TY - JOUR
T1 - Distributed Network Control of Multi-UAV Systems for Cooperative Heavy-Load Transport Using a Virtual-Passivity Framework
AU - Liu, Runxiao
AU - Le, Xiangli
AU - Gu, Shuang
AU - Lv, Shuli
AU - Mao, Pengda
AU - Quan, Quan
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2026
Y1 - 2026
N2 - This paper presents a novel distributed network control framework for cooperative heavy-load transportation using multi-UAV systems, accounting for thrust limitations and heterogeneous cable characteristics. By constructing a virtual passive system comprising interconnected virtual nodes, springs, and dampers, the proposed method decouples internal coordination stability from external velocity tracking. A velocity tracking controller is devised to asymptotically steer the load’s velocity toward a desired trajectory, while preserving inter-agent cohesion through virtual interactions. Notably, the controller operates without explicit inter-UAV communication, relying solely on relative position measurements. Numerical simulations involving ten UAVs transporting a 14 kg load-exceeding 76% of their combined thrust capacity-along a figure-eight trajectory validate the proposed method. Field tests with six UAVs transporting a 6 kg load are conducted to validate the control framework’s performance in practical applications. The results confirm accurate velocity tracking, balanced cable tension distribution, and scalability to heterogeneous UAV team configurations.
AB - This paper presents a novel distributed network control framework for cooperative heavy-load transportation using multi-UAV systems, accounting for thrust limitations and heterogeneous cable characteristics. By constructing a virtual passive system comprising interconnected virtual nodes, springs, and dampers, the proposed method decouples internal coordination stability from external velocity tracking. A velocity tracking controller is devised to asymptotically steer the load’s velocity toward a desired trajectory, while preserving inter-agent cohesion through virtual interactions. Notably, the controller operates without explicit inter-UAV communication, relying solely on relative position measurements. Numerical simulations involving ten UAVs transporting a 14 kg load-exceeding 76% of their combined thrust capacity-along a figure-eight trajectory validate the proposed method. Field tests with six UAVs transporting a 6 kg load are conducted to validate the control framework’s performance in practical applications. The results confirm accurate velocity tracking, balanced cable tension distribution, and scalability to heterogeneous UAV team configurations.
KW - Cooperative transport
KW - UAV swarms
KW - distributed network control
KW - low-altitude economy
KW - passivity-based control
UR - https://www.scopus.com/pages/publications/105027408035
U2 - 10.1109/TNSE.2026.3654107
DO - 10.1109/TNSE.2026.3654107
M3 - 文章
AN - SCOPUS:105027408035
SN - 2327-4697
VL - 13
SP - 5905
EP - 5923
JO - IEEE Transactions on Network Science and Engineering
JF - IEEE Transactions on Network Science and Engineering
ER -