Identification of additive multivariable continuous-time systems

Maarten van der Hulst; Rodrigo González; Koen Classens; Nic Dirkx; Jeroen van de Wijdeven; Tom Oomen

doi:10.48550/arXiv.2504.01639

Identification of additive multivariable continuous-time systems

Maarten van der Hulst, Rodrigo González, Koen Classens, Nic Dirkx, Jeroen van de Wijdeven, Tom Oomen

Research output: Working paper › Preprint › Academic

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Abstract

Multivariable parametric models are critical for designing, controlling, and optimizing the performance of engineered systems. The main objective of this paper is to develop a parametric identification strategy that delivers accurate and physically relevant models of multivariable systems using time-domain data. The introduced approach adopts an additive model structure, offering a parsimonious and interpretable representation of many physical systems, and employs a refined instrumental variable-based estimation algorithm. The developed identification method enables the estimation of parametric continuous-time additive models and is applicable to both open and closed-loop controlled systems. The performance of the estimator is demonstrated through numerical simulations and experimentally validated on a flexible beam system.

Original language	English
Publisher	arXiv.org
Number of pages	6
Volume	2504.01639
DOIs	https://doi.org/10.48550/arXiv.2504.01639
Publication status	Published - 2 Apr 2025

Keywords

eess.SP

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10.48550/arXiv.2504.01639

2504.01639v1Final published version, 1.41 MBLicence: CC BY-NC-ND

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AU - González, Rodrigo

AU - Classens, Koen

AU - Dirkx, Nic

AU - van de Wijdeven, Jeroen

AU - Oomen, Tom

N1 - 6 pages, 8 figures

PY - 2025/4/2

Y1 - 2025/4/2

N2 - Multivariable parametric models are critical for designing, controlling, and optimizing the performance of engineered systems. The main objective of this paper is to develop a parametric identification strategy that delivers accurate and physically relevant models of multivariable systems using time-domain data. The introduced approach adopts an additive model structure, offering a parsimonious and interpretable representation of many physical systems, and employs a refined instrumental variable-based estimation algorithm. The developed identification method enables the estimation of parametric continuous-time additive models and is applicable to both open and closed-loop controlled systems. The performance of the estimator is demonstrated through numerical simulations and experimentally validated on a flexible beam system.

AB - Multivariable parametric models are critical for designing, controlling, and optimizing the performance of engineered systems. The main objective of this paper is to develop a parametric identification strategy that delivers accurate and physically relevant models of multivariable systems using time-domain data. The introduced approach adopts an additive model structure, offering a parsimonious and interpretable representation of many physical systems, and employs a refined instrumental variable-based estimation algorithm. The developed identification method enables the estimation of parametric continuous-time additive models and is applicable to both open and closed-loop controlled systems. The performance of the estimator is demonstrated through numerical simulations and experimentally validated on a flexible beam system.

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BT - Identification of additive multivariable continuous-time systems

PB - arXiv.org

ER -

Identification of additive multivariable continuous-time systems

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