A comparison of grey-box and black-box approaches in nonlinear state-space modelling and identification.

Jean-Philippe Noel; Joannes Schoukens; Gaetan Kerschen

A comparison of grey-box and black-box approaches in nonlinear state-space modelling and identification.

Jean-Philippe Noel, Joannes Schoukens, Gaetan Kerschen

Elektriciteit

Onderzoeksoutput: Meeting abstract (Book)

Samenvatting

Nonlinear system identiﬁcation constantly faces the compromise between the ﬂexibility of the ﬁtted model and its parsimony. Flexibility refers to the ability of the model to capture complex nonlinearities, while parsimony is its quality to possess a low number of parameters. In this regard, a nonlinear state-space representation.

Originele taal-2	English
Titel	34th Benelux Meeting on Systems and Control, Center Parcs "De Vossemeren", Lommel, 24th to 26th March, 2015
Aantal pagina's	1
Status	Published - 24 mrt. 2015
Evenement	34th Benelux Meeting on Systems and Control - Vossemeren, Lommel, Belgium Duur: 24 mrt. 2015 → 26 mrt. 2015

Seminar

Seminar	34th Benelux Meeting on Systems and Control
Land/Regio	Belgium
Stad	Lommel
Periode	24/03/15 → 26/03/15

Citeer dit

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title = "A comparison of grey-box and black-box approaches in nonlinear state-space modelling and identification.",

abstract = "Nonlinear system identiﬁcation constantly faces the compromise between the ﬂexibility of the ﬁtted model and its parsimony. Flexibility refers to the ability of the model to capture complex nonlinearities, while parsimony is its quality to possess a low number of parameters. In this regard, a nonlinear state-space representation.",

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T1 - A comparison of grey-box and black-box approaches in nonlinear state-space modelling and identification.

AU - Noel, Jean-Philippe

AU - Schoukens, Joannes

AU - Kerschen, Gaetan

PY - 2015/3/24

Y1 - 2015/3/24

N2 - Nonlinear system identiﬁcation constantly faces the compromise between the ﬂexibility of the ﬁtted model and its parsimony. Flexibility refers to the ability of the model to capture complex nonlinearities, while parsimony is its quality to possess a low number of parameters. In this regard, a nonlinear state-space representation.

AB - Nonlinear system identiﬁcation constantly faces the compromise between the ﬂexibility of the ﬁtted model and its parsimony. Flexibility refers to the ability of the model to capture complex nonlinearities, while parsimony is its quality to possess a low number of parameters. In this regard, a nonlinear state-space representation.

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KW - black-box

KW - tate-space modelling

KW - tate-space identification

M3 - Meeting abstract (Book)

BT - 34th Benelux Meeting on Systems and Control, Center Parcs "De Vossemeren", Lommel, 24th to 26th March, 2015

T2 - 34th Benelux Meeting on Systems and Control

Y2 - 24 March 2015 through 26 March 2015

ER -