Collaborative tracking node planning of MUAV based on adaptive shuffled frog leaping algorithm

被引：0
|
作者：
Xue, Kaijia [1 ]
Wang, Congqing [1 ]
Li, Zhiyu [1 ]
机构：
[1] College of Automation, Nanjing University of Aeronautics and Astronautics, Nanjing
来源：
Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) | 2015年 / 43卷
关键词：
Adaptive; Asymmetric planning; Cost function; Multiple unmanned aerial vehicle; Shuffled frog leaping algorithm; Tracking node planning;
D O I：
10.13245/j.hust.15S1081
中图分类号：
学科分类号：
摘要：
An adaptive shuffled frog leaping algorithm (SFLA) was put forward to solve the collaborative tracking node planning of multiple unmanned aerial vehicle (MUAV) that different UAVs set out from the source point to find routes with minimum cost function. In this optimization algorithm, inserting breakpoint in whole tracking nodes was used to code. At the same time, the exchange operation was adopted to update the sequence of individual. The adaptive operator was introduced to improve the convergence speed and precision in the shuffled frog leaping algorithm. The results of simulation experiment show that the proposed adaptive shuffled frog leaping algorithm is more effective in solving the asymmetric MUAV collaborative tracking node planning. ©, 2015, Huazhong University of Science and Technology. All right reserved.
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页码：341 / 344
页数：3
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