An intelligent control system based on prediction of the burn-through point for the sintering process of an iron and steel plant

被引:23
|
作者
Wu, Min [2 ]
Duan, Ping [2 ]
Cao, Weihua [2 ]
She, Jinhua [1 ,2 ]
Xiang, Jie [2 ]
机构
[1] Tokyo Univ Technol, Sch Comp Sci, Tokyo, Japan
[2] Cent S Univ, Sch Informat Sci & Engn, Changsha, Hunan, Peoples R China
基金
国家高技术研究发展计划(863计划);
关键词
Burn-through point (BTP); Hierarchical configuration; Grey theory; Hybrid fuzzy-predictive control; Neural network; Prediction model; Satisfactory solution principle; Sintering process; Soft sensing; FUZZY CONTROL; OPTIMIZATION;
D O I
10.1016/j.eswa.2011.11.118
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper concerns an intelligent control system based on prediction of the burn-through point (BTP) of the sintering process of an iron and steel plant. The system has a two-level hierarchical configuration: intelligent-control level and basic-automation level. At the intelligent-control level, first, a BTP prediction model is derived using an intelligent, integrated modeling method based on grey theory and back-propagation neural networks. Next, a hybrid fuzzy-predictive controller for the BTP is established using fuzzy control, predictive control, and a flexible switching control strategy. Finally, an intelligent coordinating control algorithm based on the satisfactory solution principle is employed to coordinate BTP control and bunker-level control. Then, a satisfactory sinter strand velocity is obtained and used as the target value. The basic-automation level regulates the speed of the motor driving the strand so as to make the strand velocity track the target value. The results of actual runs show that the system adequately suppresses the variation in BTP, increases the quantity and quality of sintering agglomerate, and ensures process safety. (C) 2011 Elsevier Ltd. All rights reserved.
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页码:5971 / 5981
页数:11
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