The Transient Impulse Response Modeling Method and the Local Polynomial Method for Nonparametric System Identification

Michel Gevers; Per Hägg; Håkan Hjalmarsson; Rik Pintelon; Joannes Schoukens

doi:10.3182/20120711-3-BE-2027.00359

The Transient Impulse Response Modeling Method and the Local Polynomial Method for Nonparametric System Identification

Michel Gevers, Per Hägg, Håkan Hjalmarsson, Rik Pintelon, Joannes Schoukens

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Research output: Chapter in Book/Report/Conference proceeding › Conference paper

14 Citations (Scopus)

Abstract

This paper analyzes two recent methods for the nonparametric estimation of the Frequency Response Function (FRF) from input-output data using Prediction Error identification. Such FRF estimate can be the main goal of the identification exercise, or it can be a tool for the computation of a nonparametric estimate of the noise spectrum. We show that the choice of the method depends on the signal to noise ratio and on the objective. The method that delivers the best FRF estimate may not deliver the best estimate of the noise spectrum. Our theoretical analysis is illustrated by simulations.

Original language	English
Title of host publication	Proceedings of the 16th IFAC Symposium on System Identification, Brussels, Belgium, July 11-13, 2012
Publisher	Elsevier
Pages	55-60
Number of pages	6
ISBN (Print)	978-3-902823-06-9
DOIs	https://doi.org/10.3182/20120711-3-BE-2027.00359
Publication status	Published - 11 Jul 2012
Event	16th IFAC Symposium on System Identification (Sysid 2012) - SQUARE Brussels Meeting Center, Brussels, Belgium Duration: 11 Jul 2012 → 13 Jul 2012 http://www.sysid2012.org

Publication series

Name	IFAC Proceedings Volumes
Publisher	Elsevier
Number	16
Volume	45
ISSN (Electronic)	1474-6670

Conference

Conference	16th IFAC Symposium on System Identification (Sysid 2012)
Abbreviated title	Sysid 2012
Country/Territory	Belgium
City	Brussels
Period	11/07/12 → 13/07/12
Other	The scope of the symposium covers all major aspects of system identification, experimental modelling, signal processing and adaptive control, ranging from theoretical, methodological and scientific developments to a large variety of application areas. To enhance the applications and industrial perspective of the symposium, participation by authors from industry is particularly encouraged. It is the intention of the organizers to promote SYSID 2012 as a meeting place where scientists and engineers from several research communities can meet to discuss issues related to these areas.
Internet address	http://www.sysid2012.org

Keywords

System identification
onparametric identification
noise spectrum estimation

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10.3182/20120711-3-BE-2027.00359

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Persistent link

DWTC282: Dynamical systems, control and optimization
Pintelon, R. (Administrative Promotor), Vandewalle, J. (Co-Promotor), Aeyels, D. (Co-Promotor), Sepulchre, R. (Co-Promotor), Kinnaert, M. (Co-Promotor), Vande Wouwer, A. (Co-Promotor), Blondel, V. (Coördinator), Winkin, J. (Co-Promotor), Boyd, S. (Co-Promotor) & Leonard, N. (Co-Promotor)
1/04/12 → 30/09/17
Project: Fundamental

Cite this

Gevers, M., Hägg, P., Hjalmarsson, H., Pintelon, R., & Schoukens, J. (2012). The Transient Impulse Response Modeling Method and the Local Polynomial Method for Nonparametric System Identification. In Proceedings of the 16th IFAC Symposium on System Identification, Brussels, Belgium, July 11-13, 2012 (pp. 55-60). (IFAC Proceedings Volumes; Vol. 45, No. 16). Elsevier. https://doi.org/10.3182/20120711-3-BE-2027.00359

