A Comparison Study of Subspace Identification of Blast Furnace Ironmaking Process

被引:1
作者
Zhou, HaiYun [1 ,2 ]
Wu, Ping [3 ]
机构
[1] Xi An Jiao Tong Univ, Sch Econ & Finance, Xian 710061, Peoples R China
[2] Nanjing Forest Police Coll, Sch Publ Secur, Nanjing 210023, Peoples R China
[3] Zhejiang Sci Tech Univ, Fac Mech Engn & Automat, Hangzhou 310018, Peoples R China
基金
中国国家自然科学基金;
关键词
Blast Furnace Ironmaking Process; Molten Iron Silicon Content; Subspace Identification; Closed Loop Data; METAL-SILICON CONTENT; PREDICTION; MODELS; TIME;
D O I
10.1252/jcej.19we135
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Blast Furnace (BF) iron making process is an extremely complex industrial process. The molten iron silicon content is considered as an important indicator of the thermal status of the blast furnace. The stabilization control of blast furnace depends on the molten iron silicon content. Three classic subspace identification methods including MOESP (Multivariable Output-Error State sPace), CVA (Canonical Variate Analysis) and SSARX (Subspace identification method ARX) are considered to establish the state space model of blast furnace ironmaking process. The inputs to the model are the most responsible and easily measured variables for the fluctuation of thermal state in blast furnace while the output to the model is the molten iron silicon content. The identified state space models are then tested on datasets obtained from No.1 BF in LiuGang Iron and Steel Group Co. of China. Experiment results show that the blast furnace ironmaking process can be reliably modeled by these subspace identification methods. Further, the SSARX method outperforms over the other two subspace identification methods with closed loop data.
引用
收藏
页码:540 / 545
页数:6
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