Consensus Disturbance Rejection of MIMO Linear Multiagent Systems With Directed Switching Topologies: A Reduced Order Observer Approach

被引:7
|
作者
Wang, Peijun [1 ,2 ]
Yu, Wenwu [3 ,4 ,5 ]
Huang, Tingwen [6 ]
Lv, Yuezu [7 ,8 ]
机构
[1] Anhui Normal Univ, Sch Math & Stat, Wuhu 241000, Peoples R China
[2] Anhui Normal Univ, Anhui Prov Engn Lab Intelligent Robots Informat F, Wuhu 241000, Peoples R China
[3] Southeast Univ, Frontiers Sci Ctr Mobile Informat Commun & Secur, Sch Math, Nanjing 210096, Peoples R China
[4] Purple Mt Labs, Nanjing 211111, Peoples R China
[5] Nantong Univ, Dept Elect Engn, Nantong 226019, Peoples R China
[6] Texas A&M Univ Qatar, Sci Program, Doha, Qatar
[7] Beijing Inst Technol, Adv Res Inst Multidisciplinary Sci, Beijing 100081, Peoples R China
[8] Beijing Inst Technol, Yangtze Delta Reg Acad, Jiaxing 314000, Peoples R China
基金
中国国家自然科学基金;
关键词
Multi-agent system; consensus; disturbance rejection; directed switching topologies; reduced order observer;
D O I
10.1109/TCSII.2022.3193730
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this brief, consensus disturbance rejection problem is investigated for multiple-input-multiple-output (MIMO) linear multi-agent systems (MASs) subject to non-vanishing disturbances under directed switching topologies. First, we design a reduced order unknown input observer (UIO) based only on the relative outputs to estimate the relative full states. Then a consensus controller together with a disturbance observer (DO) is designed to achieve the cooperative goal. Second, by using the average dwell time (ADT) method, it is proven that consensus can be achieved if the ADT is greater than a positive threshold, meanwhile the non-vanishing disturbances are attenuated by DO. Finally, theoretical result is verified by performing simulation.
引用
收藏
页码:4984 / 4988
页数:5
相关论文
共 50 条
  • [31] Consensus of multiagent systems with random switching topologies and its application
    Wang, Guoliang
    Sun, Yuanyuan
    INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2020, 30 (05) : 2079 - 2096
  • [32] Hierarchical Cooperative Control for Multiagent Systems With Switching Directed Topologies
    Hu, Jianqiang
    Cao, Jinde
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2015, 26 (10) : 2453 - 2463
  • [33] Distributed MIMO MFAC-based consensus tracking strategy for multiagent systems with fixed and switching topologies
    Song, Weizhao
    Feng, Jian
    Liu, Jinze
    INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2022, 53 (09) : 1888 - 1905
  • [34] Cluster Lag Consensus for Second-Order Multiagent Systems with Nonlinear Dynamics and Switching Topologies
    Wang, Yi
    Li, Yixiao
    Ma, Zhongjun
    Cai, Guoyong
    Chen, Guanrong
    IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2020, 50 (06): : 2093 - 2100
  • [35] Mean Square Consensus of General Linear Multiagent Systems with Communication Noises under Switching Topologies
    Chen, Kairui
    Yan, Chuance
    Ren, Qijun
    Zeng, Xianxian
    Wang, Junwei
    COMPLEXITY, 2022, 2022
  • [36] Reduced order disturbance observer for discrete-time linear Systems
    Kim, Kyung-Soo
    Rew, Keun-Ho
    AUTOMATICA, 2013, 49 (04) : 968 - 975
  • [37] Fully Distributed Consensus Control for Linear Multiagent Systems: A Reduced-Order Adaptive Feedback Approach
    Li, Xianwei
    Liu, Fangzhou
    Buss, Martin
    Hirche, Sandra
    IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS, 2020, 7 (02): : 967 - 976
  • [38] A Novel Reduced-Order Protocol for Consensus Control of Linear Multiagent Systems
    Li, Xianwei
    Soh, Yeng Chai
    Xie, Lihua
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2019, 64 (07) : 3005 - 3012
  • [39] Multiconsensus of first-order multiagent systems with directed topologies
    Zhao, Xiao-Wen
    Han, Guangsong
    Lai, Qiang
    Yue, Dandan
    MODERN PHYSICS LETTERS B, 2020, 34 (23):
  • [40] Bipartite consensus for a class of nonlinear multi-agent systems under switching topologies: A disturbance observer-based approach
    Wang, Qiang
    He, Wangli
    Zino, Lorenzo
    Tan, Dayu
    Zhong, Weimin
    NEUROCOMPUTING, 2022, 488 : 130 - 143