A dynamic subspace model for predicting burn-through point in iron sintering process

被引：17

作者：

Cao, Weihua ^{[1
,2
]}

Zhang, Yongyue ^{[3
]}

She, Jinhua ^{[1
,2
,4
]}

Wu, Min ^{[1
,2
]}

Cao, Yuan ^{[3
]}

机构：

[1] China Univ Geosci, Sch Automat, Wuhan 430074, Hubei, Peoples R China

[2] Hubei Key Lab Adv Control & Intelligent Automat C, Wuhan, Hubei, Peoples R China

[3] Cent S Univ, Sch Informat Sci & Engn, Changsha 410083, Hunan, Peoples R China

[4] Tokyo Univ Technol, Sch Engn, Tokyo 1920982, Japan

来源：

INFORMATION SCIENCES | 2018年 / 466卷

基金：

中国国家自然科学基金;

关键词：

Burning-through point; Subspace modeling method; Dynamic model; Sintering process; CONTROL TECHNOLOGY; IDENTIFICATION; OPTIMIZATION; SYSTEMS;

D O I：

10.1016/j.ins.2018.06.069

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents a dynamic modeling method for predicting the exhaust-gas temperature (EGT) of the burn-through point (BTP) in an iron sintering process. First, a subspace modeling method is used to build a steady-state subspace model (SSSM) for the EGT at a steady state. Then, a dynamic subspace model (DSM) that is driven by the errors of the SSSMs is developed to improve the accuracy of the EGT prediction in a continuous process. Finally, a grid search dynamic subspace model (GSDSM) is established to find the best parameters for each SSSM in the DSM. Verification results show that the GSDSM yields a predicted EGT with a high precision, which can be implemented in a predicting controller an actual sintering process. (C) 2018 Elsevier Inc. All rights reserved.

引用

页码：1 / 12

页数：12

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