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Author:

Li, Xuejing (Li, Xuejing.) | Wang, Lin (Wang, Lin.) | Liu, Zhixin (Liu, Zhixin.) | Dong, Daoyi (Dong, Daoyi.)

Indexed by:

Scopus SCIE PubMed

Abstract:

This paper considers the consensus behavior of a spatially distributed 3-D dynamical network composed of heterogeneous agents: leaders and followers, in which the leaders have the preferred information about the destination, while the followers do not have. All followers move in a 3-D Euclidean space with a given speed and with their headings updated according to the average velocity of the corresponding neighbors. Compared with the 2-D model, a key point lies in how to analyze the dynamical behavior of a "linear" nonhomogeneous equation where the nonhomogeneous term strongly nonlinearly depends on the states of all agents. Using the network structure and the estimation of some characteristics for the initial states, we present a proper decaying rate for the nonhomogeneous term and then establish lower bounds on the ratio of the number of leaders to the number of followers that is needed for the expected consensus by considering two cases: 1) fixed speed and neighborhood radius and 2) variable speed and neighborhood radius with respect to the population size. Some simulation examples are given to justify the theoretical results.

Keyword:

lower bound leader-follower model expected consensus 3-D flocking model

Author Community:

  • [ 1 ] [Li, Xuejing]Beijing Univ Technol, Coll Appl Sci, Beijing 100124, Peoples R China
  • [ 2 ] [Wang, Lin]Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200240, Peoples R China
  • [ 3 ] [Wang, Lin]Minist Educ, Key Lab Syst Control & Informat Proc, Shanghai 200240, Peoples R China
  • [ 4 ] [Liu, Zhixin]Chinese Acad Sci, Acad Math & Syst Sci, Key Lab Syst & Control, Beijing 100190, Peoples R China
  • [ 5 ] [Dong, Daoyi]Univ New South Wales, Sch Engn & Informat Technol, Canberra, ACT 2600, Australia

Reprint Author's Address:

  • [Li, Xuejing]Beijing Univ Technol, Coll Appl Sci, Beijing 100124, Peoples R China

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Source :

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS

ISSN: 2162-237X

Year: 2017

Issue: 11

Volume: 28

Page: 2555-2565

1 0 . 4 0 0

JCR@2022

ESI Discipline: COMPUTER SCIENCE;

ESI HC Threshold:175

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count: 2

SCOPUS Cited Count: 4

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 11

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