Distributed control gains design for consensus in multi-agent systems with second-order nonlinear dynamics

被引：387

作者：

Yu, Wenwu ^{[1
,2
]}

Ren, Wei ^{[3
]}

Zheng, Wei Xing ^{[4
]}

Chen, Guanrong ^{[5
]}

Lu, Jinhu ^{[6
]}

机构：

[1] Southeast Univ, Dept Math, Nanjing 210096, Jiangsu, Peoples R China

[2] RMIT Univ, Sch Elect & Comp Engn, Melbourne, Vic 3001, Australia

[3] Univ Calif Riverside, Dept Elect Engn, Riverside, CA 92521 USA

[4] Univ Western Sydney, Sch Comp Engn & Math, Penrith, NSW 2751, Australia

[5] City Univ Hong Kong, Dept Elect Engn, Hong Kong, Hong Kong, Peoples R China

[6] Chinese Acad Sci, Acad Math & Syst Sci, Inst Syst Sci, LSC, Beijing 100190, Peoples R China

来源：

AUTOMATICA | 2013年 / 49卷 / 07期

基金：

高等学校博士学科点专项科研基金; 美国国家科学基金会; 澳大利亚研究理事会; 中国国家自然科学基金;

关键词：

Multi-agent system; Second-order consensus; Synchronization; Complex network; Distributed adaptive law; Algebraic graph theory; Leader-follower consensus; COMPLEX NETWORKS; SYNCHRONIZATION; AGENTS;

D O I：

10.1016/j.automatica.2013.03.005

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper discusses the design of distributed control gains for consensus in multi-agent systems with second-order nonlinear dynamics. First, an effective distributed adaptive gain-design strategy is proposed based only on local information of the network structure. Then, a leader-follower consensus problem in multi-agent systems with updated control gains is studied. A distributed adaptive law is then proposed for each follower based on local information of neighboring agents and the leader if this follower is an informed agent. Furthermore, a distributed leader-follower consensus problem in multi-agent systems with unknown nonlinear dynamics is investigated by combining the variable structure approach and the adaptive method. Finally, simulation examples are given to illustrate the theoretical analysis. (C) 2013 Elsevier Ltd. All rights reserved.

引用

页码：2107 / 2115

页数：9

共 34 条

[1] Boyd S., 1994, LINEAR MATRIX INEQUA
[2] Reaching a consensus in a dynamically changing environment: A graphical approach
Cao, Ming
Morse, A. Stephen
Anderson, Brian D. O.
[J]. SIAM JOURNAL ON CONTROL AND OPTIMIZATION, 2008, 47 (02) : 575 - 600
[3] Distributed Coordinated Tracking With Reduced Interaction via a Variable Structure Approach
Cao, Yongcan
Ren, Wei
[J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2012, 57 (01) : 33 - 48
[4] Distributed Adaptive Tracking Control for Synchronization of Unknown Networked Lagrangian Systems
Chen, Gang
Lewis, Frank L.
[J]. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2011, 41 (03): : 805 - 816
[5] Pinning complex networks by a single controller
Chen, Tianping
Liu, Xiwei
Lu, Wenlian
[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2007, 54 (06) : 1317 - 1326
[6] CHUA LO, 1992, AEU-INT J ELECTRON C, V46, P250
[7] Novel decentralized adaptive strategies for the synchronization of complex networks
DeLellis, Pietro
diBernardo, Mario
Garofalo, Francesco
[J]. AUTOMATICA, 2009, 45 (05) : 1312 - 1318
[8] Synchronization in Networks of Linear Agents with Output Feedbacks
Dzhunusov, I. A.
Fradkov, A. L.
[J]. AUTOMATION AND REMOTE CONTROL, 2011, 72 (08) : 1615 - 1626
[9] FIEDLER M, 1973, CZECH MATH J, V23, P298
[10] Godsil C., 2001, Algebraic graph theory

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