@inproceedings{969439bda9304b4c8fc42f5abee40a13,
title = "Resistance Distance Centrality Based Informed-Agent Selection for Leader-Follower Consensus with Convergence Rate Maximization",
abstract = "For leader-follower multi-agent systems (MAS), the selection of informed-agents is crucial to the convergence rate of the MAS. In this paper, the resistance distance centrality (RDC) of agents is applied to determine a set of informed-agents with specific scale, so that the convergence rate of the MAS is maximum. For a MAS with only one leader, we find that the follower agent with minimum value of RDC is the best informed-agent. For a connected undirected network with N followers, an iterative algorithm with running time mN3 is designed for determining m informed-agents. Simulations are carried out to manifest the validity of the approach.",
keywords = "Convergence rate, Informed-agent, Leader-follower multi-agent system, Resistance distance centrality",
author = "Shanshan Gao and Xinzhuang Chen and Shenggui Zhang",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; International Conference on Autonomous Unmanned Systems, ICAUS 2021 ; Conference date: 24-09-2021 Through 26-09-2021",
year = "2022",
doi = "10.1007/978-981-16-9492-9_309",
language = "英语",
isbn = "9789811694912",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "3152--3160",
editor = "Meiping Wu and Yifeng Niu and Mancang Gu and Jin Cheng",
booktitle = "Proceedings of 2021 International Conference on Autonomous Unmanned Systems, ICAUS 2021",
}