DocumentCode :
1349345
Title :
Development of an optimal crown/shape level-2 control model for rolling mills with multiple control devices
Author :
Guo, Remn-Min
Author_Institution :
ARMCO Res. & Technol., Middletown, OH., USA
Volume :
6
Issue :
2
fYear :
1998
fDate :
3/1/1998 12:00:00 AM
Firstpage :
172
Lastpage :
179
Abstract :
Three development stages of an online crown/shape control model are discussed. Each stage bears specific consideration and provides variable information for mill operations. Theoretical derivation of the first stage facilitates understanding of mill rolling behavior. Usage of the crown/shape model leads to the development of the linear crown control system. The second-stage development is to generate an offline simulation model which bridges the gap between theory and application. It is used to verify the theoretical model, to determine control gain factors, and even to examine stability of the control algorithm. The real-time process model is last when conducting mill setup calculations. It has to cope with uncertainties of measured devices, possible errors of the theoretical model, and real-world disturbance of mill operating conditions. Providing a stable, optimal, and accurate setup for the mill is its major responsibility. Statistical methods are used everywhere in these models from tuning to optimizing processes. This optimal linear crown/shape control system has been successfully applied to a production hot strip mill since 1992. The article describes development and application of this rolling model
Keywords :
adaptive control; learning systems; metallurgical industries; optimal control; process control; rolling mills; shape control; statistical analysis; control gain factors; linear crown control system; mill operations; offline simulation model; optimal crown/shape level-2 control model; real-time process model; rolling behavior; rolling mills; statistical methods; Bridges; Control system synthesis; Measurement uncertainty; Milling machines; Optimal control; Optimization methods; Production systems; Shape control; Stability; Statistical analysis;
fLanguage :
English
Journal_Title :
Control Systems Technology, IEEE Transactions on
Publisher :
ieee
ISSN :
1063-6536
Type :
jour
DOI :
10.1109/87.664184
Filename :
664184
Link To Document :
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