Research And Design On Temperature Control Method Of Cold-Rolling Continuous Annealing Furnace Heating Section

As the main equipment of a cold-rolling continuous annealing line in the rolling mills,continuous annealing furnace can directly affect the quality,productivity and cost of cold-rolling strip steel.Control the temperature of continuous annealing furnace effectively can not only Increase productivity,and product quality,it can also saving cost and conserving energy.Due to the continuous annealing furnace is a nonlinear,large time delay and parameter time-varying complex and difficult to control of industrial process,traditional PID control strategy is difficult to meet the control requirements,so the research of practical significance for a good performance of control strategy.This thesis embarks from the actual,take the Benxi steel continuous annealing production line as the research background,for the continuous annealing furnace temperature control system for key digestive research the thesis mainly focuses on the temperature control system of continuous annealing furnace.Detailed analysis in the system including the furnace temperature control circuit,gas flow control loop and air flow control loop.At the same time,it takes profound research on double cross limit control strategy used in the system.In view of continuous annealing furnace temperature control system being a complicated nonlinear system with the characteristic of large inertia,pure time-delay,strong-coupling,time-varying and so on,thus it is difficult to build the exact mathematic model via the mechanism modeling method.This thesis based on the orthogonal least squares(OLS)optimization of the dynamic model of the RBF neural network to identify the annealing furnace.By analyzing various parameters influencing annealing furnace temperature,it gets the main input parameters of the system which are gas flow and air flow,and it gets the conclusion that the identification effect of annealing furnace temperature model using OLS-RBF neural network is quite good.Based on the mathematical model of continuous annealing furnace heating section,the paper designs a continuous annealing furnace temperature control system.This paper designs a kind of fuzzy PID controller based on adaptive genetic algorithm(AGA)to control the furnace temperature.The adaptive genetic algorithm add self-adaptive genetic operators to the traditional genetic algorithm.The adaptive crossover probability and mutation probability provide the optimal values of the population in genetic algorithm solution.It can not only ensure the diversity in population genetic algorithm,but it can also keep the convergence of genetic algorithm.Combine fuzzy strategy and PID control,use AGA to optimize the adjustment parameters ?ij of fuzzy rules,the quantization factors KE,KFC of the deviation E and the rate of change of deviation Ec of fuzzy PID controller.Simulation results show that:compared with the furnace temperature control systems based on AGA-PID and Fuzzy PID,the system based on AGA-Fuzzy PID has better stability,dynamic performance and steady-state performance to the system,so the AGA-Fuzzy PID has better control effect to the furnace temperature control.AGA-Fuzzy PID control strategy can quickly monitoring the changes of furnace temperature,it also has quick response speed,short setting time,small steady-state error,etc.The tracking performance of the system improves greatly.