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Transient model-based operation guidance on blast furnace
Affiliation:1. Department of Systems Science, Kyoto University, Kyoto 606-8501, Japan;2. Ironmaking Research Lab., Process Research Laboratories, Nippon Steel Corporation, 20-1, Shintomi, Futtsu, Chiba 293–8511, Japan;1. Process Dynamics and Operations Group, Department of Biochemical and Chemical Engineering, TU Dortmund, Emil Figge Straße 70, 44227 Dortmund, Germany;2. Process Optimisation Iron and Steel Making Department, VDEh-Betriebsforschunginstitut GmbH, Sohnstraβe 65, 40237 Düsseldorf, Germany;3. thyssenkrupp Steel Europe AG, Kaiser-Wilhelm-Straβe 100, 47166 Duisburg, Germany;1. Department of Particulate Flow Modelling, Johannes Kepler University, Linz, Austria;2. Ironmaking R&D, voestalpine Stahl GmbH, Linz, Austria;3. Linz Institute of Technology (LIT), Johannes Kepler University, Linz, Austria;1. Department of Systems Science, Kyoto University, Kyoto, 606–8501, Japan;2. Ironmaking Research Lab., Process Research Laboratories, Chiba, Nippon Steel & Sumitomo Metal Corporation, 20-1, Shintomi, Futtsu, 293–8511, Japan
Abstract:To reduce the heat variance and realize the stable operation of a blast furnace, an operation guidance system was developed. This system involves nonlinear model predictive control based on a new transient model and provides appropriate guidance to operators. Accurate future prediction is a key to success because the huge heat capacity of the blast furnace leads to slow, complex dynamics with long dead time. The online validation results in the actual furnace showed that the standard deviation of the hot metal temperature was reduced by 3.7 °C when the operators followed the guidance provided by the developed system.
Keywords:Model predictive control  Blast furnace  Numerical simulation  Hot metal temperature  Operation guidance
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