共 50 条
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