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Proceedings of 2009 International Symposium on Computer Science and Computational Technology (ISCSCT 2009)

Huangshan, China, December 26-28, 2009

Editors: Fei Yu, Guangxue Yue, Jian Shu, Yun Liu

AP Catalog Number: AP-PROC-CS-09CN005

ISBN: 978-952-5726-07-7 (Print), 978-952-5726-08-4 (CD-ROM)

Page(s): 147-150

Based on Exponential Smoothing Model of the Mill Self-learning Optimization Control

Xin Xiong, Xiaodong Wang, Zhou Wan, and Jiande Wu

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Steel rolling process control is the key working procedure of the steel yield process, and that the control of the rolling process is the important factor to affect the quality and cost of the product. This paper is focus on the mill control. Firstly, the model of the mill is founded by exponential smoothing. Then, the method of self-learning optimization can be used to control the model. The online model, model adaptive learning control method, and adaptive learning optimize method can be founded. The model adaptive of rolling control model, careless rolling, and extract rolling can be solved greatly. The control effect and and good performance are obtained.

Index Terms

exponential smoothing; self-learning; optimization; mill

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