Control of synchronization phenomena in Complex Networks: The Kuramoto Model

The notion of Control in Complex Systems has started almost 60 years ago by Kalman. However, the results obtained were not sufficient for systems with complex topologies (Complex Networks) and non-linear dynamics. Thanks to many works and especially the one of Liu et.al. on 2011, the topic of Contro...

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Detalhes bibliográficos
Autor: Lagos, Dimitrios
Formato: tesis de maestría
Fecha de publicación:2022
País:España
Recursos:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/368652
Acesso em linha:https://hdl.handle.net/2117/368652
Access Level:acceso abierto
Palavra-chave:System theory
Synchronization
Kuramoto model
Control of synchronization
Explosive synchronization
Lyapunov
Sistemes de control
Classificació AMS::93 Systems Theory
Control::93A General
Àrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa::Optimització
Descrição
Resumo:The notion of Control in Complex Systems has started almost 60 years ago by Kalman. However, the results obtained were not sufficient for systems with complex topologies (Complex Networks) and non-linear dynamics. Thanks to many works and especially the one of Liu et.al. on 2011, the topic of Control in Complex networks has returned to the forefront and has been studied intensively during the last decade. Big progress has been made, but still there are many different aspects unsolved in the area. Different notions like structural controllability or required energy to control a network have been imported, but a unifying framework between Complex Systems and Control Theory is still missing, as non-linearity, complexity and dimensionality make it difficult and very often infeasible to extract general and unifying conclusions about this kind of systems. In this work we explore the dynamical properties of the Kuramoto model, focusing the theoretical analysis on the Star-Graph topology taking into consideration the original Kuramoto model, as well as a perturbed expansion of it. Then, a candidate control Lyapunov function is proposed and together with the rest of the theoretical results, is validated by performing various numerical simulations and deploying Model Predictive Control for the controlled cases.