The Study Of Fuzzy-Pid Control Based On Predictive Model And Its Simulation And Experiment

Temperature is one of the most important parameters in process industry, and the temperature control is of great significance especially for the petrochemical industry. The temperature of electronic boiler is a first-order inertia plus time delay unit, and has the characteristic that badly affected by the environment and other factors, so the temperature control of electronic boiler is a more difficult issue in process control.In this thesis, it applied several typical advanced control techniques on the AE2000 process control facility and on the basis of that, it studied the theory of fuzzy PID control technique based on the predictive model and its simulation in electronic boiler.It was introduced into the lab that the AE2000 process control facility and JX-300 distributed control system which is researched, developed and produced by Zhejiang SUPON Electronic Technology Co., Ltd. The subject investigated is the temperature control of electronic boiler, and it has the characteristic that is not only large inertia and large time delay but also badly affected by the environment. In the original subject on the basis of conventional PID control, it had achieved Smith control, Internal Model control, Fuzzy control and Dynamic Matrix Predictive control, and got the corresponding curves. Through compared these curves of advanced control, it concluded the advantages and disadvantages of these advanced control methods against the object.On the basis of mentioned work, it had designed the Fuzzy-PID controller based on predictive model for the characteristics of electronic boiler. Firstly, it had attained the simulation of PID control and Fuzzy-PID control in the Matlab software. Through the simulation compared the controller with the Fuzzy control and conventional PID control, it was less than about 600 seconds with smaller change of over control, and with 20% value of disturbance, the output came to stable state just in half-time before. Secondly by adding prediction model into the control model, the prediction model could predict the output of the future. It reduced the time delay influence by using the Fuzzy controller input which was the deviation and the deviation change rate of the predictive output and set-value. At last it had designed the feedback compensation predictive model of Fuzzy controller, which made the value of over control in Fuzzy-PID controller with the predictive model reduce from 3% to nearly zero, and it had better stability. The simulation curves showed that the control program had better control result.