Li Peng, Qing Li, and Zhou Zhou, Cooling hot rolling steel strip using combined tactics, J. Univ. Sci. Technol. Beijing, 15(2008), No. 3, pp. 362-365. https://doi.org/10.1016/S1005-8850(08)60068-7
Cite this article as:
Li Peng, Qing Li, and Zhou Zhou, Cooling hot rolling steel strip using combined tactics, J. Univ. Sci. Technol. Beijing, 15(2008), No. 3, pp. 362-365. https://doi.org/10.1016/S1005-8850(08)60068-7
Li Peng, Qing Li, and Zhou Zhou, Cooling hot rolling steel strip using combined tactics, J. Univ. Sci. Technol. Beijing, 15(2008), No. 3, pp. 362-365. https://doi.org/10.1016/S1005-8850(08)60068-7
Citation:
Li Peng, Qing Li, and Zhou Zhou, Cooling hot rolling steel strip using combined tactics, J. Univ. Sci. Technol. Beijing, 15(2008), No. 3, pp. 362-365. https://doi.org/10.1016/S1005-8850(08)60068-7
The coiling temperature control of a typical steel strip mill was investigated. Due to the high speed of a strip and complex circumstance, it is very hard to set up a cooling model with high accuracy. A simplified dynamic model was proposed, based on which a cooling control scheme with combined feedforward, feedback and adaptive algorithms was developed. Meanwhile, the genetic algorithms were used for the optimization of model parameters. Simulations with a model validated using actual plant data were conducted, and the results have confirmed the effectiveness of the proposed control methods. At last, a simulation system for coiling temperature control was developed. It can be used for new product trials and newcomer training.
The coiling temperature control of a typical steel strip mill was investigated. Due to the high speed of a strip and complex circumstance, it is very hard to set up a cooling model with high accuracy. A simplified dynamic model was proposed, based on which a cooling control scheme with combined feedforward, feedback and adaptive algorithms was developed. Meanwhile, the genetic algorithms were used for the optimization of model parameters. Simulations with a model validated using actual plant data were conducted, and the results have confirmed the effectiveness of the proposed control methods. At last, a simulation system for coiling temperature control was developed. It can be used for new product trials and newcomer training.
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