Research On Active Disturbance Rejection Control Strategies For Permanent Magnet Linear Synchronous Motor

In recent years,Permanent Magnet Synchronous Linear Motors(PMLSM)have gained popularity as a high-performance control solution.This can be attributed to their high efficiency,low losses and remarkable accuracy.Nevertheless,due to its non-linear nature and strong coupling,PMLSM is also a time-varying system.To guarantee the dynamic and static characteristics of a control system,it is crucial that the control algorithm can withstand disturbances even under challenging operating conditions and variable model parameters.To this end,this dissertation emphasis on self-turbulence control techniques and devises high-performance control algorithms for Permanent Magnet Synchronous Linear Motors(PMLSM),utilizing kinematic mass identification methods.The primary purpose of the dissertation is to improve the robustness of the control system by implementing these measures.The main contents of the dissertation include:(1)In this dissertation,the mathematical modelling of PMLSM is combined with coordinate transformation,the vector control scheme is adopted to achieve complete decoupling of the controlled object,the traditional ADRC control method is introduced,and the ADRC control model of PMLSM is built.The simulation results indicate that in comparison to PI control,ADRC can effectively reduce overshoot and improve the robustness of the PMLSM drive system,but there are phase delays and chattering phenomena in the traditional ARDC differential tracker link.And to improve the tracking accuracy.(2)For the application of phase delay in the differential tracker(TD)link in the conventional ADRC and its filtering performance to be improved,this dissertation introduces the tangent sigmoid excitation function and terminal attractor function in the neural network to replace the original optimal control function and design an improved differential tracker(ITD).The ITD further optimises the structure of the conventional tracking differential by integrating the function.The ITD further optimises the structure of the conventional tracking differentiator by integrating overlapping parameters to make it easier to adjust the parameters.It also incorporates a terminal attractor function to reduce the chattering caused by high frequency signals,resulting in better noise rejection of the tracker.The tracking accuracy of the system is also improved.Secondly,to address the problem that the conventional expansive state observer(ESO)has an initial peak,which will reduce the observation accuracy,this dissertation designs a variable gain function in the gain term of the observer and introduces the variable gain function into the nonlinear error control law(NLSEF),which together with ITD constitutes a variable gain ADRC control strategy.To prove the validity of this control method,a variable gain ADRC position controller model of PMLSM is built in this dissertation.The simulation results indicate that the variable gain ADRC effectively improves the observation accuracy of the ESO against disturbances and improves the anti-disturbance capability of the system.Compared with the conventional ADRC control strategy,the variable gain ADRC completely eliminates overshoot and improves the dynamic response and robustness of the system.(3)In response to the existence of disturbances under PMLSM load conditions,changes in the kinematic mass can deteriorate the tracking performance of the system.In this dissertation,a mass-discriminative ADRC control strategy based on the adaptive Landau discrete recursive discrimination algorithm is designed.This ensures good dynamic and static performance when the servo system is subject to load disturbances and changes in kinematic mass.Simulation results show that the mass-discriminative ADRC response time is reduced by 42%,the sudden load recovery time by 25% and the sinusoidal tracking position error by 98% compared to the variable-gain ADRC.It can be concluded that the quality-discriminative ADRC can further enhance the response performance and anti-interference capability of the system.(4)In order to evaluate the efficacy of our proposed control method,PMLSM position control models of traditional ADRC,variable gain ADRC and mass recognition ADRC control strategies were built based on Speedgoat semi-physical simulation platform,and the position step response for a given position and sudden addition of load were performed respectively.The experimental results show that compared with the variable gain ADRC,the no-load response time of the mass-aware ADRC is reduced by8.3% and the recovery time under load is reduced by 50%,which demonstrates that the control system proposed in this dissertation can significantly speed up the response and improve the robustness of the system.