Control Method for Hydraulic Looper of Rolling Mill Based on RBF-NN
According to the unstable situation of tension control for hydraulic loop of rolling mill, the analysis is carried to the operating characteristics of the system. The result shows that the system is a multivariate and non-line system. Generally, the requirement is not met by application of the traditional control methods. But the neural networks are applied broadly in the control field. It shows that the neural network control is more appropriate to the multivariate and non-line system. The RBF-NN is better than the general NN in the areas about approximation capability and sorting ability and speed, therefore, RBF-NN control strategy is used in the system. The applied results show that the effect is similar to RBF-NN and Inverse Linear Quadratic (ILQ) when the change of position and tension is not in a large scope. When the change of position and the tension is fast, the result is improved distinctly by the RBF control mode and the 1LQ can do nothing.
RBF neural network hydraulic looper
Chen Kuisheng Tu Fuquan Wang Rui Li Yuanhui Zheng Liang
College of Machinery & Automation, Wuhan University of Science and Technology, JicmsheYiLu.Wuhan, Hubei, 430081, China
国际会议
北戴河
英文
570-573
2007-06-06（万方平台首次上网日期，不代表论文的发表时间）