PubAg

Main content area

A New Subspace Identification Approach Based on Principal Component Analysis and Noise Estimation

Author:
Wu, Ping, Pan, HaiPeng, Ren, Jia, Yang, Chunjie
Source:
Industrial & Engineering Chemistry Research 2015 v.54 no.18 pp. 5106-5114
ISSN:
1520-5045
Subject:
activated sludge, chemistry, engineering, mathematical models, principal component analysis
Abstract:
In this paper, a new subspace identification approach based on principal component analysis (PCA) and noise estimation is developed for multivariable dynamic process modeling. In contrast to typical subspace identification methods based on standard PCA with instrumental variables, the noise term is first estimated and naturally eliminated in the proposed approach, and then a PCA procedure is used to determine system observability subspace and extract system matrices A, B, C, and D from the estimated observability subspace. For comparison with other typical subspace identification methods based on PCA, numerical simulation and activated sludge process benchmark modeling are included to demonstrate the superiority of the proposed approach and reveal the probable reason for unsatisfied B and D estimations derived by some subspace identification methods based on PCA.
Agid:
5382734