Existing consensus control algorithms for networked discrete-time linear systems have slow convergence to consensus trajectories due to limitations on the magnitude of the consensus gain. In this work we propose and analyze a new predictor-based consensus control protocol that recovers the positive features of the continuous-time counterpart in terms of arbitrary rate of convergence to the consensus dynamics. Moreover, it admits a distributed implementation based on multiple consensus steps. Our analysis concerns general weakly connected digraphs and it encompasses both single and multiple consensus.

Consensus and multi-consensus for discrete-time LTI systems / Cacace, F.; Mattioni, M.; Monaco, S.; Normand-Cyrot, D.. - In: AUTOMATICA. - ISSN 0005-1098. - 166:(2024). [10.1016/j.automatica.2024.111718]

Consensus and multi-consensus for discrete-time LTI systems

Mattioni M.
;
Monaco S.;
2024

Abstract

Existing consensus control algorithms for networked discrete-time linear systems have slow convergence to consensus trajectories due to limitations on the magnitude of the consensus gain. In this work we propose and analyze a new predictor-based consensus control protocol that recovers the positive features of the continuous-time counterpart in terms of arbitrary rate of convergence to the consensus dynamics. Moreover, it admits a distributed implementation based on multiple consensus steps. Our analysis concerns general weakly connected digraphs and it encompasses both single and multiple consensus.
2024
Decentralization; Digital implementation; Multi-agent systems; Multi-consensus
01 Pubblicazione su rivista::01a Articolo in rivista
Consensus and multi-consensus for discrete-time LTI systems / Cacace, F.; Mattioni, M.; Monaco, S.; Normand-Cyrot, D.. - In: AUTOMATICA. - ISSN 0005-1098. - 166:(2024). [10.1016/j.automatica.2024.111718]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1710259
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