A Data-Based Compact High-Order Volterra Model for Complex Blast Furnace System

Abstract

In this article, a data-based compact Volterra model is constructed to carry out the silicon prediction task. The main motivations are to, on the one hand, make better use of the strong memory ability of the Volterra series, which is suitable for reflecting the large inertia of the blast furnace process, on the other hand, overcome the difficulty that high complexity of the original Volterra models may result in serious overfitting. Six kinds of models, including single-input and two-input linear, second-order and third-order compact Volterra models, are successively designed and verified through a real blast furnace case. The reasonable agreement between the predicted values and the observed values indicates the compact Volterra model, especially the single-input third-order Volterra model, are powerful and competitive for describing the complex blast furnace system. The experimental results can serve as a guide for the blast furnace operators to judge the in-furnace thermal state change in time and further provide an indication on how to control the blast furnace in advance.