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Hauptverfasser: Qin, Yuzhen, Pasqualetti, Fabio, Bassett, Danielle S., van Gerven, Marcel
Format: Preprint
Veröffentlicht: 2024
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Online-Zugang:https://arxiv.org/abs/2408.08263
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author Qin, Yuzhen
Pasqualetti, Fabio
Bassett, Danielle S.
van Gerven, Marcel
author_facet Qin, Yuzhen
Pasqualetti, Fabio
Bassett, Danielle S.
van Gerven, Marcel
contents The stability of complex networks, from power grids to biological systems, is crucial for their proper functioning. It is thus important to control such systems to maintain or restore their stability. Traditional approaches rely on real-time state measurements for feedback control, but this can be challenging in many real-world systems, such as the brain, due to their complex and dynamic nature. This paper utilizes vibrational control -- an open-loop strategy -- to regulate network stability. Unlike conventional methods targeting network nodes, our approach focuses on manipulating network edges through vibrational inputs. We establish sufficient graph-theoretic conditions for vibration-induced functional modifications of network edges and stabilization of network systems as a whole. Additionally, we provide methods for designing effective vibrational control inputs and validate our theoretical findings through numerical simulations.
format Preprint
id arxiv_https___arxiv_org_abs_2408_08263
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Vibrational Control of Complex Networks
Qin, Yuzhen
Pasqualetti, Fabio
Bassett, Danielle S.
van Gerven, Marcel
Optimization and Control
The stability of complex networks, from power grids to biological systems, is crucial for their proper functioning. It is thus important to control such systems to maintain or restore their stability. Traditional approaches rely on real-time state measurements for feedback control, but this can be challenging in many real-world systems, such as the brain, due to their complex and dynamic nature. This paper utilizes vibrational control -- an open-loop strategy -- to regulate network stability. Unlike conventional methods targeting network nodes, our approach focuses on manipulating network edges through vibrational inputs. We establish sufficient graph-theoretic conditions for vibration-induced functional modifications of network edges and stabilization of network systems as a whole. Additionally, we provide methods for designing effective vibrational control inputs and validate our theoretical findings through numerical simulations.
title Vibrational Control of Complex Networks
topic Optimization and Control
url https://arxiv.org/abs/2408.08263