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Abstract

In this paper, we present a novel approach to com-bine data-driven non-parametric representations with model-based representations of dynamical systems. Based on a data-driven form of linear fractional transformations, we introduce a data-driven form of generalized plants. This form can be leveraged to accomplish performance characterizations, e.g., in the form of a mixed-sensitivity approach, and LMI-based conditions to verify finite-horizon dissipativity. In particular, we show how finite-horizon l2 -gain under weighting filter-based general performance specifications can be verified for implemented controllers on systems for which only input-output data is available. The overall effectiveness of the proposed method is demonstrated by simulation examples.

Original languageEnglish
Title of host publication2024 European Control Conference, ECC 2024
PublisherInstitute of Electrical and Electronics Engineers
Pages894-899
Number of pages6
ISBN (Electronic)978-3-9071-4410-7
DOIs
Publication statusPublished - 24 Jul 2024
Event22nd European Control Conference 2024, ECC 2024 - KTH Royal Institute of Technology, Stockholm, Sweden
Duration: 25 Jun 202428 Jun 2024
Conference number: 22
https://ecc24.euca-ecc.org/

Conference

Conference22nd European Control Conference 2024, ECC 2024
Abbreviated titleECC 2024
Country/TerritorySweden
CityStockholm
Period25/06/2428/06/24
Internet address

Keywords

  • Data-Driven Control
  • Dissipativity Analysis

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