Tracking and Formation of Multi-agent Systems with Collision and Obstacle Avoidance Based on Distributed RHC

被引:8
|
作者
Yang, Yuanqing [1 ]
Ding, Baocang [1 ]
机构
[1] Xi An Jiao Tong Univ, Sch Elect & Informat Engn, Dept Automat, Xian 710049, Shaanxi, Peoples R China
基金
国家重点研发计划;
关键词
Receding horizon control (RHC); Distributed control; Multi-agent systems; Collision avoidance; Obstacle avoidance; MODEL-PREDICTIVE CONTROL; CONSENSUS;
D O I
10.1007/s00034-018-1003-5
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
This paper proposes a distributed receding horizon control approach for the formation and tracking problems of multi-agent systems with collision and obstacle avoidance. We design an algorithm to enlarge the terminal position sets of the agents in sequential order. Since the proposed approach is based on the synchronous framework, each agent must utilize the assumed predictive information of its neighbors. A compatibility constraint is reformulated for the local optimization, which restricts the deviation between the assumed and true predictive states. To ensure the safety of each agent, the deviation-dependent collision-avoidance constraint and the obstacle-avoidance constraint are designed. Moreover, the closed-loop multi-agent systems are guaranteed to be exponentially stable, and the control performance is improved compared with the previous approaches. A simulation example is provided to illustrate the advantages of the proposed approach.
引用
收藏
页码:2951 / 2970
页数:20
相关论文
共 50 条
  • [11] Multi-Agent Cluster Systems Formation Control with Obstacle Avoidance
    Sun, Yi
    Hu, Xiaoguang
    Xiao, Jin
    Zhang, Guofeng
    Wang, Shaojie
    Liu, Lei
    PROCEEDINGS OF THE 15TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA 2020), 2020, : 1635 - 1640
  • [12] Formation Control Strategy of Multi-agent Systems with Obstacle Avoidance
    Li, Jingcheng
    Zhang, Changzhu
    Huang, Chao
    Zhang, Hao
    Wang, Zhuping
    Kong, Deyang
    2020 12TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTATIONAL INTELLIGENCE (ICACI), 2020, : 138 - 143
  • [13] Relative Distributed Formation and Obstacle Avoidance with Multi-agent Reinforcement Learning
    Yan, Yuzi
    Li, Xiaoxiang
    Qiu, Xinyou
    Qiu, Jiantao
    Wang, Jian
    Wang, Yu
    Shen, Yuan
    2022 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2022), 2022, : 1661 - 1667
  • [14] Velocity Obstacle Approaches for Multi-Agent Collision Avoidance
    Douthwaite, James A.
    Zhao, Shiyu
    Mihaylova, Lyudmila S.
    UNMANNED SYSTEMS, 2019, 7 (01) : 55 - 64
  • [15] Path planning in formation and collision avoidance for multi-agent systems
    Cheng, Pangcheng David Cen
    Indri, Marina
    Possieri, Corrado
    Sassano, Mario
    Sibona, Fiorella
    NONLINEAR ANALYSIS-HYBRID SYSTEMS, 2023, 47
  • [16] Formation control and collision avoidance for a class of multi-agent systems
    Liu, Yutong
    Yu, Hongjun
    Shi, Peng
    Lim, Cheng-Chew
    JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2019, 356 (10): : 5395 - 5420
  • [17] Collision and obstacle avoidance strategy for multi-agent systems with velocity dynamic programing
    Xiong, Zhigang
    Liu, Zhong
    Luo, Yasong
    MEASUREMENT & CONTROL, 2023, 56 (1-2): : 257 - 268
  • [18] Formation control and collision avoidance for multi-agent systems based on position estimation
    Xia, Yuanqing
    Na, Xitai
    Sun, Zhongqi
    Chen, Jing
    ISA TRANSACTIONS, 2016, 61 : 287 - 296
  • [19] Collision/Obstacle Avoidance Dynamic Formation Reconfiguration of High-Order Nonlinear Multi-Agent Systems
    An, Liwei
    Gao, Weinan
    Deng, Chao
    Che, Wei-Wei
    2023 35TH CHINESE CONTROL AND DECISION CONFERENCE, CCDC, 2023, : 1480 - 1486
  • [20] A Scalable Distributed Collision Avoidance Scheme for Multi-agent UAV systems
    Lindqvist, Bjorn
    Sopasakis, Pantelis
    Nikolakopoulos, George
    2021 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2021, : 9212 - 9218