Scafuti, Francesco (2016) Evolving and adaptive strategies for consensus and synchronization of multi-agent systems. [Tesi di dottorato]
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Item Type: | Tesi di dottorato |
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Resource language: | English |
Title: | Evolving and adaptive strategies for consensus and synchronization of multi-agent systems |
Creators: | Creators Email Scafuti, Francesco francesco.scafuti@unina.it |
Date: | 31 March 2016 |
Number of Pages: | 110 |
Institution: | Università degli Studi di Napoli Federico II |
Department: | Ingegneria Elettrica e delle Tecnologie dell'Informazione |
Scuola di dottorato: | Ingegneria dell'informazione |
Dottorato: | Ingegneria informatica ed automatica |
Ciclo di dottorato: | 28 |
Coordinatore del Corso di dottorato: | nome email Garofalo, Francesco franco.garofalo@unina.it |
Tutor: | nome email di Bernardo, Mario UNSPECIFIED |
Date: | 31 March 2016 |
Number of Pages: | 110 |
Keywords: | evolving networks; synchronization; consensus |
Settori scientifico-disciplinari del MIUR: | Area 09 - Ingegneria industriale e dell'informazione > ING-INF/04 - Automatica |
Date Deposited: | 03 May 2016 13:04 |
Last Modified: | 31 Oct 2016 11:16 |
URI: | http://www.fedoa.unina.it/id/eprint/10919 |
Collection description
We investigate evolving and adaptive strategies, in network of dynamical agents, for solving general types of consensus and synchronization. First, we analyse the problem of max/min consensus in directed networks of integrators. Extending edge snapping method with a three-well potential, we are able to show the effectiveness of our strategy to achieve general types of consensus, different from the average. Theoretical results are validated via a number of numerical examples. Then we move to synchronization of coupled non identical oscillators. We design an evolutionary strategy for network synchronization. Our results suggest that heterogeneity is the driving force determining the evolution of state-dependent functional networks. Minimal emergent networks show enhanced synchronization properties and high levels of degree-frequency assortativity. We analyse networks of N = 100 and N = 1000 Kuramoto oscillators showing that hubs in the network tend to emerge as nodes' heterogeneity is increased. Finally, we study synchronization of multi-agent systems from a contraction theory viewpoint. Contraction theory is a useful tool to study convergence of dynamical systems and networks, recently proposed in the literature. In detail, we recall three strategies: virtual systems method, convergence to a flow-invariant subspace and hierarchical approach. While the former is simple to apply, the latter is suited for larger networks.
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