Non-parametric system norm estimation of multivariable systems

Data-driven estimation of system norms is essential for analyzing, verifying, and designing control systems. Existing data-based methods often do not capture the inter-grid and transient behavior of the system, leading to inaccurate and unreliable system norm estimations. This paper presents a unified approach for accurate and reliable estimation of the H 2 and H ∞ norm with a limited amount of data. The key step is to exploit local parametric models that explicitly incorporate the inter-grid and transient dynamics. The system norm is estimated through the computation of local system norms of the local parametric models within their the local frequency interval. Simulation and experimental results illustrate the effectiveness of the proposed method.

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Publication Details

Journal
Control Engineering Practice
Published
2025-06-19
DOI
https://doi.org/10.1016/j.conengprac.2025.106421
Primary Topic
Control Systems and Identification
Type
article
Field-Weighted Citation Impact
0.00

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article

Non-parametric system norm estimation of multivariable systems

Tom Oomen, Paul Tacx
Control Engineering Practice
Control Systems and Identification
article

Non-parametric system norm estimation of multivariable systems

Tom Oomen, Paul Tacx
article en

Abstract

Data-driven estimation of system norms is essential for analyzing, verifying, and designing control systems. Existing data-based methods often do not capture the inter-grid and transient behavior of the system, leading to inaccurate and unreliable system norm estimations. This paper presents a unified approach for accurate and reliable estimation of the H 2 and H ∞ norm with a limited amount of data. The key step is to exploit local parametric models that explicitly incorporate the inter-grid and transient dynamics. The system norm is estimated through the computation of local system norms of the local parametric models within their the local frequency interval. Simulation and experimental results illustrate the effectiveness of the proposed method.

Control Engineering PracticeVol. 164
Eindhoven University of Technology (NL), ASML (Netherlands) (NL), Delft University of Technology (NL)
Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Nederlandse Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek
Openalex Percentile: Top 84%
Control Systems and Identification
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