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abstract = "This paper analyzes two recent methods for the nonparametric estimation of the Frequency Response Function (FRF) from input-output data using Prediction Error identification. Such FRF estimate can be the main goal of the identification exercise, or it can be a tool for the computation of a nonparametric estimate of the noise spectrum. We show that the choice of the method depends on the signal to noise ratio and on the objective. The method that delivers the best FRF estimate may not deliver the best estimate of the noise spectrum. Our theoretical analysis is illustrated by simulations.",

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Gevers, M, Hägg, P, Hjalmarsson, H, Pintelon, R & Schoukens, J 2012, The Transient Impulse Response Modeling Method and the Local Polynomial Method for Nonparametric System Identification. in Proceedings of the 16th IFAC Symposium on System Identification, Brussels, Belgium, July 11-13, 2012. IFAC Proceedings Volumes, no. 16, vol. 45, Elsevier, pp. 55-60, 16th IFAC Symposium on System Identification (Sysid 2012), Brussels, Belgium, 11/07/12. https://doi.org/10.3182/20120711-3-BE-2027.00359

The Transient Impulse Response Modeling Method and the Local Polynomial Method for Nonparametric System Identification. / Gevers, Michel; Hägg, Per; Hjalmarsson, Håkan et al.
Proceedings of the 16th IFAC Symposium on System Identification, Brussels, Belgium, July 11-13, 2012. Elsevier, 2012. p. 55-60 (IFAC Proceedings Volumes; Vol. 45, No. 16).

Research output: Chapter in Book/Report/Conference proceeding › Conference paper

TY - GEN

T1 - The Transient Impulse Response Modeling Method and the Local Polynomial Method for Nonparametric System Identification

AU - Gevers, Michel

AU - Hägg, Per

AU - Hjalmarsson, Håkan

AU - Pintelon, Rik

AU - Schoukens, Joannes

PY - 2012/7/11

Y1 - 2012/7/11

N2 - This paper analyzes two recent methods for the nonparametric estimation of the Frequency Response Function (FRF) from input-output data using Prediction Error identification. Such FRF estimate can be the main goal of the identification exercise, or it can be a tool for the computation of a nonparametric estimate of the noise spectrum. We show that the choice of the method depends on the signal to noise ratio and on the objective. The method that delivers the best FRF estimate may not deliver the best estimate of the noise spectrum. Our theoretical analysis is illustrated by simulations.

AB - This paper analyzes two recent methods for the nonparametric estimation of the Frequency Response Function (FRF) from input-output data using Prediction Error identification. Such FRF estimate can be the main goal of the identification exercise, or it can be a tool for the computation of a nonparametric estimate of the noise spectrum. We show that the choice of the method depends on the signal to noise ratio and on the objective. The method that delivers the best FRF estimate may not deliver the best estimate of the noise spectrum. Our theoretical analysis is illustrated by simulations.

KW - System identification

KW - onparametric identification

KW - noise spectrum estimation

U2 - 10.3182/20120711-3-BE-2027.00359

DO - 10.3182/20120711-3-BE-2027.00359

M3 - Conference paper

SN - 978-3-902823-06-9

T3 - IFAC Proceedings Volumes

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BT - Proceedings of the 16th IFAC Symposium on System Identification, Brussels, Belgium, July 11-13, 2012

PB - Elsevier

T2 - 16th IFAC Symposium on System Identification (Sysid 2012)

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ER -

Gevers M, Hägg P, Hjalmarsson H, Pintelon R, Schoukens J. The Transient Impulse Response Modeling Method and the Local Polynomial Method for Nonparametric System Identification. In Proceedings of the 16th IFAC Symposium on System Identification, Brussels, Belgium, July 11-13, 2012. Elsevier. 2012. p. 55-60. (IFAC Proceedings Volumes; 16). doi: 10.3182/20120711-3-BE-2027.00359

The Transient Impulse Response Modeling Method and the Local Polynomial Method for Nonparametric System Identification

Abstract

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Keywords

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Projects

DWTC282: Dynamical systems, control and optimization

Cite this