Data-Driven Dissipativity Analysis of Linear Parameter-Varying Systems

Chris Verhoek (Corresponding author), Julian Berberich, Sofie Haesaert, Frank Allgower, Roland Toth

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2 Citaten (Scopus)
3 Downloads (Pure)

Samenvatting

In this article, we derive direct data-driven dissipativity analysis methods for linear parameter-varying (LPV) systems using a single sequence of input-scheduling-output data. By means of constructing a semidefinite program subject to linear matrix inequality constraints based on this data-dictionary, direct data-driven verification of (Q,S,R)-type of dissipativity properties of the data-generating LPV system is achieved. Multiple implementation methods are proposed to achieve efficient computational properties and to even exploit structural information on the scheduling, e.g., rate bounds. The effectiveness and tradeoffs of the proposed methodologies are shown in simulation studies of academic and physically realistic examples.

Originele taal-2Engels
Artikelnummer10568305
Pagina's (van-tot)8603-8616
Aantal pagina's14
TijdschriftIEEE Transactions on Automatic Control
Volume69
Nummer van het tijdschrift12
Vroegere onlinedatum21 jun. 2024
DOI's
StatusGepubliceerd - dec. 2024

Financiering

This work was supported in part by the European Research Council (ERC) under Grant 714663, in part by the European Union within the framework of the National Laboratory for Autonomous Systems under Grant RRF-2.3.1-21-2022-00002, in part by Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy-EXC 2075-390740016 and under Grant 468094890. The work of Frank Allg\u00F6wer was supported by the Stuttgart Center for Simulation Science (SimTech). Recommended by Associate Editor Isabelle Queinnec.

FinanciersFinanciernummer
Universitat Stuttgart
European Research Council
Deutsche ForschungsgemeinschaftStrategy-EXC 2075-390740016, 468094890
European Union’s Horizon Europe research and innovation programme714663
UK Research and Innovation104831

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