Distributed control for output-constrained nonlinear multi-agent systems with completely unknown non-identical control directions

被引:18
|
作者
Fan, Debao [1 ]
Zhang, Xianfu [1 ]
Liu, Shuai [1 ]
Chen, Xiandong [1 ]
机构
[1] Shandong Univ, Sch Control Sci & Engn, Jinan 250061, Peoples R China
基金
中国国家自然科学基金;
关键词
Multi-agent systems; Constraints; Unknown control directions; Distributed control; ADAPTIVE CONSENSUS;
D O I
10.1016/j.jfranklin.2021.08.021
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 studies the consensus problem for a class of nonlinear multi-agent systems with asym-metric time-varying output constraints and completely unknown non-identical control directions. Firstly, in order to deal with the problem of asymmetric time-varying output constraints, the original output-constrained multi-agent systems are transformed into new unconstrained multi-agent systems by con-structing the state transformation for each agent. Secondly, the emergence of multiple Nussbaum-type function terms is avoided by introducing novel sliding-mode-esque auxiliary variables and consensus estimate variables, which allows the control directions to be completely unknown non-identical. Thirdly, a novel control strategy is proposed by combining novel variables with state transformation method for the first time, which makes the design of distributed consensus protocol more concise. Through Lya-punov stability analysis, the proposed distributed protocol ensures that the output constraints are never violated and the consensus can be achieved asymptotically. Finally, a practical simulation example is given to demonstrate the effectiveness of the proposed distributed consensus protocol. (c) 2021 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:8270 / 8287
页数:18
相关论文
共 50 条
  • [41] Output synchronization for multi-agent systems with prescribed performance in the presence of unknown control directions
    Peng, Junmin
    Wang, Kaining
    Li, Jianbo
    Li, Chaoyong
    Xiao, Shenping
    ASIAN JOURNAL OF CONTROL, 2024, 26 (05) : 2732 - 2744
  • [42] Output feedback control for a class of output-constrained nonlinear systems
    Li, Hanfeng
    Zhang, Xianfu
    Chen, Xiandong
    Liu, Qingrong
    2017 29TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2017, : 6355 - 6359
  • [43] Cooperative Output Regulation for a Class of Nonlinear Multi-agent Systems with Unknown Control Directions subject to Switching Networks
    Liu, Tao
    Huang, Jie
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2018, 63 (03) : 783 - 790
  • [44] Distributed Adaptive Consensus of Nonlinear Multi-agent Systems with Unknown Control Coefficients
    Niu, Xinglong
    Liu, Yinigang
    Man, Yongchao
    IFAC PAPERSONLINE, 2015, 48 (28): : 915 - 920
  • [45] Distributed Containment Control for a Class of Uncertain Nonlinear Multi-Agent Systems With Unknown Control Direction
    Cheng, Hui
    Dong, Yi
    PROCEEDINGS OF THE 36TH CHINESE CONTROL CONFERENCE (CCC 2017), 2017, : 1174 - 1179
  • [46] Delay Robustness in Non-Identical Multi-Agent Systems
    Muenz, Ulrich
    Papachristodoulou, Antonis
    Allgoewer, Frank
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2012, 57 (06) : 1597 - 1603
  • [47] Adaptive Fuzzy Output-Constrained Control for Nonlinear Stochastic Systems With Input Delay and Unknown Control Coefficients
    Wang, Yingchun
    Zhang, Jiaxin
    Zhang, Huaguang
    Xie, Xiangpeng
    IEEE TRANSACTIONS ON CYBERNETICS, 2021, 51 (11) : 5279 - 5290
  • [48] Coordinative control of multi-agent systems using distributed nonlinear output regulation
    Jia Liu
    Zhongxin Liu
    Zengqiang Chen
    Nonlinear Dynamics, 2012, 67 : 1871 - 1881
  • [49] Coordinative control of multi-agent systems using distributed nonlinear output regulation
    Liu, Jia
    Liu, Zhongxin
    Chen, Zengqiang
    NONLINEAR DYNAMICS, 2012, 67 (03) : 1871 - 1881
  • [50] Adaptive Event-triggered Control for Stochastic Nonlinear Multi-agent Systems with Unknown Control Directions
    Jiaang Zhang
    Chang-E. Ren
    Quanxin Fu
    International Journal of Control, Automation and Systems, 2021, 19 : 2950 - 2958