Noise variance estimate for blast furnace temperature of hot metal based on Autoregressive model in presence of noise

被引：0
|
作者：
Zhang, Yong [1 ,2 ]
Zhao, Zhe [1 ]
Cui, Guimei [1 ]
机构：
[1] Inner Mongolia Univ Sci & Technol, Sch Informat Engn, Baotou 014010, Peoples R China
[2] Northeastern Univ, State Key Lab Synthetically Automat Proc Ind, Shenyang 110819, Peoples R China
来源：
2015 27TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC) | 2015年
关键词：
Parameter Estimate; Noise Variance; Noisy AutoRegressive (AR) Model; Blast Furnace; PARAMETER-ESTIMATION; SYSTEMS; ALGORITHM;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Noise variance is an important variable for data filtering. In order to estimate the noise variance of hot iron temperature in process of blast furnace (BF) ironmaking, this work will study parameter estimate of AutoRegressive (AR) process in presence of noise based on BF observed data. Furthermore, a given instrumental variable choosing method and recursive least squares algorithm will be delivered in this paper. The proposed method requires loose assumptions, which are more close to the data fact in blast furnace ironmaking process. Finally, noise variance estimate results are shown by simulation tests.
引用
收藏
页码：6461 / 6465
页数：5
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