Automation on thermal control of blast furnace

Ryosuke Masuda; Yoshinari Hashimoto; Max Mulder; Marinus M.(René) van Paassen; Manabu Kano

doi:10.1016/j.dche.2023.100085

Automation on thermal control of blast furnace

Ryosuke Masuda, Yoshinari Hashimoto^*, Max Mulder, Marinus M.(René) van Paassen, Manabu Kano

^*Corresponding author for this work

Control & Simulation

Research output: Contribution to journal › Article › Scientific › peer-review

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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.

Original language	English
Article number	100085
Number of pages	10
Journal	Digital Chemical Engineering
Volume	7
DOIs	https://doi.org/10.1016/j.dche.2023.100085
Publication status	Published - 2023

Keywords

Hot metal temperature
Industrial application
Model predictive control
Process control

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10.1016/j.dche.2023.100085

1-s2.0-S2772508123000030-mainFinal published version, 6.22 MBLicence: CC BY

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title = "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, Industrial application, Model predictive control, Process control",

author = "Ryosuke Masuda and Yoshinari Hashimoto and Max Mulder and {van Paassen}, {Marinus M.(Ren{\'e})} and Manabu Kano",

year = "2023",

doi = "10.1016/j.dche.2023.100085",

language = "English",

volume = "7",

journal = "Digital Chemical Engineering",

issn = "2772-5081",

publisher = "Elsevier",

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TY - JOUR

T1 - Automation on thermal control of blast furnace

AU - Masuda, Ryosuke

AU - Hashimoto, Yoshinari

AU - Mulder, Max

AU - van Paassen, Marinus M.(René)

AU - Kano, Manabu

PY - 2023

Y1 - 2023

N2 - 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.

AB - 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.

KW - Hot metal temperature

KW - Industrial application

KW - Model predictive control

KW - Process control

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U2 - 10.1016/j.dche.2023.100085

DO - 10.1016/j.dche.2023.100085

M3 - Article

AN - SCOPUS:85148982622

SN - 2772-5081

VL - 7

JO - Digital Chemical Engineering

JF - Digital Chemical Engineering

M1 - 100085

ER -

Automation on thermal control of blast furnace

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