Subspace Algorithms for the Identification of Multivariable Dynamic Errors-in-Variables Models

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• 作者：CHOU ; C.T. ; et. al.
• 关键词：System identification ; errors-in-variables ; subspace methods ; instrumental variable methods ; consistency ; closed-loop identification ; state-space models
• 刊名：Automatica
• 出版年：1997
• 出版时间：October, 1997
• 年：1997
• 卷：33
• 期：10
• 页码：1857-1869
• 全文大小：1.07 M

文摘

We consider the problem of identifying multivariable finite dimensional linear time-invariant systems from noisy input/output measurements. Apart from the fact that both the measured input and output are corrupted by additive white noise, the output may also be contaminated by a term which is caused by a white input process noise; furthermore, all these noise processes are allowed to be correlated with each other. We shall develop a solution to this problem in the framework of subspace identification and we shall show that our algorithms give consistent estimates when the system is operating in open- or closed-loop. Two realistic simulation studies are presented to demonstrate the practical applicability of the proposed algorithms. © 1997 Elsevier Science Ltd. Publisher: Elsevier Science Language of Publication: English Item Identifier: S0005-1098(97)00092-7 Publication Type: Article ISSN: 0005-1098 Cited by:

1. Gustafsson, Tony,""Subspace identification using instrumental variable techniques""Automatica2001pp. 2005-2010
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2. Li, Weihua; Qin, S. Joe,""Consistent dynamic PCA based on errors-in-variables subspace identification""Journal of Process Control2001pp. 661-678
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3. Wang, Jin; Qin, S. Joe,""A new subspace identification approach based on principal component analysis""Journal of Process Control2002pp. 841-855
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4. Soderstrom, Torsten; Soverini, Umberto; Mahata, Kaushik,""Perspectives on errors-in-variables estimation for dynamic systems""Signal Processing2002pp. 1139-1154
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5. Li, Weihua; Shah, Sirish,""Structured residual vector-based approach to sensor fault detection and isolation""Journal of Process Control2002pp. 429-443
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6. Kadali, Ramesh; Huang, Biao; Rossiter, Anthony,""A data driven subspace approach to predictive controller design""Control Engineering Practice2003pp. 261-278
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7. Li, Weihua; Raghavan, Harigopal; Shah, Sirish,""Subspace identification of continuous time models for process fault detection and isolation³""Journal of Process Control2003pp. 407-421
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8. Vajk, I.; Hetthessy, J.,""Identification of nonlinear errors-in-variables models""Automatica2003pp. 2099-2107
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9. Cao, Jin; Gertler, Janos,""Noise-induced bias in last principal component modeling of linear system""Journal of Process Control2004pp. 365-376
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10. Treasure, Richard J.; Kruger, Uwe; Cooper, Jonathan E.,""Dynamic multivariate statistical process control using subspace identification""Journal of Process Control2004pp. 279-292
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Footnotes:

1. This paper was not presented at any IFAC meeting. This paper was recommended for publication in revised form by Associate Editor H. Hjalmarsson under the direction of Editor Torsten Söderström.

2. Supported by a research fellowship of Delft University of Technology.

3. The earlier version of this paper was presented at the IFAC sponsored CHEMFAS-4 meeting in June, 2001, Korea.