Abstract

We propose a computational framework for optimal control design of oscillator networks. We first introduce a new system representation to eliminate challenges arising from the periodic nature of oscillators. The representation allows us to consider the general problem of pattern formation for oscillators as a classical point-to-point steering. We then develop a novel control design technique that offers the flexibility to blend the time-optimal and energy-optimal considerations with a parameter of choice. We demonstrate the applicability of the proposed framework to a variety of neuroscience applications.

Original languageEnglish
Title of host publication2023 American Control Conference, ACC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3466-3471
Number of pages6
ISBN (Electronic)9798350328066
DOIs
StatePublished - 2023
Event2023 American Control Conference, ACC 2023 - San Diego, United States
Duration: May 31 2023Jun 2 2023

Publication series

NameProceedings of the American Control Conference
Volume2023-May
ISSN (Print)0743-1619

Conference

Conference2023 American Control Conference, ACC 2023
Country/TerritoryUnited States
CitySan Diego
Period05/31/2306/2/23

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