In this paper, we propose a data-driven control strategy to solve the distributed modal consensus and synchronization problems. The proposed solution relies only on input/output data and does not require any knowledge of the dynamics of each agent. Furthermore, it is shown that the synchronization task requires to address the problem of transferring, in finite time, the state of a system from an initial state to a terminal one in a completely data-driven framework, which is therefore tackled and solved here. The above concepts are then illustrated via a multi-agent system consisting of RC circuits.

Monti, A., Galeani, S., Possieri, C., Sassano, M. (2022). A data-driven approach to distributed modal consensus and synchronization. In Proceedings of the IEEE Conference on Decision and Control (pp.4853-4858). New York : IEEE [10.1109/CDC51059.2022.9992981].

A data-driven approach to distributed modal consensus and synchronization

Monti A.;Galeani S.;Possieri C.;Sassano M.
2022-01-01

Abstract

In this paper, we propose a data-driven control strategy to solve the distributed modal consensus and synchronization problems. The proposed solution relies only on input/output data and does not require any knowledge of the dynamics of each agent. Furthermore, it is shown that the synchronization task requires to address the problem of transferring, in finite time, the state of a system from an initial state to a terminal one in a completely data-driven framework, which is therefore tackled and solved here. The above concepts are then illustrated via a multi-agent system consisting of RC circuits.
61st IEEE Conference on Decision and Control (CDC 2022)
Cancun, Mexico
2022
61
IEEE
Rilevanza internazionale
2022
Settore ING-INF/04
Settore IINF-04/A - Automatica
English
Intervento a convegno
Monti, A., Galeani, S., Possieri, C., Sassano, M. (2022). A data-driven approach to distributed modal consensus and synchronization. In Proceedings of the IEEE Conference on Decision and Control (pp.4853-4858). New York : IEEE [10.1109/CDC51059.2022.9992981].
Monti, A; Galeani, S; Possieri, C; Sassano, M
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/337765
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