Steady-state Detection for Multivariate Systems Based on Pca and Wavelets
نویسندگان
چکیده
Steady-state detection has been an important tool in data processing, for nonlinear model identification, real time optimization, variability analysis, and so on. In this article, it is proposed a new methodology applied to multivariate systems for steadystate detection based on PCA and wavelets. The proposed approach is applied to an industrial distillation column. The combination of PCA and wavelets allows quantifying the steady-state considering a single variable generated by a PCA projection. Copyright © 2006 IFAC
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تاریخ انتشار 2006