Research On PMLSM Control System Based On Nonlinear Disturbance Observer

Permanent magnet linear synchronous motor(PMLSM)is widely used in aerospace,semiconductor and high-speed automatic processing equipment because of high thrust,fast response and high reliability.Compared with traditional rotary motors,PMLSM saves intermediate transmission link,drives load directly and increases efficiency greatly.However,PMLSM can be affected by uncertainties easily such as external load disturbance,frictional force and thrust fluctuation,etc.Therefore,PMLSM control system is a highly nonlinear time-varying system in practical applications.In order to weaken the influence of uncertainties on PMLSM,adaptive fuzzy control based on nonlinear disturbance observer(NDO)and intelligent control based on NDO are proposed.Firstly,the basic structure and working principle of PMLSM are elaborated,the dynamic equation of motion for PMLSM with uncertainties is established,the vector control system of PMLSM is established based on vector control theory,and the influencing factors of disturbance for PMLSM are analyzed.Secondly,aiming at the system is affected easily by uncertainties such as external load disturbance,frictional force and thrust fluctuation,etc,an adaptive fuzzy control method based on NDO is proposed.Using feedback linearization controller to linearize the system and guarantee global stability,combined with an improved NDO,change rate of uncertainties which approximate zero is eliminated,and the uncertainties are effectively observed and compensated.Because the selection of observer gain can lead to large observation error easily in the actual operation process,the adaptive fuzzy control is used to approximate the observation error of NDO,and the adaptive law is used to adjust the fuzzy rules dynamically to improve the performance of the fuzzy controller.The simulation results show that the adaptive fuzzy control method based on NDO can reduce the tracking error and enhance the robustness of the system effectively.Finally,the adaptive law has some limitations on dynamic adjustment of fuzzy rules When the adaptive fuzzy control approximates NDO observation error,the intelligent control method based on NDO is adopted,and the wavelet neural network(WNN)is introduced to compensate the observation errors of NDO dynamically,which can improve the compensation performance of NDO effectively.The simulation results show that compared with the adaptive fuzzy control method based on NDO,the intelligent control method based on NDO can improve the compensation performance of NDO.It improves the tracking accuracy and robustness of the system.