DocumentCode :
3451014
Title :
A Method to Improve Model Calculation Accuracy of Process Control in Tandem Cold Mills
Author :
Wang, J.S. ; Jiang, Z.Y. ; Tieu, A.K. ; Liu, X.H. ; Wang, G.D.
Author_Institution :
Wollongong Univ., Wollongong
fYear :
2007
fDate :
23-25 May 2007
Firstpage :
2787
Lastpage :
2790
Abstract :
An adaptive learning algorithm using laser velocity meter is proposed for the process control of tandem cold mills. This method is used for on-line adaptive learning calculation of deformation resistance of strip and rolling friction models. The reverse calculation values of deformation resistance and friction coefficient as variables of non-linear equations can be obtained by introducing the measured rolling force and forward slip into the calculation model individually. Using Newton-Raphson iterative calculation to solve the non-linear equations, the reverse calculation values as actual values can be calculated. The actual forward slip obtained from the measured strip rolling speed using laser meter makes it possible that the deformation resistance of strip and friction coefficient can be uncoupled for model adaptive learning calculation. The inverse calculation and adaptive learning can improve whole control system of tandem cold mills significantly.
Keywords :
Newton-Raphson method; adaptive control; milling; nonlinear equations; process control; Newton-Raphson iterative calculation; Process Control; Tandem Cold Mills; adaptive learning algorithm; deformation resistance; friction coefficient; laser velocity meter; model calculation accuracy; non-linear equations; Accuracy; Adaptive control; Deformable models; Friction; Laser modes; Milling machines; Nonlinear equations; Process control; Programmable control; Strips;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics and Applications, 2007. ICIEA 2007. 2nd IEEE Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-0737-8
Electronic_ISBN :
978-1-4244-0737-8
Type :
conf
DOI :
10.1109/ICIEA.2007.4318919
Filename :
4318919
Link To Document :
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