Reasearch On The Key Technique Of The Multi-servomotor Synchronization Control

Along with the continuous development of modern industrial and commercial systems,the concepts of "Industrial 4.0" and "Made in China 2025" have been proposed one after another.The future industry will develop toward digitization,networking and intelligence.This is also the direction of China's manufacturing transformation and upgrading.Thus,in many areas of production and processing,multi-axis intelligent equipment body will become a trend,multi-axis motion control applications will be more extensive.At present,the most mature cooperative control strategies are noncoupled cooperative control and cooperative cooperative control.However,there are still great potentials in improving the coordination precision.This dissertation is based on four-axis motion control system simulation platform and experimental platform as the research background and object of study.The mathematical model of multi-servo motor motion system is established,and the factors that affect the synergetic error of multi-motor system are analyzed respectively from dynamics and control algorithm.And we are addressing the following three questions: design of single-axis controllers for multi-motor systems;design of Multi-motor System Cooperative Controller;the multi-axis position tracking coordination based on the electronic cam is designed.The main research work and the novel contributions are listed as follows:First,a control strategy of SOA-PID controller based on crowd search algorithm is proposed for one of the key technologies of multi-servo motor coordinated control: single-axis tracking response.This strategy is based on the swarm intelligence algorithm of searching and evolutionary thinking,and the PID controller is designed.Based on the PID controller,this paper designs a SOA-PID controller to solve the problems such as perturbation,weak robustness and strong dependency on parameter selection.PID parameters optimization and optimization rate,thus improving the single-axis tracking accuracy and responsiveness,and ultimately improve the system to achieve the purpose of robustness.The simulation model of the four-axis coordinated control system was established by Matlab/Simulink.The structure model of the conventional cooperative controller was selected and the simulation results were obtained.Similarly,on the basis of PID control,in order to verify the utility of the crowd search algorithm,another kind of intelligent algorithm-genetic algorithm is used to optimize the PID parameters,and another optimization result is obtained.Compared with the simulation results,it can be seen that the population search algorithm has the advantages of fast convergence speed,high precision and small error,and verifies the effectiveness of the population search algorithm.At the same time,it also lay a good foundation for the research of the follow-up multi-axis cooperative controller.Second,based on the realization of single-axis fast tracking response in the previous chapter,the key technology of cooperative control of multi-servo motor is studied: cooperative controller,and the control strategy of the cooperative controller based on wavelet neural network is proposed.Aiming at the problem that the conventional cooperative controller in the multi-axis cooperative control is difficult to eliminate the cooperative error quickly,a speed compensator based on the wavelet neural network is proposed.The approximation ability and computational capability of the arbitrary function by neural network and the wavelet transform can be self-The proposed algorithm can adjust the shape of wavelet base to realize the advantage of wavelet transform,and make the whole algorithm have stronger learning ability and faster convergence speed.Combining on-line training algorithm,it realizes the prediction and compensation of co-error and finally achieves the purpose of eliminating co-error quickly.Then,on the Ma.tlab/Simulink experimental platform,the simulation model of the four-axis coordinated control system is built,and the speed compensator designed in this chapter is used to simulate and analyze the analysis results under different disturbances.Finally,under the same simulation condition,the results are compared with the simulation results of the conventional cooperative controller.The comparison results show that the cooperative control structure based on wavelet neural network has higher coordination precision,less fluctuation in velocity and shorter adjustment time,The convergence rate is fast,and the validity of the designed speed compensator is verified.Third,aiming at the position tracking problem of multi-servo motor coordinated control,a collaborative control system based on the electronic cam technology is designed.The control system consists of BECKHOFF embedded PC,permanent magnet synchronous servo motor,ball screw linear platform and other components.For the four-axis experimental platform,in order to meet the control requirements of highfrequency start-stop and high-precision positioning dual-constraint high-response control,the constant trapezoidal combination curve of high-speed cam is used to select the non-stop modified trapezoidal acceleration As the acceleration strategy of the servo motor,the electronic cam curve is designed rationally,and the rigid shock and the flexible shock can be eliminated by the uniform and continuous change of the speed,acceleration and jump of the screw platform movement,so as to improve the tracking precision.Experiments were carried out on a four-axis experimental platform.The realtime data was collected by TWINCAT's Scope View software.The single-axis tracking algorithm and multi-axis cooperative algorithm designed in this dissertation provide a theoretical basis for multi-axis cooperative control.