Abstract

The problem of controlling ensembles of similar dynamical systems appears in many scientific domains, ranging from quantum physics and neuroscience to robotic engineering. These applications have led to the development of a variety of ensemble control methods. These methods, although effective, rely on a critical assumption, namely, the availability of an accurate parametric model for the entire population. In this paper, we relax such assumptions and present a data-driven framework for designing both open-loop and feedback control schemes for ensemble systems, which only uses the measurement of a small number of subsystems within the population. We validate our approach through numerical analysis and simulation, showing its effectiveness in regulating large populations with just a few of their subsystems measured.

Original languageEnglish
Title of host publication2024 American Control Conference, ACC 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5004-5009
Number of pages6
ISBN (Electronic)9798350382655
DOIs
StatePublished - 2024
Event2024 American Control Conference, ACC 2024 - Toronto, Canada
Duration: Jul 10 2024Jul 12 2024

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

Conference

Conference2024 American Control Conference, ACC 2024
Country/TerritoryCanada
CityToronto
Period07/10/2407/12/24

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