Adaptive group consensus in uncertain networked Euler-Lagrange systems under directed topology

被引:56
|
作者
Liu, Jun [1 ,2 ]
Ji, Jinchen [3 ]
Zhou, Jin [1 ]
Xiang, Lan [4 ]
Zhao, Liyun [1 ,5 ]
机构
[1] Shanghai Univ, Shanghai Inst Appl Math & Mech, Shanghai 200072, Peoples R China
[2] Jining Univ, Dept Math, Qufu 273155, Shandong, Peoples R China
[3] Univ Technol Sydney, Fac Engn & IT, Sydney, NSW 2007, Australia
[4] Shanghai Univ, Sch Sci, Dept Phys, Shanghai 200444, Peoples R China
[5] Inner Mongolia Univ Sci & Technol, Sch Math Phys & Biol Engn, Baotou 014010, Peoples R China
基金
美国国家科学基金会;
关键词
Group consensus; Networked Euler-Lagrange systems; Parametric uncertainties; Adaptive control; Input-to-state stable; MULTIAGENT SYSTEMS; MECHANICAL SYSTEMS; INERTIAL AGENTS; SYNCHRONIZATION; FLOCKING; TRACKING; GRAPHS;
D O I
10.1007/s11071-015-2222-y
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
This paper investigates the adaptive group consensus of networked Euler-Lagrange systems with parametric uncertainties under directed topology graph. A novel decomposition approach is developed by using both algebraic graph theory and matrix theory. Three distributed adaptive group consensus protocols are proposed for the cases of topology graphs with acyclic partition and balanced couple, respectively. Some necessary and sufficient conditions for solving group consensus problems are established. It is shown that for the case of directed acyclic graphs, the group consensus can always be guaranteed by the structure of acyclic interaction topology. In particular, an explicit expression of group consensus states can be obtained using the proposed integral protocol, which can be used to develop a unified approach yielding the desired group consensus. For the case of directed balanced couple graphs, a simple algebraic criterion for ensuring group consensus is presented in terms of the eigenvalue computation of Laplacian matrix and thus can be easily applied in practice. Finally, numerical simulations are given to demonstrate the effectiveness of the proposed control methodologies.
引用
收藏
页码:1145 / 1157
页数:13
相关论文
共 50 条
  • [21] Adaptive H∞ Consensus Control of Euler-Lagrange Systems on Directed Network Graph
    Miyasato, Yoshihiko
    [J]. PROCEEDINGS OF 2016 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI), 2016,
  • [22] Adaptive Position Feedback Consensus of Networked Euler-Lagrange Systems in the Presence of Communication Delays
    Wang, Lijiao
    Hu, Yong
    [J]. PROCEEDINGS OF THE 28TH CHINESE CONTROL AND DECISION CONFERENCE (2016 CCDC), 2016, : 5297 - 5302
  • [23] Adaptive Velocity-free Consensus of Networked Euler-Lagrange Systems with Delayed Communication
    Wang, Lijiao
    Hu, Yong
    Meng, Bin
    [J]. PROCEEDINGS OF THE 2016 12TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA), 2016, : 851 - 856
  • [24] Distributed leaderless consensus algorithms for networked Euler-Lagrange systems
    Ren, Wei
    [J]. INTERNATIONAL JOURNAL OF CONTROL, 2009, 82 (11) : 2137 - 2149
  • [25] Achieving distributed consensus for networked uncertain Euler-Lagrange systems with average dwell time approach
    Liu, Lixia
    Liu, Wencheng
    Li, Yanping
    Liu, Shang
    Guo, Rongwei
    Li, Bin
    [J]. ASIAN JOURNAL OF CONTROL, 2024, 26 (02) : 657 - 667
  • [26] Adaptive Leader-Following Consensus of Networked Uncertain Euler-Lagrange Systems With Dynamic Leader Based on Sensory Feedback
    Lu, Maobin
    Liu, Lu
    [J]. 2018 15TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION (ICARCV), 2018, : 756 - 761
  • [27] Adaptive Leader-Following Consensus for Multiple Euler-Lagrange Systems under Directed Switching Networks
    Liu Tao
    Huang Jie
    [J]. PROCEEDINGS OF THE 35TH CHINESE CONTROL CONFERENCE 2016, 2016, : 8178 - 8183
  • [28] Fixed-time synchronization of networked uncertain Euler-Lagrange systems
    Dong, Yi
    Chen, Zhiyong
    [J]. AUTOMATICA, 2022, 146
  • [30] Adaptive Appointed-Time Consensus Control of Networked Euler-Lagrange Systems With Connectivity Preservation
    Wei, Caisheng
    Gui, Mingzhen
    Zhang, Chengxi
    Liao, Yuxin
    Dai, Ming-Zhe
    Luo, Biao
    [J]. IEEE TRANSACTIONS ON CYBERNETICS, 2022, 52 (11) : 12379 - 12392