Research And Application Of Intelligent Control On Tension Control

Because the algorithm of the conventional PID controller is simple and can improve the systematic dynamic characteristic and the steady characteristic, it is widely applied to tension control system. But while carrying on the roll tension control, the systematic parameter is changed according to the change of the diameter of the roller and the influence of some other detectable factors. The parameter of conventional PID controller is often exactly designed to a kind of situation and is invariable. So the conventional PID controller is very difficult to keep tension well. Then we design a kind of fuzzy neural network adaptive PID controller. In view of the real change of roll tension control, we use the fuzzy neural network controller to change the parameter of PID controller in time in order to enable it to adapt for the process with the change of object. Then we can realize the permanent tension control.In this article,we elaborate the fuzzy neural network control principle in detail. The fuzzy neural network control system mainly includes two parts: the fuzzy control system and the neural network system. We can adapt the learning capability of the neural network to the fuzzy control system and use it by the organization and the learning capability to realize seeking superior function of the fuzzy rule and adjust the subordination. The fuzzy neural network control system can overcome difficulty of the define of the neural network structure as well as the shortcoming of the learning capability of the fuzzy control. It can apply to more complicated system.We simulate this system in laboratory successfully. The system work stably and operate easily. It can obtain the satisfied performance and high stability, follows the source well. The time of control improve obviously. It improve the system antijamming ability and comprehensibly improve the dynamic performance of system. After a period of practical application, it has obviously obtained the better control characteristic of tension control compared to the conventional PID controller.