The Research On Servo Control Of Winding Machine Based On Fuzzy Neural Network

Because of the advantages of high strength,low density,abrasion resistance,corrosion resistance,good reliability and so on,composite fiber has been applied in many fields such as national defense and industrial production.Filament winding machine is core equipment used in the filament winding technology.To meet high-precision and rapid position tracking requirement for AC servo system in filament winding technology,the servo control system of winding machine based on fuzzy neural network is designed in this paper.This paper mainly studied the principles of the filament winding,winding types,winding rules and motion characteristics.First,according to the process requirements of filament winding technology,the servo control system of the winding machine is designed.The main shaft and carriage are the main control objects of the system,the main shaft applies the closed loop speed control mode and the carriage adopts the semi-closed loop position control mode,respectively.Trio motion controller and Panasonic servo motor are respectively used as the core controller and the performer of the servo control system,the industrial computer is used to realize human-machine interaction,the real-time control and the random-position conversion location control of the main shaft and the carriage are realized,and a certain winding angle is maintained.Second,in order to reduce the nonlinearity of the servo system and improve the response speed and control precision,the compensatory fuzzy neural network control algorithm is applied to the Trio controller.Finally,MATLAB simulations are performed to verify the effictiveness of conventional PID algorithm,fuzzy neural network algorithm and compensatory fuzzy neural network algorithm,the results show that compared with conventional PID algorithm and fuzzy neural network algorithm,compensatory fuzzy neural network algorithm could increase the steady-state performance and control precision of the system.