Research On Fuzzy RBF Control Of Air Speed In Pneumatic Convey Of Tobacco Leaf System

In the cigarette industry,the wind speed valve is the core control part of the wind-driven wire feeding system,which is related to the broken rate of tobacco and the quality of product.The aim of air speed balance research is to find a more reasonable optimal control method,so that the wind-driven wire feeding system can quickly adjust the air speed in the wire feeding pipeline under the condition of frequent load changes,and keep the stable transmission of tobacco in real time.This paper combines theoretical analysis with experimental research,and develops a set of multi-functional automatic air speed balance control system based on the project of an air supply balance supporting product manufacturer,which can be applied to process production.The main content of this paper is the design and implementation of the air speed balance system for tobacco delivery of cigarette machine,including the overall design of the air speed balance system,the analysis of the technological characteristics of the network,the study of the control system module,the design of the system software and the analysis of the system experiment.By analyzing and researching the problems of pipe network design and valve process characteristics in wind power wire feeding system,a fuzzy RBF neural network with strong global optimization ability is proposed to identify and learn the system model,and constantly iteratively predict the ideal air speed,so as to solve the problems of the influence of other loads on the air speed of wind pipe and the insufficient response caused by control valve hysteresis effect and friction force,and to enhance the control system.The control accuracy,response time and stability of the system are discussed.In industrial control design,the air speed balance system adopts the design mode of unit industrial computer PLC,and takes the idea of PID theory control as the core,designs a new intelligent PID control method which combines intelligent control theory RBF neural network with fuzzy control technology.According to the theory of fuzzy control,fuzzification and de-fuzzification are carried out for the setting of air speed in air speed balance system,the actual input of air speed,the output of valve opening position,etc.Then the parameters of PID control are online learned,calculated and adjusted by RBF neural network algorithm,so as to realize the reasonable control of air speed balance control system.Finally,the software and hardware of the air speed balance system are debugged through the realization of the control program and operation interface by relevant software.In the engineering experiment stage,considering the environmental factors of the air speed balance test system,under the industrial temperature requirement,the errors and causes in the experiment process are continuously detected and analyzed by the way of simulation production,which provides a theoretical basis for improving the accuracy of the control system.Experiments show that the precision of fuzzy RBF neural network PID control and the compatibility of various modules can achieve the desired results,and achieve the design requirements.