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A neural network controls the galvannealing process

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4 Author(s)
Schiefer, C. ; Inst. for Machine & Process Autom., Wien Univ. of Technol., Austria ; Rubenzucker, F.X. ; Jorgl, H.P. ; Aberl, H.R.

High-quality galvanized steel strip is a need of today's manufacturers of various products. In particular, in the top quality section, steel strips for the automotive, building and consumer goods industries, only those steel producers who are applying state-of-the-art process technologies will be successful. For this reason, VOEST-ALPINE Industrieanlagenbau GmbH (VAI) and VOEST-ALPINE Stahl Linz have developed a new galvannealing control system to optimize this metallurgical process. As the latest improvement of the galvannealing control strategy, a neural network controller has been developed by VAI in cooperation with the Christian Doppler Laboratory for Intelligent Control Methods for Process Technologies, Vienna University of Technology. This paper describes the galvannealing process as far as it is necessary for the understanding of the controller functions, the controller structure and its essential functions. Furthermore, the used neural network structure and its integration in the controller system are explained. A discussion of simulation and practical operation results shows the improvements achieved by using a neural network controller in comparison to the conventional controller

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Industry Applications, IEEE Transactions on  (Volume:35 ,  Issue: 1 )