Title of article
Identification of state models using principal components analysis
Author/Authors
Hartnett، نويسنده , , M.K. and Lightbody، نويسنده , , G. and Irwin، نويسنده , , G.W.، نويسنده ,
Issue Information
دوفصلنامه با شماره پیاپی سال 1999
Pages
16
From page
181
To page
196
Abstract
A predictive state-space dynamic plant is identified using a two-stage approach based on principal components analysis. The procedure is applied to a simulated benchmark problem known as the overheads condensor reflux drum (OCRD) model, a non-linear multivariable plant with mixed dynamics. The identified model is validated against an independent test set and its step and frequency responses compared with a linearised analytical model of the OCRD.
Keywords
Prediction , PCA , State-space modelling
Journal title
Chemometrics and Intelligent Laboratory Systems
Serial Year
1999
Journal title
Chemometrics and Intelligent Laboratory Systems
Record number
1460114
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