Geometric properties of partial least squares for process monitoring

被引:298
作者
Li, Gang [2 ]
Qin, S. Joe [1 ,3 ]
Zhou, Donghua [2 ]
机构
[1] Univ So Calif, Mork Family Dept Chem Engn & Mat Sci, Los Angeles, CA 90089 USA
[2] Tsinghua Univ, TNList, Dept Automat, Beijing 100084, Peoples R China
[3] Univ So Calif, Ming Hsieh Dept Elect Engn, Los Angeles, CA 90089 USA
关键词
Partial least squares (PLS); Weight-deflated PLS (W-PLS); Simplified PLS (SIMPLS); Process monitoring; DIAGNOSIS;
D O I
10.1016/j.automatica.2009.10.030
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Projection to latent structures or partial least squares (PLS) produces output-supervised decomposition on input X, while principal component analysis (PCA) produces unsupervised decomposition of input X In this paper, the effect of output Y on the X-space decomposition in PLS is analyzed and geometric properties of the PLS structure are revealed. Several PUS algorithms are compared in a geometric way for the purpose of process monitoring. A numerical example and a case study are given to illustrate the analysis results. (C) 2009 Elsevier Ltd. All rights reserved.
引用
收藏
页码:204 / 210
页数:7
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