In the continuous casting of steel, there is a variety of dynamic situations, both planned such as changing the steel grade, tundish replacement and unplanned such as breakout system interventions, equipment failure, etc. These situations cause variations of the casting parameters such as of the casting speed, casting temperature, intensity of cooling in the secondary cooling zone, etc. An improper configuration of casting parameters can negatively affect the quality of semi-finished products. A real-time tool based on a fuzzy-predictive control algorithm with the 3D dynamic solidification model was created. The real-time predictive control simulation is provided with the use of massive GPU source-code parallelization. Software implementation and integration to the Level 2 automatization system is also shown. Results are presented for the case with a casting-speed drop and for a slab caster with 17 cooling loops in the secondary cooling zone.Keywords: Secondary Cooling, Fuzzy control, Model predictive control, GPU calculation
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