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Abstract and Applied Analysis
Volume 2014 (2014), Article ID 872418, 10 pages
Research Article

Automatic Gauge Control in Rolling Process Based on Multiple Smith Predictor Models

1School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China
2School of International Studies, Communication University of China (CUC), Beijing 100024, China

Received 13 August 2014; Accepted 12 September 2014; Published 24 November 2014

Academic Editor: Shen Yin

Copyright © 2014 Jiangyun Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Automatic rolling process is a high-speed system which always requires high-speed control and communication capabilities. Meanwhile, it is also a typical complex electromechanical system; distributed control has become the mainstream of computer control system for rolling mill. Generally, the control system adopts the 2-level control structure—basic automation (Level 1) and process control (Level 2)—to achieve the automatic gauge control. In Level 1, there is always a certain distance between the roll gap of each stand and the thickness testing point, leading to the time delay of gauge control. Smith predictor is a method to cope with time-delay system, but the practical feedback control based on traditional Smith predictor cannot get the ideal control result, because the time delay is hard to be measured precisely and in some situations it may vary in a certain range. In this paper, based on adaptive Smith predictor, we employ multiple models to cover the uncertainties of time delay. The optimal model will be selected by the proposed switch mechanism. Simulations show that the proposed multiple Smith model method exhibits excellent performance in improving the control result even for system with jumping time delay.