ISIJ International
Online ISSN : 1347-5460
Print ISSN : 0915-1559
ISSN-L : 0915-1559
Strip Thickness Control of Reversing Mill Using Self-tuning PID Neurocontroller
J. FanA. K. TieuW. Y. D. Yuen
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1999 Volume 39 Issue 1 Pages 39-46


A self-tuning PID control approach is presented for improvement of the head and tail strip thickness accuracy in a reversing cold mill for offering a cost saving. A neural network is used on-line to tune the parameters of a conventional PID controller in AGC to improve the response of strip thickness during a transient rolling process, which results in a reduction of off-gauge strip length. The effectiveness of the presented approach has been demonstrated through a simulation example. The results of simulation show that a neural network can reduce the strip thickness error quickly during mill starting process while the Pl controller parameters are being tuned on-line, so that a saving of off-gauge strip length about 73% is achieved.

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© The Iron and Steel Institute of Japan
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