采用基于多属性决策的方法评估小型电动垂直起降固定翼无人机的任务效率

Zhuo Bai, Bangchu Zhang, Zhong Tian, Shangnan Zou, Weiyu Zhu
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引用次数: 0

摘要

在复杂、多源和多维要求下,评估各种无人机配置的任务效率仍然是一项重大挑战。本研究旨在开发一种综合决策支持系统(DSS),采用任务效率评估、概率犹豫模糊集(PHF)和多属性决策(MADM)方法来评估和优化无人机设计。在所提出的方法中,任务效率被定义为完成任务所需的飞行性能、适应性和经济可行性的综合衡量标准。通过设计 "需求-能力-设计 "映射方法,该系统可有效解决决策过程中的多属性冲突。为了演示所提出的方法,对一组小型电动垂直起降固定翼(e-VTOLFW)无人机进行了比较,并根据其任务效率进行了排序。此外,还讨论了不同任务要求对无人机评估的影响。结果表明,该模型解决了无人机设计中信息流不清晰的传统问题。通过改进评价标准,该模型增强了无人机设计评估中的知情决策和评价结果的稳健性。此外,该模型还具有通用性,可广泛应用于 "需求-产品设计 "等类似领域,从而提高对产品性能的理解和优化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementing a Multi-Attribute Decision-Making-Based Approach to Evaluate Small Electric Vertical Takeoff and Landing Fixed-Wing Drones with Mission Efficiency
Evaluating the mission efficiency of various drone configurations under complex, multi-source, and multi-dimensional requirements remains a significant challenge. This study aimed to develop a comprehensive decision support system (DSS) that employs mission efficiency evaluation, probabilistic hesitant fuzzy sets (PHFs), and multi-attribute decision-making (MADM) methods to assess and optimize drone design. In the proposed method, mission efficiency is defined as a composite measure of the flight performance, adaptability, and economic viability required to complete a mission. By designing a “demand–capability–design” mapping approach, this system effectively resolves multi-attribute conflicts in the decision-making process. To demonstrate the proposed approach, a set of small electric vertical takeoff and landing fixed-wing (e-VTOLFW) drones are compared and ranked based on their mission efficiency. The impacts of different mission requirements on drone evaluation are also discussed. The results demonstrate that this model resolves the traditional issue of unclear information flow in drone design. By improving the evaluation criteria, it enhances informed decision making and the robustness of evaluation results in drone design assessments. Additionally, the model is generalizable and can be widely applied to similar fields such as “demand–product design”, improving the understanding and optimization of product performance.
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