Publication Type |
Journal Article |
Title |
Determination of state-space model uncertainty using bootstrap techniques |
Authors |
Vitor V. Lopes Carla I C Pinheiro Jose Cardoso de Menezes |
Groups |
CATHPRO |
Journal |
JOURNAL OF PROCESS CONTROL |
Year |
2006 |
Month |
August |
Volume |
16 |
Number |
7 |
Pages |
685-692 |
Abstract |
Robust control theory is widely used as the theoretical basis for the design of controllers with reduced sensibility to model errors. The model parameters variance-covariance (VC) matrix allows to design controllers with a consistent control action, even in the presence of moderate model mismatch. This paper presents a technique to extract the state-space model variance-covariance matrix using bootstrap techniques. The VC matrix is estimated from bootstrapped models using a first-order approximation of the model parameters space. The technique is applied by estimating the nominal model uncertainty of a deisopentanizer petrochemical unit. The model uncertainty is determined more accurately by the proposed method, when compared to the use of minimal canonical parameterization, providing better first-order approximation confidence intervals. (C) 2006 Elsevier Ltd. All rights reserved. |
DOI |
http://dx.doi.org/10.1016/j.jprocont.2006.01.007 |
ISBN |
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Publisher |
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Book Title |
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ISSN |
0959-1524 |
EISSN |
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Conference Name |
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Bibtex ID |
ISI:000238557900003 |
Observations |
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