Simulation and Research on Pulp Consistency Control System

Due to the problems of delay,nonlinear and time-varying for pulp consistency,the conventional PID control effects are not ideal.To improve the performances of pulp consistency control system,the BP neural network and a new type of controller called PIDNN were applied in this paper,which coalesces traditional PID and neural network together.Through the model identification and control problems analyses of pulp consistency,the BP and PIDNN were used for simulations and contrast research.The results show that the simulation effects with both BP and PIDNN are satisfactory.However,the BP neural network has complex structure and its parameters are difficult to adjust,while the PIDNN has the advantages of conventional PID for its simple construction and definite physical meaning of parameters,and also has good adaptability and strong robustness of neural network.It is an appropriate and simple control method for the complex control system and good accuracy for real-time control.