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A Intelligent Control Model of Hot Metal Desulphurization Process

机译:铁水脱硫过程智能控制模型

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摘要

In view of the shortcomings that traditional desulphurization control model's low precision and low auto-adapted ability, according to the mechanism of hot metal desulphurization process, the intelligent control model based on RBF nerve network and feedback consumption control method is introduced. The model uses RBF nerve work technology to build desulphurization control model, uses feedback compensation method to solve model failure problem caused by desulphurization powder quality change. The emulate contrast shows the mathematical model can suffice for the requirement of desulphurization control, can reduce consumption of desulphurization powder effectively. This is the paper style requirement for the Chinese Control and Decision Conference. The writers of papers should and must provide normalized electronic documents in order for readers to search and read papers conveniently.
机译:针对传统脱硫控制模型精度低,自适应能力差的不足,针对铁水脱硫过程机理,提出了基于RBF神经网络和反馈消耗控制方法的智能控制模型。该模型采用RBF神经工作技术建立脱硫控制模型,采用反馈补偿法解决了脱硫粉质量变化引起的模型失效问题。仿真对比表明,该数学模型可以满足脱硫控制的要求,可以有效减少脱硫粉的消耗。这是中国控制与决策会议的论文样式要求。论文的作者应该并且必须提供标准化的电子文档,以便读者方便地搜索和阅读论文。

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