Systems Engineering and Electronics ›› 2022, Vol. 44 ›› Issue (8): 2530-2539.doi: 10.12305/j.issn.1001-506X.2022.08.18

• Systems Engineering • Previous Articles     Next Articles

Multi-level module partition method of UAV based on fuzzy clustering and expert scoring mechanism

Jianfeng YANG1,2, Heye XIAO3, Liang LI2, Junqiang BAI3,*, Weihao DONG2   

  1. 1. School of Aeronautic, Northwestern Polytechnical University, Xi'an 710072, China
    2. Unit 95889 of the PLA, Jiuquan 735018, China
    3. Unmanned System Technology Research Institute, Northwestern Polytechnical University, Xi'an 710072, China
  • Received:2021-07-05 Online:2022-08-01 Published:2022-08-24
  • Contact: Junqiang BAI

Abstract:

Based on the multi-level progressive module partition architecture of preliminary partition-comprehensive evaluation-precision partition, this paper provides a credible and effective method for module partition in modular unmanned aerial vehicle (UAV) design. In order to improve the credibility of the results of module partition, a scoring mechanism using expert reliability is introduced in the evaluation of module partition indicators. A multi-level module partition method is presented by applying fuzzy clustering and expert scoring mechanism. Taking the one-time and reusable UAVs as examples, the proposed module partition method is adopted to cluster the components and form a module partition scheme. Through the results of the module partition, it can be seen that the proposed method can provide a reliable module partition scheme and satisfy their application characteristics for different kinds of UAVs. Therefore, the rationality and effectiveness of the method is further verified.

Key words: modular unmanned aerial vehicle (UAV), module partition method, fuzzy clustering, expert reliability, network hierarchy structure, particle swarm optimization (PSO) algorithm

CLC Number: 

[an error occurred while processing this directive]