Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/152109
Title: Distributed adaptive leader–follower and leaderless consensus control of a class of strict-feedback nonlinear systems : a unified approach
Authors: Huang, Jiangshuai
Wang, Wei
Wen, Changyun
Zhou, Jing
Li, Guoqi
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2020
Source: Huang, J., Wang, W., Wen, C., Zhou, J. & Li, G. (2020). Distributed adaptive leader–follower and leaderless consensus control of a class of strict-feedback nonlinear systems : a unified approach. Automatica, 118, 109021-. https://dx.doi.org/10.1016/j.automatica.2020.109021
Journal: Automatica
Abstract: In this paper, distributed adaptive consensus for a class of strict-feedback nonlinear systems under directed topology condition is investigated. Both leader–follower and leaderless cases are considered in a unified framework. To design distributed controller for each subsystem, a local compensatory variable is generated based on the signals collected from its neighbors. Such a technique enables us to solve the leader–follower consensus and leaderless consensus problems in a unified framework. And it further allows us to treat the leaderless consensus as a special case of the leader–follower consensus. For leader–follower consensus, the assumption that the leader trajectory is linearly parameterized with some known functions as required in most recent relevant literatures is successfully relaxed. It is shown that global uniform boundedness of all closed-loop signals and asymptotically output consensus could be achieved for both cases. Simulation results are provided to verify the effectiveness of our schemes.
URI: https://hdl.handle.net/10356/152109
ISSN: 0005-1098
DOI: 10.1016/j.automatica.2020.109021
Schools: School of Electrical and Electronic Engineering 
Rights: © 2020 Elsevier Ltd. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

SCOPUSTM   
Citations 5

142
Updated on May 5, 2025

Web of ScienceTM
Citations 5

86
Updated on Oct 28, 2023

Page view(s)

256
Updated on May 5, 2025

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.