Non-parametric system norm estimation of multivariable systems

  • Paul Tacx (Corresponding author-nrf)
  • , Tom Oomen

Research output: Contribution to journalArticleAcademicpeer-review

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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 H2 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.

Original languageEnglish
Article number106421
Number of pages11
JournalControl Engineering Practice
Volume164
DOIs
Publication statusPublished - Nov 2025

Bibliographical note

Publisher Copyright:
© 2025

Keywords

  • Control applications
  • Identification for control
  • Local parametric modeling
  • Motion control
  • Multivariable control systems
  • Robust control

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