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 language | English |
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Title of host publication | 2024 European Control Conference, ECC 2024 |
Publisher | Institute of Electrical and Electronics Engineers |
Pages | 894-899 |
Number of pages | 6 |
ISBN (Electronic) | 978-3-9071-4410-7 |
DOIs | |
Publication status | Published - 24 Jul 2024 |
Event | 22nd European Control Conference 2024, ECC 2024 - KTH Royal Institute of Technology, Stockholm, Sweden Duration: 25 Jun 2024 → 28 Jun 2024 Conference number: 22 https://ecc24.euca-ecc.org/ |
Conference
Conference | 22nd European Control Conference 2024, ECC 2024 |
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Abbreviated title | ECC 2024 |
Country/Territory | Sweden |
City | Stockholm |
Period | 25/06/24 → 28/06/24 |
Internet address |
Keywords
- Data-Driven Control
- Dissipativity Analysis