Air-ground coordinated unmanned swarm systems: A multitasking framework for control design

被引:1
|
作者
Wang, Xiuye [1 ]
Wang, Huiming [1 ]
Sun, Qinqin [2 ]
Chen, Ye-Hwa [3 ]
机构
[1] Nanjing Univ Sci & Technol, Sch Mech Engn, Nanjing 210094, Peoples R China
[2] Nanjing Univ Aeronaut & Astronaut, Coll Energy & Power Engn, Nanjing 210016, Peoples R China
[3] Georgia Inst Technol, George W Woodruff Sch Mech Engn, Atlanta, GA 30332 USA
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Air-ground coordination; Unmanned swarm system; Tracking-avoidance; Adaptive robust control; Uncertainty; TRACKING CONTROL; UAV;
D O I
10.1016/j.isatra.2023.12.003
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
An air-ground heterogeneous unmanned swarm system coordination is considered. The system consists of N unmanned aerial vehicles (UAVs) and one unmanned ground vehicle (UGV). This forms a complicated mission, which consists of the following four different tasks. First, the aerial vehicles are in a compact formation, while avoiding collision with each other. Second, the aerial vehicles should stay close to the ground, while avoiding collision with the ground. Third, the aerial vehicles should stay close to the ground vehicle. Fourth, the ground vehicle should follow a desired trajectory. These tasks reflect two seemingly contradictory nature: close to (due to tracking) and away from (due to avoidance). The effective control design should address all four tasks even in the presence of uncertainty. By two creative transformations, this multitude of tasks are consolidated in a chi-measure. An adaptive robust control, which includes a robust control scheme and an online adaptation law, is then proposed to render guarantee boundedness performance of this chi-measure. As a result, the control design is able to accomplish the combined tracking-avoidance mission for the uncertain swarm system. Despite the presence of conflicting aspects between these tasks, the designed controller exhibits outstanding performance.
引用
收藏
页码:315 / 329
页数:15
相关论文
共 50 条
  • [1] Unmanned tactical air-ground systems family of unmanned systems experiment
    Fyfe, W
    Johnson, R
    2005 IEEE International Workshop on Robot and Human Interactive Communication (RO-MAN), 2005, : 103 - 108
  • [2] Distributed Nonlinear Predictive Control for Unmanned Air-Ground Vehicles
    Morando, Alessandra Elisa Sindi
    Bozzi, Alessandro
    Graffione, Simone
    Sacile, Roberto
    Zero, Enrico
    IFAC PAPERSONLINE, 2024, 58 (21): : 37 - 42
  • [3] Unmanned Aircraft Systems Air-Ground Channel Characterization for Future Applications
    Matolak, David W.
    Sun, Ruoyu
    IEEE VEHICULAR TECHNOLOGY MAGAZINE, 2015, 10 (02): : 79 - 85
  • [4] AIR-GROUND CHANNEL CHARACTERIZATION FOR UNMANNED AIRCRAFT SYSTEMS: THE MOUNTAINOUS ENVIRONMENT
    Sun, Ruoyu
    Matolak, David W.
    2015 IEEE/AIAA 34TH DIGITAL AVIONICS SYSTEMS CONFERENCE (DASC), 2015,
  • [5] A Visio and Neu a Network Based Air-Ground Coordinated Control System
    Jiang, Muyun
    Shi, Jiahui
    Ma, Hongbin
    Li, You
    PROCEEDINGS OF 2017 IEEE INTERNATIONAL CONFERENCE ON UNMANNED SYSTEMS (ICUS), 2017, : 488 - 493
  • [6] Trajectory Design and Access Control for Air-Ground Coordinated Communications System With Multiagent Deep Reinforcement Learning
    Ding, Ruijin
    Xu, Yadong
    Gao, Feifei
    Shen, Xuemin
    IEEE INTERNET OF THINGS JOURNAL, 2022, 9 (08) : 5785 - 5798
  • [7] Air-Ground Channels & Models: Comprehensive Review and Considerations for Unmanned Aircraft Systems
    Matolak, David W.
    2012 IEEE AEROSPACE CONFERENCE, 2012,
  • [8] Air-Ground Channel Characterization for Unmanned Aircraft Systems: the Hilly Suburban Environment
    Matolak, David W.
    Sun, Ruoyu
    2014 IEEE 80TH VEHICULAR TECHNOLOGY CONFERENCE (VTC FALL), 2014,
  • [9] Optimal Unmanned Ground Vehicle-Unmanned Aerial Vehicle Formation-Maintenance Control for Air-Ground Cooperation
    Zhang, Jingmin
    Yue, Xiaokui
    Zhang, Haofei
    Xiao, Tiantian
    APPLIED SCIENCES-BASEL, 2022, 12 (07):
  • [10] Air-Ground Coordinated MEC: Joint Task, Time Allocation and Trajectory Design
    Wang, Liuneng
    Li, Yanjun
    Chen, Yuzhe
    Li, Tingting
    Yin, Zheng
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2025, 74 (03) : 4728 - 4743