Research On Thrust Fluctuation Analysis And Compensation Control Method Of Linear Motor

Compared with the traditional motor to realize linear motion,permanent magnet synchronous linear motor does not have problems such as reverse clearance,large inertia,large friction force and insufficient stiffness caused by the intermediate link,so the system has better stiffness,smaller inertia and better dynamic performance.However,due to the lack of intermediate mechanical transmission link,the system’s ability to resist external disturbance is reduced,which brings more model uncertainty problems.In order to more efficient application of linear motor in practical engineering,it is necessary to design appropriate control scheme to solve the impact of the above problems.Firstly,this paper deduces the mathematical model of linear motor platform through the vector analysis and dynamic analysis,and establishes a more accurate controlled object model by combining the sweep analysis and parameter identification experiment,which lays a foundation for the follow-up control algorithm research.Secondly,it is difficult to accurately describe the self-nonlinearity and external disturbance in the actual system,so the control method which requires higher model accuracy is not suitable for this kind of system.Considering the active disturbance rejection control(ADRC)scheme,which is less dependent on the system model,two kinds of ADRC schemes,linear and nonlinear,are designed in combination with the core idea of active disturbance rejection,and the extended state observer is used to compensate the system nonlinearity.In contrast analysis of the two plans on the basis of simulation and experiment,considering the nonlinear since the immunity control adjustment difficulties not easily used in actual system,linear since the immunity control phase lag problem when estimate time-varying disturbance,the bandwidth of the advanced correction with lifting system and the ability to control accuracy,to design the linear since the immunity control scheme based on advanced correction.The experimental results show that the linear active disturbance rejection controller based on advance correction can effectively improve the disturbance observation performance,and greatly improve the anti-interference ability and tracking accuracy of the linear motor platform compared with the traditional passive compensation.Thirdly,in view of the phenomenon that the linear motor platform has a large number of repetitive disturbances,considering the excellent performance of the learning ability of iterative learning control on the suppression of repetitive disturbances,the PD type iterative learning control scheme was designed.Through theoretical analysis,simulation research and experimental research,the iterative learning compensation method was deeply studied.The experimental results show that the iterative learning compensation method has a good ability to suppress the repetitive interference.Finally,in view of the large initial error and slow error convergence of the above PD-type iterative learning control,and the phenomenon that the error decreases first and then increases with the increase of the number of iterations,a filter type iterative learning control is further designed to improve the above phenomenon.The excellent performance of filter based iterative learning control is verified by theoretical analysis,simulation research and experimental verification.