航空学报 > 2023, Vol. 44 Issue (7): 327100-327100   doi: 10.7527/S1000-6893.2022.27100

面向任务需求的模块化无人机配置方法

肖和业1, 杨建峰2, 白俊强1(), 张旭东3, 吴利荣3   

  1. 1.西北工业大学 无人系统技术研究院,西安 710072
    2.中国人民解放军 95889部队,酒泉 735018
    3.中国人民解放军 96236部队,北京 100085
  • 收稿日期:2022-03-04 修回日期:2022-03-16 接受日期:2022-06-23 出版日期:2023-04-15 发布日期:2022-07-08
  • 通讯作者: 白俊强 E-mail:Junqiang@nwpu.edu.cn
  • 基金资助:
    国家级项目

Modular UAVs configuration method responded to task requirements

Heye XIAO1, Jianfeng YANG2, Junqiang BAI1(), Xudong ZHANG3, Lirong WU3   

  1. 1.Unmanned System Research Institute,Northwestern Polytechnical University,Xi’an 710072,China
    2.95889 Troop of PLA,Jiuquan 735018,China
    3.96236 Troop of PLA,Beijing 100085,China
  • Received:2022-03-04 Revised:2022-03-16 Accepted:2022-06-23 Online:2023-04-15 Published:2022-07-08
  • Contact: Junqiang BAI E-mail:Junqiang@nwpu.edu.cn
  • Supported by:
    National Level Project

摘要:

为了实现成本约束下面向任务需求的模块化无人机(UAVs)高效配置,基于无人机需求集和模块备选元素集,构建了任务需求与模块备选元素之间的关联矩阵;以无人机总体成本为约束条件,建立了需求满意度评价模型,引入了改进粒子群算法以获得无人机专用模块的最优配置方案,并通过算例与其他2种优化算法对比,验证了本文优化算法的有效性,进而提出了一种面向模块化无人机的配置方法。以某任务场景为例,在预定成本约束下构建了3型无人机的模块配置方案,并与文献中的单兵无人机参数配置进行对比,验证了配置方案的合理性。结合不同配置方案的成本计算结果表明,提出的模块化无人机配置方法能够实现无人机性能、成本与多种任务用途需求的协同匹配。在此基础之上,开展了模块化无人机多个配置方案单体成本、面向任务运用成本的对比分析,探讨了无人机配置参数对其单机及集群运用成本的影响规律,间接验证了本文算法对无人机单机及集群运用成本控制的支撑作用。

关键词: 无人机配置方法, 模块化无人机, 成本控制, 需求满意度评价, 粒子群算法

Abstract:

A configuration method for constructing modular Unmanned Aerial Vehicles (UAVs) is proposed to meet their mission requirements under cost constraints. Firstly, the set of mission requirements and module alternative elements are constructed. The correlation between mission requirements and module alternative elements is established. A demand satisfaction evaluation algorithm is built by selecting the overall costs of UAVs as the constraint condition. The particle swarm optimization algorithm is introduced to obtain the optimal configuration plan of the special-use UAV modules in the evaluation model. A numerical example is given to illustrate the difference between the proposed algorithm and the genetic algorithms. The results of the proposed method agree with those of the genetic algorithms. Then, a mission scenario is selected as an example, and the disposable UAVs are planned to be used in this mission. The modular configuration plans of three types of UAVs are constructed by the proposed method, restrained by the predetermined cost. The these plans show good agreements with the parameter configuration of disposable UAVs in previous studies. The rationality of the proposed configuration method is verified according to the calculation results of cost of each plan. Therefore, the modular UAVs configuration method can be used to achieve collaborative match of the performance of UAVs with the cost and task requirements of UAVs. Furthermore, single UAV cost and task cost of UAVs with different plans, which are obtained by the proposed configuration methods, are compared. The effects of configuration selections on the cost of single UAVs and swam UAVs are discussed. It is concluded that the proposed configuration algorithm can be used to control the cost of a single UAV and swarm UAVs.

Key words: UAV configuration method, modular UAV, cost control, demand satisfaction evaluation model, particle swarm optimization method

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