Dynamic network identification using the direct prediction-error method

A.G. Dankers; P.M.J. Hof, Van den; P.S.C. Heuberger; X. Bombois

doi:10.1109/CDC.2012.6426780

Dynamic network identification using the direct prediction-error method

A.G. Dankers, P.M.J. Hof, Van den, P.S.C. Heuberger, X. Bombois

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

9 Citations (Scopus)

1 Downloads (Pure)

Abstract

The problem of identifying dynamical models on the basis of measurement data is usually considered in a classical open-loop or closed-loop setting. In this paper this problem is generalized to linear dynamical systems that operate in a complex interconnection structure and the dynamical relationships between the measured variables signals need to be identified. It is shown that the classical Direct Method of closed-loop identification in the prediction-error context can be generalized to provide consistent model estimates, under specified experimental circumstances.

Original language	English
Title of host publication	Proceedings of the 51st IEEE Conference on Decision and Control (CDC 2012), 10-13 December 2012, Maui, Hawai
Place of Publication	Piscataway
Publisher	Institute of Electrical and Electronics Engineers
Pages	901-906
DOIs	https://doi.org/10.1109/CDC.2012.6426780
Publication status	Published - 2012
Event	51st IEEE Conference on Decision and Control, CDC 2012 - Maui, United States Duration: 10 Dec 2012 → 13 Dec 2012 Conference number: 51

Conference

Conference	51st IEEE Conference on Decision and Control, CDC 2012
Abbreviated title	CDC 2012
Country/Territory	United States
City	Maui
Period	10/12/12 → 13/12/12

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10.1109/CDC.2012.6426780

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Dankers, A. G., Hof, Van den, P. M. J., Heuberger, P. S. C., & Bombois, X. (2012). Dynamic network identification using the direct prediction-error method. In Proceedings of the 51st IEEE Conference on Decision and Control (CDC 2012), 10-13 December 2012, Maui, Hawai (pp. 901-906). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/CDC.2012.6426780

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title = "Dynamic network identification using the direct prediction-error method",

abstract = "The problem of identifying dynamical models on the basis of measurement data is usually considered in a classical open-loop or closed-loop setting. In this paper this problem is generalized to linear dynamical systems that operate in a complex interconnection structure and the dynamical relationships between the measured variables signals need to be identified. It is shown that the classical Direct Method of closed-loop identification in the prediction-error context can be generalized to provide consistent model estimates, under specified experimental circumstances.",

author = "A.G. Dankers and {Hof, Van den}, P.M.J. and P.S.C. Heuberger and X. Bombois",

year = "2012",

doi = "10.1109/CDC.2012.6426780",

language = "English",

pages = "901--906",

booktitle = "Proceedings of the 51st IEEE Conference on Decision and Control (CDC 2012), 10-13 December 2012, Maui, Hawai",

publisher = "Institute of Electrical and Electronics Engineers",

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note = "51st IEEE Conference on Decision and Control, CDC 2012, CDC 2012 ; Conference date: 10-12-2012 Through 13-12-2012",

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Dankers, AG, Hof, Van den, PMJ, Heuberger, PSC & Bombois, X 2012, Dynamic network identification using the direct prediction-error method. in Proceedings of the 51st IEEE Conference on Decision and Control (CDC 2012), 10-13 December 2012, Maui, Hawai. Institute of Electrical and Electronics Engineers, Piscataway, pp. 901-906, 51st IEEE Conference on Decision and Control, CDC 2012, Maui, Hawaii, United States, 10/12/12. https://doi.org/10.1109/CDC.2012.6426780

Dynamic network identification using the direct prediction-error method. / Dankers, A.G.; Hof, Van den, P.M.J.; Heuberger, P.S.C. et al.
Proceedings of the 51st IEEE Conference on Decision and Control (CDC 2012), 10-13 December 2012, Maui, Hawai. Piscataway: Institute of Electrical and Electronics Engineers, 2012. p. 901-906.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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T1 - Dynamic network identification using the direct prediction-error method

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AU - Hof, Van den, P.M.J.

AU - Heuberger, P.S.C.

AU - Bombois, X.

N1 - Conference code: 51

PY - 2012

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N2 - The problem of identifying dynamical models on the basis of measurement data is usually considered in a classical open-loop or closed-loop setting. In this paper this problem is generalized to linear dynamical systems that operate in a complex interconnection structure and the dynamical relationships between the measured variables signals need to be identified. It is shown that the classical Direct Method of closed-loop identification in the prediction-error context can be generalized to provide consistent model estimates, under specified experimental circumstances.

AB - The problem of identifying dynamical models on the basis of measurement data is usually considered in a classical open-loop or closed-loop setting. In this paper this problem is generalized to linear dynamical systems that operate in a complex interconnection structure and the dynamical relationships between the measured variables signals need to be identified. It is shown that the classical Direct Method of closed-loop identification in the prediction-error context can be generalized to provide consistent model estimates, under specified experimental circumstances.

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DO - 10.1109/CDC.2012.6426780

M3 - Conference contribution

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BT - Proceedings of the 51st IEEE Conference on Decision and Control (CDC 2012), 10-13 December 2012, Maui, Hawai

PB - Institute of Electrical and Electronics Engineers

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T2 - 51st IEEE Conference on Decision and Control, CDC 2012

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ER -

Dynamic network identification using the direct prediction-error method

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