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

Authors:
Min Wu;Ping Duan;Weihua Cao;Jinhua She;Jie Xiang
Affiliations:
School of Information Science and Engineering, Central South University, Changsha, Hunan, China;School of Information Science and Engineering, Central South University, Changsha, Hunan, China;School of Information Science and Engineering, Central South University, Changsha, Hunan, China;School of Information Science and Engineering, Central South University, Changsha, Hunan, China and School of Computer Science, Tokyo University of Technology, Tokyo, Japan;School of Information Science and Engineering, Central South University, Changsha, Hunan, China
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

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Abstract

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.