Research On Control System Design And Intelligent Control Algorithm Of Spinning Production Line

With the improvement of people's quality of life,people's demand are more and more urgent on health,environmental protection,comfort for textiles.By the yield and quality constraints,there is now a contradiction between the domestic demand for high performance chitosan fiber pure chitosan fiber with low grade low yield shell.In view of this situation,this paper designs a set of spinning production line control system,which meets the basic requirements of production line control.In addition,the ant colony algorithm is successfully applied to the liquid level control of the coagulation bath liquid level control system in the process of adjusting the simulated PID.First of all,in understanding the spinning production line production process and control requirements,based on the design of the overall system architecture,and then the system hardware selection and provides a basis for selection,the role of commonly used hardware equipment to do a simple Introduction.Secondly,the monitoring system of the spinning production line is built.The monitoring system designed in this paper includes two aspects: the bottom monitoring and remote monitoring of the production line.The bottom of the monitoring is MCGS and Siemens PLC through the serial port MCGS touch screen monitoring,remote monitoring is through the GPRS remote monitoring module on the scene of the remote monitoring and control.Thirdly,the traditional PID control and advanced control algorithm are introduced briefly,and the ant colony algorithm is introduced and described systematically.The control system of the coagulation bath is modeled and the ant colony algorithm is introduced into the PID parameter setting.Finally,through MATLAB simulation,the simulation of Z-N method,genetic algorithm,fuzzy adaptive ant colony algorithm and show that,from the theoretical analysis and experimental results,has small overshoot,short setting time advantage of ant colony algorithm in PID parameters optimization of the system.This combination of advanced control and conventional control strategy to achieve the coordinated operation of advanced control and conventional control to improve the quality of control.