Modeling And Control Algorithm Optimization Of Rubber Compound Extruder Barrel Temperature System

Efficient,lean and intelligent extrusion technology is the development direction of contemporary rubber extrusion technology.As the core process equipment of rubber semi-finished product extrusion,the temperature control of rubber extruder is the key factor to determine the quality and performance of the semi-finished product.Therefore,accurate measurement and control of the temperature in the extrusion process can effectively improve the performance of the semi-finished product,reduce the energy loss in the extrusion process and improve the industrial production efficiency.This paper takes the temperature control system of rubber extruder as the research object,and deeply understands the process and technical characteristics of rubber cold feed extrusion molding,and analyzes the energy consumption in the extrusion process.The structure and control principle of the temperature control system are analyzed in the actual process site,and the main control variables in the temperature control process are defined.According to the actual temperature control data of extrusion production provided by Guilin rubber Design Institute,the MATLAB system identification model is established,and the mathematical model of the temperature control system of the discharge barrel is identified.On this basis,the control scheme is designed.In order to improve the dynamic response characteristics of the controlled system,fuzzy PID controller is used.In order to solve the problem of large time lag in temperature control system essentially,Smith predictor is introduced to design Smith fuzzy PID barrel temperature control system,and forgetting factor recursive least square method is introduced to identify Smith predictor model.In order to solve the problem of poor control accuracy caused by manual parameter adjustment,particle swarm optimization algorithm(PSO)is used to automatically optimize PID controller parameters.At the same time,in order to prevent PSO algorithm from falling into local optimization,a hybrid particle swarm optimization(HPSO)algorithm is designed to optimize PID parameters by decomposing social factors into local and global social factors.Firstly,the traditional PID temperature control system and the fuzzy PID temperature control system are compared after the PID parameters are set by the artificial experience method,and the step and nonlinear disturbance experiments are carried out to compare the anti-interference performance of the traditional PID temperature control system and the fuzzy PID temperature control system.The experimental results show that the dynamic output response of fuzzy PID temperature control system is better than that of traditional PID temperature control system,but both of them have poor antiinterference performance.Based on the analysis of Smith-fuzzy PID temperature control system affected by parameter changes,the on-line identification experiment of FFRLS system is carried out to verify that FFRLS-Smith-fuzzy PID control system has stronger delay compensation ability.Then the Smith-fuzzy PID temperature control system is simulated,and the control effect is compared with the fuzzy PID temperature control system.The experimental results show that the dynamic characteristics and antiinterference performance of Smith-fuzzy PID temperature control system are better.Comparing the optimization effect of PSO algorithm and HPSO algorithm,through experimental analysis,the maximum overshoot and steady-state error of Smith-fuzzy PID temperature control system optimized by HPSO algorithm are almost zero,and the fluctuation amplitude is less than ±1.2? after being disturbed,which meets the requirements of extruder temperature control technical index.The paper studies and designs the control algorithm according to the relevant process and performance index of Guilin rubber Design Institute,which has certain reference value for the temperature control technology of extruder to realize accurate control.