A tutorial on the informativity framework for data-driven control

Henk J. Van Waarde*, J. Eising, M. Kanat Camlibel, Harry L. Trentelman

*Bijbehorende auteur voor dit werk

OnderzoeksoutputAcademicpeer review

1 Citaat (Scopus)
46 Downloads (Pure)


The purpose of this paper is to provide a tutorial on the so-called informativity framework for direct data-driven control. This framework views data-driven analysis and design through the lens of robust control, and aims at assessing system properties and determining controllers for sets of systems unfalsified by the data. We will first introduce the informativity approach at an abstract level. Thereafter, we will study several case studies where we highlight the strength of the approach in the context of stabilizability analysis and stabilizing feedback design in different setups involving exact and noisy data, and for both input-state and input-output measurements. Finally, we provide an account of other applications of the data informativity framework.

Originele taal-2English
Titel2022 IEEE 61st Conference on Decision and Control, CDC 2022
Aantal pagina's6
ISBN van elektronische versie978-1-6654-6761-2
ISBN van geprinte versie978-1-6654-6762-9
StatusPublished - 2022
Evenement61st IEEE Conference on Decision and Control, CDC 2022 - Cancun, Mexico
Duur: 6-dec.-20229-dec.-2022

Publicatie series

NaamProceedings of the IEEE Conference on Decision and Control
ISSN van geprinte versie0743-1546
ISSN van elektronische versie2576-2370


Conference61st IEEE Conference on Decision and Control, CDC 2022

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