Practical consensus tracking of homogeneous sampled-data multi-agent systems

Florence Josse (1, 2) , Emmanuel Bernuau (3) , Emmanuel Moulay (4, 2) , Patrick Coirault (5, 6) , Qing Hui (7) , Josh Allen (7)

1 XLIM-SRI - Systèmes et Réseaux Intelligents
2 UP - Université de Poitiers = University of Poitiers
3 SayFood - Paris-Saclay Food and Bioproduct Engineering
4 XLIM - XLIM
5 LIAS [Poitiers] - Laboratoire d'informatique et d'automatique pour les systèmes
6 A&S - Automatique et Systèmes
7 University of Nebraska–Lincoln

The aim of this article is to study the robustness of homogeneous sampled-data multi-agent systems including a leader whose dynamic evolution is independent of its followers. We explore the effects caused simultaneously by the sampling and the acceleration of the leader on the system, and show that practical consensus is achieved in this case. The results are illustrated in simulations.

Domaines: Automatique; Système multi-agents [cs.MA]

Florence Josse, Emmanuel Bernuau, Emmanuel Moulay, Patrick Coirault, Qing Hui, et al.. Practical consensus tracking of homogeneous sampled-data multi-agent systems. 2022 American Control Conference (ACC), Jun 2022, Atlanta, United States. pp.1569-1574, ⟨10.23919/ACC53348.2022.9867581⟩. ⟨hal-03773195⟩