Design Of Intelligent PID Control System For Reactor Temperature

Reactor is an important equipment in pharmaceutical,food,light industry,resin and chemical production process.The chemical reaction mechanism in the reactor is more complex.The system itself has large time-varying,nonlinear and time-lag properties.Because of the chemical reaction of process parameters in the measurement method is very complicated,controlling the reaction temperature becomes an effective way to control product quality.The conventional PID control is a control method based on process parameters,which has the advantages of simple control principle,good stability,high reliability and easy adjustment of parameters.However,the design of the controller depends on the precise mathematical model of the controlled model.Because of the complex reaction mechanism and the changing of parameters in the process of system reaction,it is difficult to establish an accurate mathematical model,and it is difficult to adjust the parameters and solve the relative stability of the system.Therefore,using conventional PID controller can not realize the accurate control of reactor temperature.In this case,it is of great significance to study the intelligent PID control of the reactor temperature.The subject takes the reactor temperature control as the study object,the conventional PID control,fuzzy adaptive PID control,fuzzy RBF neural network PID control and dynamic matrix prediction PID control are specifically studied.First of all,aiming at a certain chemical reaction process,the reactor temperature control is taken as the goal.The PID parameters are set by SMPT-1000 simulation platform and PCS7 software.The simulation curves are obtained through experiments,and the regulation rules and methods of conventional PID parameters in temperature control system are summarized.In order to solve the problem that the design of the conventional PID controller depends on the precise mathematical model of the controlled object,a fuzzy adaptive PID controller is designed.Through simulation experiments and compared with the conventional PID control method,it is proved that the fuzzy adaptive PID control has better control performance and stronger self-adaptive ability.At the same time,in order to make the PID controller have a certain ability of self-regulating control parameters,an improved fuzzy RBF neural network intelligent control method is proposed,and the fuzzy RBF neural network PID controller is designed.After MATLAB simulation,it shows that the method has better control performance and stronger robustness.In view of the complexity of the reactor temperature control,the design uses predictive control to improve the control accuracy and efficiency of system.Dynamic matrix control(DMC)algorithm is a kind of optimization control algorithm based on object step response prediction model,rolling implementation and combined with feedback correction.The dynamic matrix predictive PID controller is designed,after MATLAB simulation,it is proved that this method can maintain better control effect for disturbance and different controlled objects.