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Correlation analysis-based error compensation recursive least-square identification method for the Hammerstein model
文献类型:期刊论文
作者:Li, Feng[1]  Jia, Li[2]  
机构:[1]Shanghai Univ, Coll Mech Engn & Automat, Dept Automat, Shanghai Key Lab Power Stn Automat Technol, Shanghai 200072, Peoples R China.;
[2]Shanghai Univ, Coll Mech Engn & Automat, Dept Automat, Shanghai Key Lab Power Stn Automat Technol, Shanghai 200072, Peoples R China.;
通讯作者:Jia, L (reprint author), Shanghai Univ, Coll Mech Engn & Automat, Dept Automat, Shanghai Key Lab Power Stn Automat Technol, Shanghai 200072, Peoples R China.
年:2018
期刊名称:JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
卷:88
期:1
页码范围:56-74
增刊:正刊
学科:数学
所属部门:机电工程与自动化学院
语言:外文
ISSN:0094-9655
人气指数:5
浏览次数:5
基金:National Natural Science Foundation of China [61773251, 61374044]; Shanghai Municipal Science and Technology Commission [15510722100, 16111106300, 17511109400]; Shanghai Municipal Education Commission [14ZZ088]; Shanghai talent development plan
关键词:Hammerstein model; correlation analysis; error compensation; separable signal; 60E15; 60G05; 60H30; 60H40
摘要:
In this paper, the correlation analysis based error compensation recursive least-square (RLS) identification method is proposed for the Hammerstein model. Firstly, the covariance matrix between input and output data points of the Hammerstein model is derived by using separable signal to realize that the unmeasurable internal variable is replaced by the covariance matrix of input. Thus, the correlation analysis method can be accordingly used to estimate parameters of the linear part, which result ...More
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