Distributed Finite-Time Supremum/Infimum Dynamic Consensus Under Directed Network Topology. Furchì, A., Lippi, M., Marino, A., & Gasparri, A. 2023.
Distributed Finite-Time Supremum/Infimum Dynamic Consensus Under Directed Network Topology [link]Paper  doi  abstract   bibtex   
In this paper, we address the distributed supremum/infimum dynamic consensus problem in networked multi-agent systems. More in detail, by considering that each agent has access to a local exogenous time-varying signal, the objective is to have all the agents distributively track the global maximum supremum (or minimum infimum) of these exogenous signals. We propose a distributed protocol guaranteeing finite-time convergence under directed network topology. The sole requirements are the strong connectivity of the communication graph and the boundedness of the derivatives of the exogenous signals, with known bounds. The effectiveness of the proposed protocol is corroborated through numerical simulations in a precision farming case study.
@conference{
	11580_109743,
	author = {Furchì, Antonio and Lippi, Martina and Marino, Alessandro and Gasparri, Andrea},
	title = {Distributed Finite-Time Supremum/Infimum Dynamic Consensus Under Directed Network Topology},
	year = {2023},
	booktitle = {IEEE Conference on Decision and Control (CDC)},
	abstract = {In this paper, we address the distributed supremum/infimum dynamic consensus problem in networked multi-agent systems. More in detail, by considering that each agent has access to a local exogenous time-varying signal, the objective is to have all the agents distributively track the global maximum supremum (or minimum infimum) of these exogenous signals. We propose a distributed protocol guaranteeing finite-time convergence under directed network topology. The sole requirements are the strong connectivity of the communication graph and the boundedness of the derivatives of the exogenous signals, with known bounds. The effectiveness of the proposed protocol is corroborated through numerical simulations in a precision farming case study.},
	keywords = {Distributed control; multi-agent systems.},
	url = {https://ieeexplore.ieee.org/document/10384085/authors#authors},
	doi = {10.1109/cdc49753.2023.10384085},
	isbn = {979-8-3503-0124-3},	
	pages = {4480--4485}
}

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