Journal of System Simulation
Abstract
Abstract: To solve the problem of difficulty in UAV cluster formation rendezvous based on MADDPG algorithm, an autonomous collaborative control strategy based on LDE-MADDPG algorithm is proposed. To address the issues of weak generalization, poor scalability, and slow cluster training process of MADDPG algorithm, LDE-MADDPG algorithm was proposed by designing a state feature learning network and a decoupled Critical network. By integrating LDE-MADDPG algorithm with strategy generation elements such as the decoupled reward function, cluster state space, and UAV action space, a control strategy for UAV cluster formation endezvous that can adapt to diverse formations and varying quantities has been developed. Simulation experiments show that compared to MADDPG algorithm, LDE-MADDPG algorithm improves the training process by 19.6%; The generated control strategy can complete the assembly of six different formations, such as a diamond, within 60 seconds, and achieve the formation and assembly of 6-21 drone clusters within 80 seconds with good generalization and scalability.
Recommended Citation
Xiao, Wei; Gao, Jiabo; and Ke, Xueliang
(2025)
"Control Strategy for UAV Cluster Formation Rendezvous Based on LDE-MADDPG Algorithm,"
Journal of System Simulation: Vol. 37:
Iss.
9, Article 12.
DOI: 10.16182/j.issn1004731x.joss.24-0333
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol37/iss9/12
First Page
2335
Last Page
2351
CLC
V279; TP391.9
Recommended Citation
Xiao Wei, Gao Jiabo, Ke Xueliang. Control Strategy for UAV Cluster Formation Rendezvous Based on LDE-MADDPG Algorithm[J]. Journal of System Simulation, 2025, 37(9): 2335-2351.
DOI
10.16182/j.issn1004731x.joss.24-0333
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