Unfalsified approach to data-driven control design

Giorgio  Battistelli; Daniele  Mari; Daniela Selvi; Pietro Tesi

doi:10.1109/CDC.2014.7040329

Unfalsified approach to data-driven control design

Giorgio Battistelli, Daniele Mari, Daniela Selvi, Pietro Tesi^*

^*Bijbehorende auteur voor dit werk

Smart Manufacturing Systems

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4 Citaten (Scopus)

Samenvatting

The paper deals with the problem of designing controllers from experimental data. We propose a non-iterative direct approach in which the parameters of a controller of a prescribed order and structure are optimized with respect to a relevant performance criterion. The proposed approach builds upon the so-called unfalsified control theory. This is the key point which makes it possible to derive simple and intuitive relations between the choice of the performance criterion to optimize and closed-loop stability conditions, thus making it possible to derive a data-driven controller tuning procedure incorporating simple stability tests. An example is presented to substantiate the analysis.

Originele taal-2	English
Titel	Proceedings of the 53rd IEEE Conference on Decision and Control
Uitgeverij	IEEE (The Institute of Electrical and Electronics Engineers)
Pagina's	6003 - 6008
Aantal pagina's	6
ISBN van geprinte versie	978-1-4799-7746-8
DOI's	https://doi.org/10.1109/CDC.2014.7040329
Status	Published - dec.-2014
Evenement	53rd IEEE Conference on Decision and Control - Los Angeles, United States Duur: 15-dec.-2014 → 17-dec.-2014

Conference

Conference	53rd IEEE Conference on Decision and Control
Land/Regio	United States
Stad	Los Angeles
Periode	15/12/2014 → 17/12/2014

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10.1109/CDC.2014.7040329

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title = "Unfalsified approach to data-driven control design",

abstract = "The paper deals with the problem of designing controllers from experimental data. We propose a non-iterative direct approach in which the parameters of a controller of a prescribed order and structure are optimized with respect to a relevant performance criterion. The proposed approach builds upon the so-called unfalsified control theory. This is the key point which makes it possible to derive simple and intuitive relations between the choice of the performance criterion to optimize and closed-loop stability conditions, thus making it possible to derive a data-driven controller tuning procedure incorporating simple stability tests. An example is presented to substantiate the analysis.",

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Battistelli, G, Mari, D, Selvi, D & Tesi, P 2014, Unfalsified approach to data-driven control design. in Proceedings of the 53rd IEEE Conference on Decision and Control. IEEE (The Institute of Electrical and Electronics Engineers), blz. 6003 - 6008, 53rd IEEE Conference on Decision and Control, Los Angeles, United States, 15/12/2014. https://doi.org/10.1109/CDC.2014.7040329

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AU - Selvi, Daniela

AU - Tesi, Pietro

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N2 - The paper deals with the problem of designing controllers from experimental data. We propose a non-iterative direct approach in which the parameters of a controller of a prescribed order and structure are optimized with respect to a relevant performance criterion. The proposed approach builds upon the so-called unfalsified control theory. This is the key point which makes it possible to derive simple and intuitive relations between the choice of the performance criterion to optimize and closed-loop stability conditions, thus making it possible to derive a data-driven controller tuning procedure incorporating simple stability tests. An example is presented to substantiate the analysis.

AB - The paper deals with the problem of designing controllers from experimental data. We propose a non-iterative direct approach in which the parameters of a controller of a prescribed order and structure are optimized with respect to a relevant performance criterion. The proposed approach builds upon the so-called unfalsified control theory. This is the key point which makes it possible to derive simple and intuitive relations between the choice of the performance criterion to optimize and closed-loop stability conditions, thus making it possible to derive a data-driven controller tuning procedure incorporating simple stability tests. An example is presented to substantiate the analysis.

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DO - 10.1109/CDC.2014.7040329

M3 - Conference contribution

SN - 978-1-4799-7746-8

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BT - Proceedings of the 53rd IEEE Conference on Decision and Control

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