Intelligent Coordinating Control Between Burn-Through Point and Mixture Bunker Level in an Iron Ore Sintering Process
Sheng Du*,**, Min Wu*,**,†, Xin Chen*,**, Xuzhi Lai*,**, and Weihua Cao*,**
*School of Automation, China University of Geosciences
Wuhan, Hubei 430074, China
**Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems
Wuhan, Hubei 430074, China
Sintering is a process that involves complex physical and chemical reactions. An intelligent coordinating control strategy is proposed for the strong coupling between the burn-through point (BTP) and the mixture bunker level (MBL). First, an intelligent integrated controller is established for the BTP by fusing the neural network, expert rules, and fuzzy logic. Moreover, an expert controller is designed for the MBL based on expert rules using the analysis of the main factors that affect the MBL. Furthermore, by employing the soft switching control algorithm, an intelligent coordinating controller for the BTP and the MBL is designed. The optimal operation parameters are obtained from the algorithm, which realize the multi-objective control of the sintering process. Finally, a simulation and an experiment of the intelligent coordinating control between the BTP and the MBL are carried out, where the models of the BTP and the MBL are the Takagi-Sugeno (T-S) fuzzy model and the linear model, respectively. And the results show that the proposed approach is feasible and effective.
-  M. H. Li and J. Wang, “The research for soft measuring technique of sintering burning through point,” IEEE Conf. on Industrial Electronics and Applications, pp. 1-4, 2006.
-  Y. Liu, J. Yang, J. Wang, Z. L. Cheng, and Q. W. Wang, “Energy and exergy analysis for waste heat cascade utilization in sinter cooling bed,” Energy, Vol.67, No.4, pp. 370-380, 2014.
-  W. Yang, S. Choi, E. S. Choi, D. W. Ri, and S. Kim, “Combustion characteristics in an iron ore sintering bed-evaluation of fuel substitution,” Combustion & Flame, Vol.145, No.3, pp. 447-463, 2006.
-  C. M. Dinis, G. N. Popa, and A. Iagar, “Modeling and simulation of processes from an iron ore sintering plant,” WSEAS Int. Conf. on System Science and Simulation in Engineering, pp. 119-124, 2008.
-  I. Koštial, P. Nemvcovsky, J. Terpak, and L. Dorvcak, “Optimization of the sintering process,” Metalurgija – Sisak then Zagreb –, Vol.40, No.2, pp. 67-70, 2001.
-  T. Kraft and H. Riedel, “Numerical simulation of solid state sintering model and application,” J. of the European Ceramic Society, Vol.24, No.2, pp. 345-361, 2004.
-  W. S. Cheng, “Prediction System of Burning Through Point (BTP) Based on Adaptive Pattern Clustering and Feature Map,” Int. Conf. on Machine Learning and Cybernetics, pp. 3089-3094, 2006.
-  J. H. Zhang, A. G. Xie, and F. M. Shen, “Multi-Objective Optimization and Analysis Model of Sintering Process Based on BP Neural Network,” J. of Iron & Steel Research Int., Vol.14, No.14, pp. 1-5, 2007.
-  R. Barea, J. Mochón, and A. Cores, “Fuzzy Control of Micum Strength for Iron Ore Sinter,” ISIJ Int., Vol.46, No.5, pp. 687-693, 2006.
-  M. Wu, P. Duan, W. H. Cao, J. H. She, and J. Xiang, “An intelligent control system based on prediction of the burn-through point for the sintering process of an iron and steel plant,” Expert Systems with Applications, Vol.39, No.5, pp. 5971-5981, 2012.
-  J. Xiang, M. Wu, W. H. Cao, and P. Duan, “Multi-objective optimal control based on fuzzy satisfying for sintering process,” CIESC J., Vol.61, No.8, pp. 2138-2143, 2010 (in Chinese).
-  H. Zhou, J. P. Zhao, L. C. Eng, E. B. George, and K. F. Cen, “Numerical Modeling of the Iron Ore Sintering Proces,” ISIJ Int., Vol.52, No.9, pp. 1550-1558, 2012.
-  J. Terpák, L. Dorvcák, I. Koštial, and L. Pivka, “Control of burn-through point for agglomeration belt,” Metalurgija – Sisak then Zagreb –, Vol.44, No.4, pp. 281-284, 2005.
-  X. Chen, B. Huang, M. Wu, and Y. He, “Coordinated optimal control based on priority for sintering process,” CIESC J., Vol.67, No.3, pp. 885-890, 2016 (in Chinese).
-  Y. Wang, X. Chen, M. Wu, and Y. He, “T-S fuzzy model based on time-delay state space for the control of burning through point,” The 32nd Chinese Control Conf., pp. 1940-1944, 2013 (in Chinese).
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