A Stochastic Approach to the Synchronization of Coupled Oscillators

This paper deals with an optimal control problem associated with the Kuramoto model describing the dynamical behavior of a network of coupled oscillators. Our aim is to design a suitable control function allowing us to steer the system to a synchronized configuration in which all the oscillators are...

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Main Authors: Umberto Biccari, Enrique Zuazua
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-06-01
Series:Frontiers in Energy Research
Subjects:
Online Access:https://www.frontiersin.org/article/10.3389/fenrg.2020.00115/full
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spelling doaj-f619030c1d6e4cff9f8d933b121e6fe42020-11-25T02:53:53ZengFrontiers Media S.A.Frontiers in Energy Research2296-598X2020-06-01810.3389/fenrg.2020.00115534163A Stochastic Approach to the Synchronization of Coupled OscillatorsUmberto Biccari0Umberto Biccari1Enrique Zuazua2Enrique Zuazua3Enrique Zuazua4Chair of Computational Mathematics, Fundación Deusto, Avda. de las Universidades 24, Bilbao, SpainUniversidad de Deusto, Avenida de las Universidades 24, Bilbao, SpainChair of Computational Mathematics, Fundación Deusto, Avda. de las Universidades 24, Bilbao, SpainChair in Applied Analysis, Alexander von Humboldt-Professorship, Department of Mathematics Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, GermanyDepartamento de Matemáticas, Universidad Autónoma de Madrid, Madrid, SpainThis paper deals with an optimal control problem associated with the Kuramoto model describing the dynamical behavior of a network of coupled oscillators. Our aim is to design a suitable control function allowing us to steer the system to a synchronized configuration in which all the oscillators are aligned on the same phase. This control is computed via the minimization of a given cost functional associated with the dynamics considered. For this minimization, we propose a novel approach based on the combination of a standard Gradient Descent (GD) methodology with the recently-developed Random Batch Method (RBM) for the efficient numerical approximation of collective dynamics. Our simulations show that the employment of RBM improves the performances of the GD algorithm, reducing the computational complexity of the minimization process and allowing for a more efficient control calculation.https://www.frontiersin.org/article/10.3389/fenrg.2020.00115/fullcoupled oscillatorsKuramoto modeloptimal controlsynchronizationgradient descentrandom batch method
collection DOAJ
language English
format Article
sources DOAJ
author Umberto Biccari
Umberto Biccari
Enrique Zuazua
Enrique Zuazua
Enrique Zuazua
spellingShingle Umberto Biccari
Umberto Biccari
Enrique Zuazua
Enrique Zuazua
Enrique Zuazua
A Stochastic Approach to the Synchronization of Coupled Oscillators
Frontiers in Energy Research
coupled oscillators
Kuramoto model
optimal control
synchronization
gradient descent
random batch method
author_facet Umberto Biccari
Umberto Biccari
Enrique Zuazua
Enrique Zuazua
Enrique Zuazua
author_sort Umberto Biccari
title A Stochastic Approach to the Synchronization of Coupled Oscillators
title_short A Stochastic Approach to the Synchronization of Coupled Oscillators
title_full A Stochastic Approach to the Synchronization of Coupled Oscillators
title_fullStr A Stochastic Approach to the Synchronization of Coupled Oscillators
title_full_unstemmed A Stochastic Approach to the Synchronization of Coupled Oscillators
title_sort stochastic approach to the synchronization of coupled oscillators
publisher Frontiers Media S.A.
series Frontiers in Energy Research
issn 2296-598X
publishDate 2020-06-01
description This paper deals with an optimal control problem associated with the Kuramoto model describing the dynamical behavior of a network of coupled oscillators. Our aim is to design a suitable control function allowing us to steer the system to a synchronized configuration in which all the oscillators are aligned on the same phase. This control is computed via the minimization of a given cost functional associated with the dynamics considered. For this minimization, we propose a novel approach based on the combination of a standard Gradient Descent (GD) methodology with the recently-developed Random Batch Method (RBM) for the efficient numerical approximation of collective dynamics. Our simulations show that the employment of RBM improves the performances of the GD algorithm, reducing the computational complexity of the minimization process and allowing for a more efficient control calculation.
topic coupled oscillators
Kuramoto model
optimal control
synchronization
gradient descent
random batch method
url https://www.frontiersin.org/article/10.3389/fenrg.2020.00115/full
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