Research on Neural Network Self-Tuning PID Control Strategy for Rolling Force Control System of Skin Pass Mill

In order to improve the dynamic characteristics of rolling force control system and enhance the control precision of elongation rate in skin pass mill,the control strategy was studied based on the analysis of rolling force control model.According to the electro hydraulic coupling characteristics,parameters time variant characteristics,external disturbances and nonlinear characteristics of the rolling control system,a neural network self-tuning PID controller based on improved BP algorithm was proposed and the simulation analysis was carried out on the response characteristics.The results show that the neural network self-tuning PID controller has better performance than conventional PID controller and has good control performance in nonlinear and time variant system.