Task allocation of heterogeneous multi-UAVs in uncertain environment based on multi-strategy integrated GWO

被引：0
|
作者：
Zhang A. [1 ]
Yang M. [1 ]
Bi W. [1 ]
Zhang B. [1 ]
Wang Y. [1 ]
机构：
[1] School of Aeronautics, Northwestern Polytechnical University, Xi’an
来源：
Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica | 2023年 / 44卷 / 08期
基金：
中国国家自然科学基金;
关键词：
grey wolf optimization algorithm; heterogeneous unmanned aerial vehicles; multiple unmanned aerial vehicles; task allocation; uncertain environment;
D O I：
10.7527/S1000-6893.2022.27115
中图分类号：
学科分类号：
摘要：
To solve the problem of task allocation in reconnaissance and attack on ground targets by multi-UAVs with complex constraints，the impact of multiple uncertain factors such as uncertain task execution time，target disappear⁃ ance time and UAV cruise speed on the task allocation results is considered. A fuzzy chance constrained program⁃ ming model for multi-UAV task allocation is constructed based on the fuzzy credibility theory，with minimization of the total cost as the optimization goal. In addition，a Multi-Strategy Integrated Grey Wolf Optimization（IMSGWO）algo⁃ rithm is proposed. By introducing the adaptive control parameter adjustment strategy，adaptive inertia weight strategy，optimal learning strategy and jumping out of local optimal strategy，the search ability of the algorithm is improved while enhancing population diversity. Numerical results show that the proposed algorithm can effectively solve the problem of multi-UAV task allocation in uncertain environment. © 2023 AAAS Press of Chinese Society of Aeronautics and Astronautics. All rights reserved.
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