This paper investigates the collective behaviors induced by the network interconnection of heterogeneous input-affine single-input nonlinear systems through a constant but general directed graph. In this sense, we prove that the dynamics of all agents cluster into as many subgroups as the number of cells of the almost equitable partition induced by the communication graph. All agents belonging to the same cell are equally influenced by a new mean-field dynamics which is paradigmatic of the network. The case of a network of pendula illustrates the results through simulations.

Cluster partitioning of heterogeneous multi-agent systems / Mattioni, M.; Monaco, S.. - In: AUTOMATICA. - ISSN 0005-1098. - 138:(2022). [10.1016/j.automatica.2021.110136]

Cluster partitioning of heterogeneous multi-agent systems

Mattioni M.
;
Monaco S.
2022

Abstract

This paper investigates the collective behaviors induced by the network interconnection of heterogeneous input-affine single-input nonlinear systems through a constant but general directed graph. In this sense, we prove that the dynamics of all agents cluster into as many subgroups as the number of cells of the almost equitable partition induced by the communication graph. All agents belonging to the same cell are equally influenced by a new mean-field dynamics which is paradigmatic of the network. The case of a network of pendula illustrates the results through simulations.
2022
Linear/nonlinear models; Multi-agent systems; Multiconsensus
01 Pubblicazione su rivista::01a Articolo in rivista
Cluster partitioning of heterogeneous multi-agent systems / Mattioni, M.; Monaco, S.. - In: AUTOMATICA. - ISSN 0005-1098. - 138:(2022). [10.1016/j.automatica.2021.110136]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1605131
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