Research Of Dual Permanent Magnet Linear Motor Synchronization Control

This subject comes from the National Natural Science Foundation of “Research ofdouble position loop linear servo dynamic precision synchronous feed theory andimplementation methods (50057075)” and “Arbitrary trajectory planning and precisioncontour control based on direct drive XY platform of the velocity field (51175349)”. Inthis thesis, there is a research on dual permanent magnet linear motor synchronous controlsystem which composed of dual gantry framework. Its purpose is to improve the systemsynchronized feed performance.Firstly, dual gantry framework synchronized feed has the nature of repetitive motion,so the structure of the position circuit is adopted PID feedback and iterative learningcontrol. Feedback controller can make the system stable and not far from the giventrajectory. The designed P-type iterative algorithm does not affect the stability of thesystem. It can rapidly improve the response speed and position tracking accuracy. Also theservo shedding problems are solved. The simulation experiments show that with theincrease in the number of iterations, the position tracking error can be reduced effectively.Its control effect is better than using traditional PID control.Secondly, for the role of the strong coupling caused by mechanical beams in the dualgantry framework, a fuzzy synchronization controller is designed. Un-synchronizationmotion of dual gantry frameworks makes the beam produce mechanical deformation force.This will seriously affect the dual-axis synchronous feed performance. The fuzzysynchronous controller captures dual-axis error information, and compensatessynchronization position and synchronization speed error using fuzzy reasoning. Thesimulation results show that it can overcome the effects of mechanical coupling, eliminatethe mutual interference between the shafts, and enhance the biaxial synchronizationoperating performance.Finally, a single neuron PID synchronization controller is designed as the limitationsof fuzzy control. Fuzzy control effect depends on the accuracy of the control rules, as wellas expert knowledge or experience. In addition, there are strict requirements in the selection of the fuzzy control rules structure and membership function. Inappropriatechoice of the scale factor or quantify factors can make the system oscillation, and then itcan’t reach the control effect. Neuron PID controller consider outside interference of thesystem as the measurable quantity. If one axis suffers from disturbance in the synchronousfeed movement, then neuron network weights value will be corrected. Furthermore it cancompensate interference and achieve synchronous control purposes. The simulations verifythat the scheme can achieve the dual-axis synchronization feed. It effectively eliminatesinterference in the movement and achieves high positioning accuracy and highsynchronization accuracy. Compared with the fuzzy synchronization controller, itssynchronization performance gets better.