Maffettone, Gian Carlo (2024) Controlling the Collective Dynamics of Large-Scale Multi-Agent Systems. [Tesi di dottorato]
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| Tipologia del documento: | Tesi di dottorato |
|---|---|
| Lingua: | English |
| Titolo: | Controlling the Collective Dynamics of Large-Scale Multi-Agent Systems |
| Autori: | Autore Email Maffettone, Gian Carlo giancarlo.maffettone@unina.it |
| Data: | 12 Dicembre 2024 |
| Numero di pagine: | 189 |
| Istituzione: | Università degli Studi di Napoli Federico II |
| Dottorato: | Modeling and engineering risk and complexity |
| Ciclo di dottorato: | 36 |
| Coordinatore del Corso di dottorato: | nome email Di Bernardo, Mario mario.dibernardo@unina.it |
| Tutor: | nome email Di Bernardo, Mario [non definito] Porfiri, Maurizio [non definito] |
| Data: | 12 Dicembre 2024 |
| Numero di pagine: | 189 |
| Parole chiave: | Control Theory, Large-scale Systems, Collective Behaviour |
| Settori scientifico-disciplinari del MIUR: | Area 09 - Ingegneria industriale e dell'informazione > ING-INF/04 - Automatica |
| Depositato il: | 27 Nov 2025 10:57 |
| Ultima modifica: | 12 Ago 2026 05:38 |
| URI: | https://www.fedoa.unina.it/id/eprint/16916 |
Abstract
The understanding, modeling and control of large-scale multi-agent systems is crucial in uncountable open problems spanning from mathematics to physics and engineering. A deeper comprehension of these fascinating dynamical entities can enable the development of important steps towards new, more convenient solutions for many real world applications, from etho/swarm robotics to synthetic biology, and traffic/crowds control. In this Theses, we focus on how the multi-scale nature of large aggregates of interacting dynamical units plays an essential role when dealing with cutting-edges control problems. In particular, we face the problem of how to analytically ensure the fulfillment of macroscopic objectives regarding the emerging properties of a complex system, by only using microscopic actuation. Within the general context of density control, we both consider homogeneous and heterogeneous groups. In the former case, we apply control actions to all the individuals in the collective, in the latter, control is constrained to be exertable via a subset of special leader agents. Robustness of the proposed solution is assessed theoretically, numerically and experimentally. In particular, the experimental validation is performed through a mixed reality platform we developed for the agile testing of swarm robotics solutions.
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