Heating Furnace Optimum Air-Fuel Ratio And Temperature Control System Research

The step heating furnace is a complex industrial controlled object with many factors,such as large inertia, pure time-delay, nonlinear, external disturbances characteristics, and thestep heating furnace is one of the main equipments of hot-rolling production process iniron and steel enterprises, its main task is to provide the qualified billets, which meets therequirements of rolling technology. The step heating furnace is the key equipment of rollingprocess, and its control level directly affects the billet heating quality, yield, and the cost ofproduction. Therefore, it is very important for the research to improve.For the problem of a steel enterprises that the temperature of the heating furnace is notbalanced, the control loop respond slowly and air-fuel ratio can’t be self-optimizing. Thispaper begins with the heating furnace process, analysis the temperature changes of theheating furnace, and puts forward the control method of the furnace temperature. That is say,it is using PID controller and fuzzy controller to optimize the heating furnace combustionsystem.This paper introduces the structure, process and control requirements of the step heatingfurnace, expounds the control situation of stepping type furnace, analyzes the process controlsystem of the step heating furnace, and also discusses the implement methods of heatingfurnace combustion process optimization model in the industry, and in the light of theheating furnace, studies and researches the following aspects:First, access to a large number of data about the heating furnace, I masters the structure,process and control requirements of heating furnace. Second, after studying the cascade ratiocontrol system, establishes the model of the controlled object by this method. Third, studythe PID control method and the fuzzy control method on the basis of the modeling. Fourth,in mastering the knowledge based on the above, designs the PID controller and the fuzzycontroller, and takes simulation contrast between them. In the full understanding of fuzzyalgorithm, improves the fuzzy controller, joins the adjustment factor, and makes thesimulation effect more close to the desired effect.The results show that when the fuzzy controller is joined the adjustment factor, thefurnace temperature can achieve stability faster and better, and the heating furnace canrealize the control effect better.