Controlling Complex Systems
Fuente:
arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866909666428059648 |
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| author | Coraggio, Marco Salzano, Davide di Bernardo, Mario |
| author_facet | Coraggio, Marco Salzano, Davide di Bernardo, Mario |
| contents | This chapter provides a comprehensive overview of controlling collective behavior in complex systems comprising large ensembles of interacting dynamical agents. Building upon traditional control theory's foundation in individual systems, we introduce tools designed to address the unique challenges of coordinating networks that exhibit emergent phenomena, including consensus, synchronization, and pattern formation. We analyze how local agent interactions generate macroscopic behaviors and investigate the fundamental role of network topology in determining system dynamics. Inspired by natural systems, we emphasize control strategies that achieve global coordination through localized interventions while considering practical implementation challenges. The chapter concludes by presenting novel frameworks for managing very large agent ensembles and leveraging interacting networks for control purposes. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_07579 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Controlling Complex Systems Coraggio, Marco Salzano, Davide di Bernardo, Mario Systems and Control Optimization and Control This chapter provides a comprehensive overview of controlling collective behavior in complex systems comprising large ensembles of interacting dynamical agents. Building upon traditional control theory's foundation in individual systems, we introduce tools designed to address the unique challenges of coordinating networks that exhibit emergent phenomena, including consensus, synchronization, and pattern formation. We analyze how local agent interactions generate macroscopic behaviors and investigate the fundamental role of network topology in determining system dynamics. Inspired by natural systems, we emphasize control strategies that achieve global coordination through localized interventions while considering practical implementation challenges. The chapter concludes by presenting novel frameworks for managing very large agent ensembles and leveraging interacting networks for control purposes. |
| title | Controlling Complex Systems |
| topic | Systems and Control Optimization and Control |
| url | https://arxiv.org/abs/2504.07579 |