Iterative learning-based formation control for multiple quadrotor unmanned aerial vehicles

被引:22
作者
Zhao, Zhihui [1 ]
Wang, Jing [1 ]
Chen, Yangquan [2 ]
Ju, Shuang [1 ]
机构
[1] Beijing Univ Chem Technol, Coll Informat Sci & Technol, Dept Automat, Beijing, Peoples R China
[2] Univ Calif Merced, Sch Engn, Mechatron Embedded Syst & Automat Lab, Merced, CA USA
基金
中国国家自然科学基金; 北京市自然科学基金;
关键词
Multiple quadrotor UAV system; double-layer formation control; iterative learning control; directed graph; FOLLOWER FORMATION CONTROL; MULTIAGENT SYSTEMS; NETWORKS; TRACKING; DESIGN; UAVS;
D O I
10.1177/1729881420911520
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
A double-layer formation control is proposed to solve the repeated tasks for multiple quadrotor unmanned aerial vehicle systems. The first layer aims at achieving a formation target in which the iterative learning control is designed based on relative distance with neighbor unmanned aerial vehicles and absolute distance with virtual leader unmanned aerial vehicle. The formation controller is responsible for keeping the formation shape and generating the desired flying trajectories for each drones. The second layer control aims at achieving a high-precision tracking to desired flying trajectories which are generated from the formation controller. A double closed-loop proportional-derivative strategy is designed to ensure the accuracy of trajectory tracking for each individual drone. Simulations for the circle formation mission of the multiple quadrotor unmanned aerial vehicle system are given to verify the efficiency of the proposed method.
引用
收藏
页数:12
相关论文
共 50 条
  • [41] A cooperative control framework of multiple unmanned aerial vehicles for dynamic oil spill cleanup
    Kaviri, Samane
    Tahsiri, Ahmadreza
    Taghirad, Hamid D.
    JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING, 2021, 43 (06)
  • [42] Time-varying formation control for unmanned aerial vehicles with switching interaction topologies
    Dong, Xiwang
    Zhou, Yan
    Ren, Zhang
    Zhong, Yisheng
    CONTROL ENGINEERING PRACTICE, 2016, 46 : 26 - 36
  • [43] Reinforcement learning-based formation-surrounding control for multiple quadrotor UAVs pursuit-evasion games
    Xiong, Hang
    Zhang, Ying
    ISA TRANSACTIONS, 2024, 145 : 205 - 224
  • [44] Adaptive finite time fault tolerant control for the quadrotor unmanned aerial vehicles based on time-triggered strategy
    Di, Wangyue
    Li, Zhigang
    Lv, Dongyi
    Gao, Chuang
    Yang, Yonghui
    Zhou, Xin
    OPTIMAL CONTROL APPLICATIONS & METHODS, 2023, 44 (01) : 66 - 80
  • [45] Observer-Based Adaptive Neural Control of Quadrotor Unmanned Aerial Vehicles Subject to Model Uncertainties and External Disturbances
    Mousavi, Rashin
    Mousavi, Arash
    Mousavi, Yashar
    Tavasoli, Mahsa
    Arab, Aliasghar
    Kucukdemiral, Ibrahim Beklan
    Fekih, Afef
    ACTUATORS, 2024, 13 (12)
  • [46] Route planning for multiple unmanned aerial vehicles
    Aguiar, Antonio Lucas Sousa
    Pinto, Vandilberto Pereira
    Sousa, Ligia Maria Carvalho
    Da Silva Pinheiro, Jose Lucas
    do Nascimento Sousa, Jose Cleilton
    PRZEGLAD ELEKTROTECHNICZNY, 2024, 100 (09): : 219 - 223
  • [47] Distributed fault-tolerant formation control for multiple unmanned aerial vehicles under actuator fault and intermittent communication interrupt
    Han, Bing
    Jiang, Ju
    Yu, Chaojun
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING, 2021, 235 (07) : 1064 - 1083
  • [48] Robust Hierarchical Formation Control of Unmanned Aerial Vehicles via Neural-Based Observers
    Fei, Yang
    Sun, Yuan
    Shi, Peng
    DRONES, 2022, 6 (02)
  • [49] Mobile Edge Computing and Machine Learning in the Internet of Unmanned Aerial Vehicles: A Survey
    Ning, Zhaolong
    Hu, Hao
    Wang, Xiaojie
    Guo, Lei
    Guo, Song
    Wang, Guoyin
    Gao, Xinbo
    ACM COMPUTING SURVEYS, 2024, 56 (01)
  • [50] Cooperative formation control of multiple aerial vehicles based on guidance route in a complex task environment
    Sun, Guibin
    Zhou, Rui
    Xu, Kun
    Weng, Zhi
    Zhang, Yuhang
    Dong, Zhuoning
    Wang, Yingxun
    CHINESE JOURNAL OF AERONAUTICS, 2020, 33 (02) : 701 - 720