Unfalsified approach to data-driven control design

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

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

4 Citations (Scopus)


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.
Original languageEnglish
Title of host publicationProceedings of the 53rd IEEE Conference on Decision and Control
PublisherIEEE (The Institute of Electrical and Electronics Engineers)
Pages6003 - 6008
Number of pages6
ISBN (Print)978-1-4799-7746-8
Publication statusPublished - Dec-2014
Event53rd IEEE Conference on Decision and Control - Los Angeles, United States
Duration: 15-Dec-201417-Dec-2014


Conference53rd IEEE Conference on Decision and Control
Country/TerritoryUnited States
CityLos Angeles

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