Abstract
The force, torque and slab temperature models of each pass in the plate hotrolling process are established in this paper. In the first, an experimental model of a plate hot-rolling is represented. The structure of this model is in the neural network forms and predicts the steady-state values of force, torque and slab temperature. In the second part, the proposed dynamical models are compared with the classical empiric models commonly used in the rolling practice. The experimental data obtained from Eregli Iron and Steel Factory in Turkey was used for developing both of the models.
Original language | English |
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Pages (from-to) | 17-22 |
Number of pages | 6 |
Journal | IFAC-PapersOnLine |
Volume | 37 |
Issue number | 15 |
DOIs | |
Publication status | Published - 2004 |
Event | 11th IFAC Symposium on Automation in Mining, Mineral and Metal Processing, MMM 2004 - Nancy, France Duration: 8 Sept 2004 → 10 Sept 2004 |
Bibliographical note
Publisher Copyright:© 2004 lFAC.
Keywords
- Experimental Modeling
- Hot-rolling process
- Identification
- Neural networks