A consensus protocol considering Lipschitz constant and communication topology condition of high-order nonlinear multi-agent systems

被引:9
作者
Wen, Hao [1 ,2 ,4 ]
Zhou, Hexiong [2 ]
Fu, Jian [1 ,2 ]
Yao, Baoheng [1 ,2 ,3 ,4 ]
Lian, Lian [1 ,2 ]
机构
[1] Shanghai Jiao Tong Univ, Sch Oceanog, Shanghai 200030, Peoples R China
[2] Shanghai Jiao Tong Univ, State Key Lab Ocean Engn, Shanghai 200240, Peoples R China
[3] Second Inst Oceanog, Hangzhou 310012, Peoples R China
[4] Shanghai Jiao Tong Univ, Inst Polar & Ocean Technol, Inst Marine Equipment, Shanghai 200030, Peoples R China
来源
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION | 2022年 / 111卷
基金
国家重点研发计划;
关键词
Nonlinear consensus; High-order consensus; Lipschitz condition; Multi-agent systems; DISTRIBUTED CONSENSUS; TRACKING CONTROL; DYNAMICS; SEEKING; DESIGN;
D O I
10.1016/j.cnsns.2022.106499
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
A new protocol is proposed for the consensus of multi-agent systems with the properties of high-order and nonlinearity for every single system. It is assumed that the nonlinear function of the sub-agent is restricted by the Lipschitz condition, and in addition, there are two kinds of communication topology structures among the members. The protocol combines the eigenvalues of the Laplace matrix and the Lipschitz constant of the multiagent system. By reasonably designing the Lyapunov function, the convergence condition of the system is divided into two parts which are connected by an unknown quantity k Except for quantity k the connection of other parts of the protocol is loose, which makes the protocol more flexible. (C) 2022 Elsevier B.V. All rights reserved.
引用
收藏
页数:21
相关论文
共 36 条
  • [1] [Anonymous], 2006, MODERN CONTROL THEOR
  • [2] Bhatta P., 2004, NONLINEAR STABILITY
  • [3] Nonlinear multiple-input-multiple-output adaptive backstepping control of underwater glider systems
    Cao, Junjun
    Cao, Junliang
    Zeng, Zheng
    Lian, Lian
    [J]. INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS, 2016, 13 : 1 - 14
  • [4] Optimal Linear-Consensus Algorithms: An LQR Perspective
    Cao, Yongcan
    Ren, Wei
    [J]. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2010, 40 (03): : 819 - 830
  • [5] Distributed Consensus of Nonlinear Multi-Agent Systems on State-Controlled Switching Topologies
    Chen, Kairui
    Wang, Junwei
    Zhang, Yun
    [J]. ENTROPY, 2016, 18 (01):
  • [6] On Consensus of Nonlinear Multi-Agent Systems with Output Constraints
    Dinh Hoa Nguyen
    Narikiyo, Tatsuo
    Kawanishi, Michilnro
    [J]. IFAC PAPERSONLINE, 2016, 49 (22): : 103 - 108
  • [7] Adaptive consensus seeking of multiple nonlinear systems
    Dong, Wenjie
    [J]. INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, 2012, 26 (05) : 419 - 434
  • [8] Adaptive Consensus Tracking of High-order Nonlinear Multi-agent Systems with Directed Communication Graphs
    Fu, Junjie
    Wang, Jinzhi
    [J]. INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, 2014, 12 (05) : 919 - 929
  • [9] Distributed observers design for leader-following control of multi-agent networks
    Hong, Yiguang
    Chen, Guanrong
    Bushnell, Linda
    [J]. AUTOMATICA, 2008, 44 (03) : 846 - 850
  • [10] Horn R. A, 1985, Matrix Analysis, V2