Automation on thermal control of blast furnace

Abstract

Accurate process control through automation is the key to achieving efficient and stable operation of a blast furnace. In this study, we developed an automatic control system of hot metal temperature (HMT). To cope with the slow and complex process dynamics of the blast furnace, we constructed a control algorithm that predicts eight-hour-ahead HMT using a two-dimensional (2D) transient model and calculates optimal target pulverized coal ratio (PCR) and pulverized coal flow rate by non-linear model predictive control (NMPC). An evaluation in a real plant showed that the developed control system suppressed the effects of disturbances, such as changes in the coke ratio and blast volume, on the HMT. The root mean square (RMS) of the control deviation of HMT was successfully reduced by 1.6 °C compared to the conventional manual operation.

Keywords

• Hot metal temperature
• Model predictive control
• Industrial application
• Process control