Robust Macroscopic Density Control of Heterogeneous Multi-Agent Systems

Fuente: arXiv
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Autores principales: Maffettone, Gian Carlo, Salzano, Davide, di Bernardo, Mario
Formato: Preprint
Publicado: 2026
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author Maffettone, Gian Carlo
Salzano, Davide
di Bernardo, Mario
author_facet Maffettone, Gian Carlo
Salzano, Davide
di Bernardo, Mario
contents Modern applications, such as orchestrating the collective behavior of robotic swarms or traffic flows, require the coordination of large groups of agents evolving in unstructured environments, where disturbances and unmodeled dynamics are unavoidable. In this work, we develop a scalable macroscopic density control framework in which a feedback law is designed directly at the level of an advection--diffusion partial differential equation. We formulate the control problem in the density space and prove global exponential convergence towards the desired behavior in $\mathcal{L}^2$ with guaranteed asymptotic rejection of bounded unknown drift terms, explicitly accounting for heterogeneous agent dynamics, unmodeled behaviors, and environmental perturbations. Our theoretical findings are corroborated by numerical experiments spanning heterogeneous oscillators, traffic systems, and swarm robotics in partially unknown environments.
format Preprint
id arxiv_https___arxiv_org_abs_2602_09695
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Robust Macroscopic Density Control of Heterogeneous Multi-Agent Systems
Maffettone, Gian Carlo
Salzano, Davide
di Bernardo, Mario
Systems and Control
Modern applications, such as orchestrating the collective behavior of robotic swarms or traffic flows, require the coordination of large groups of agents evolving in unstructured environments, where disturbances and unmodeled dynamics are unavoidable. In this work, we develop a scalable macroscopic density control framework in which a feedback law is designed directly at the level of an advection--diffusion partial differential equation. We formulate the control problem in the density space and prove global exponential convergence towards the desired behavior in $\mathcal{L}^2$ with guaranteed asymptotic rejection of bounded unknown drift terms, explicitly accounting for heterogeneous agent dynamics, unmodeled behaviors, and environmental perturbations. Our theoretical findings are corroborated by numerical experiments spanning heterogeneous oscillators, traffic systems, and swarm robotics in partially unknown environments.
title Robust Macroscopic Density Control of Heterogeneous Multi-Agent Systems
topic Systems and Control
url https://arxiv.org/abs/2602.09695