Distributed optimization problem for double-integrator systems with the presence of the exogenous disturbances

被引:29
|
作者
Ngoc-Tu Tran [1 ,2 ]
Wang, Yan-Wu [1 ,2 ,3 ]
Yang, Wu [1 ,2 ]
机构
[1] Huazhong Univ Sci & Technol, Sch Automat, Wuhan 430074, Hubei, Peoples R China
[2] Huazhong Univ Sci & Technol, Minist Educ, Key Lab Image Proc & Intelligent Control, Wuhan, Hubei, Peoples R China
[3] China Three Gorges Univ, Hubei Prov Collaborat Innovat Ctr New Energy Micr, Yichang, Peoples R China
基金
中国国家自然科学基金;
关键词
Second-order multi-agent systems; Distributed optimization; Gradient-based algorithm; External disturbance; Internal model principle; CONVEX-OPTIMIZATION; MULTIAGENT SYSTEMS; ALGORITHMS; CONSENSUS;
D O I
10.1016/j.neucom.2017.07.005
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The aim of this paper is to study the distributed optimization problem for continuous-time multi-agent systems with the existence and the interference of external disturbance, therein each agent is described as double-integrator dynamic. To reject the exogenous disturbance, the distributed algorithm is proposed for each agent based on the internal model principle. The proposed algorithm only utilizes the position information of each agent from its neighbors subject to the undirected graph, which can reduce communication costs and energy consumptions in applications. Moreover, the algorithm only needs the cost functions of the agent itself, which can greatly protect the privacy of other agents. The optimal solution of the problem is thus obtained with the design of Lyapunov function and the help of convex analysis, LaSallel's Invariance Principle. Finally, two numerical simulation examples and the comparison of proposed algorithm with other previous research are presented to illustrate the persuasive effectiveness of the theoretical result. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:386 / 395
页数:10
相关论文
共 50 条
  • [21] Coverage Control for Mobile Sensor Networks With Double-Integrator Dynamics and Unknown Disturbances
    Wang, Peng
    Song, Cheng
    Liu, Lu
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2023, 68 (10) : 6299 - 6306
  • [22] Robust consensus tracking of double-integrator dynamics by bounded distributed control
    Zhu, Bo
    Meng, Chang
    Hu, Guoqiang
    INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2016, 26 (07) : 1489 - 1511
  • [23] Resilient Consensus of Double-Integrator Multi-Agent Systems
    Dibaji, Seyed Mehran
    Ishii, Hideaki
    2014 AMERICAN CONTROL CONFERENCE (ACC), 2014, : 5139 - 5144
  • [24] Distributed Finite-Time Optimization for Integrator Chain Multiagent Systems With Disturbances
    Wang, Xiangyu
    Wang, Guodong
    Li, Shihua
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2020, 65 (12) : 5296 - 5311
  • [25] Distributed Differential Graphical Game for Control of Double-Integrator Multi-Agent Systems with Input Delay
    Jond H.B.
    IEEE Transactions on Control of Network Systems, 2024, 11 (04): : 1 - 12
  • [26] Distributed Formation Control for Time-delayed Multi-agent Systems with Double-integrator Dynamics
    Han, Liang
    Dong, Xiwang
    Li, Qingdong
    Ma, Ming
    Ren, Zhang
    PROCEEDINGS OF THE 38TH CHINESE CONTROL CONFERENCE (CCC), 2019, : 6172 - 6177
  • [27] Distributed average tracking for double-integrator multi-agent systems with reduced requirement on velocity measurements
    Ghapani, Sheida
    Ren, Wei
    Chen, Fei
    Song, Yongduan
    AUTOMATICA, 2017, 81 : 1 - 7
  • [28] Distributed Near-Optimal Consensus of Double-Integrator Multi-Agent Systems With Input Constraints
    Deng, Qingyun
    Zhang, Yinyan
    2021 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2021,
  • [29] Robustness issues in double-integrator undirected rigid formation systems
    Sun, Zhiyong
    Anderson, Brian D. O.
    Mou, Shaoshuai
    Morse, A. Stephen
    IFAC PAPERSONLINE, 2017, 50 (01): : 1334 - 1339
  • [30] An event-triggered protocol for distributed optimal coordination of double-integrator multi-agent systems
    Wang, Dong
    Gupta, Vijay
    Wang, Wei
    NEUROCOMPUTING, 2018, 319 : 34 - 41