode control and fuzzy control is proposed to improve the tracking accuracy and robust performance of the system.Firstly,the basic structure and working principle of PMLSM were summarized,a mathematical model for PMLSM with uncertain factors was established,PMLSM vector control system was established based on the vector control theory,and the factors affecting the disturbance for PMLSM and the causes of uncertainty in the system were analyzed.Secondly,in view of the susceptibility of PMLSM servo control systems to uncertain factors such as parameter changes and non-linear friction,an adaptive non-linear sliding mode control method was proposed.By combining speed as a state variable and the generalized sliding mode surface,a nonlinear sliding mode surface was designed,which not only improves the response speed of the system,but also enhances the robustness of the system.Introducing adaptive control to adjust the control gain in the approach law to adjust the approach speed of the system state trajectory to the sliding mode surface,which reduces the chattering phenomenon,reduces the system tracking error,and improves the control accuracy of the system.By comparing the simulation results,the effectiveness of the proposed method is verified.Finally,in order to solve the problem that the uncertainty factors in the system are difficult to measure,a fuzzy control scheme is used to estimate and compensate the uncertainty factors online.This scheme can continuously reduce the estimation error by adjusting parameters in the fuzzy rules online.The tracking rules are used to construct fuzzy rules online to optimize the number of fuzzy rules.At the same time,an exponential compensator is used to ensure the stable performance of the system.The simulation results prove the feasibility of online construction of fuzzy adaptive nonlinear sliding mode control.