Fuzzy Prediction of Molten Iron Silicon Content in BF Based on Hierarchical System

摘要

A hierarchical fuzzy system model is presented based on data driving, and then, the model is used to predict the molten iron silicon content in BF. As input variables this model uses the control parameters of a current BF such as moisture, pulverized coal injection, oxygen addition, coke ratio, etc. And variables employed to develop the model have been obtained from data collected online from Blast Furnace of Baotou Steel plant. This paper utilizes the fuzzy clustering algorithm combined nearest neighbor clustering and fuzzy c-means clustering to classify the input space. The simulation and error results show that the prediction based on hierarchical fuzzy model and data-driven method has good approximation and fit the output characteristics of the system. The most important point is that the number of fuzzy rules is greatly reduced.