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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Hütter, Sebastian
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article
Data based model predictive control for ring rolling
Abstract
<p>Thermomechanical ring rolling is an evolution of the process where deformation and heat treatment are combined to obtain a product with both the desired geometry and hardness or microstructure in a single step. However, the high sensitivity of the process to the initial condition and to various disturbances limits its repeatability and accuracy. In this paper, the authors implement a concept for hardness control of ring rolling in virtual experiments. A concept based on soft sensors and model predictive control is implemented on a digital twin. The operation of the different models needed for this control loop are detailed and the controller itself is illustrated.</p>