Optimization Study of Steady-State Aerial-Towed Cable Circling Strategy Based on BP Neural Network Prediction

IF 2.1 3区 工程技术 Q2 ENGINEERING, AEROSPACE
Luqi Feng, Xueqiang Liu, Zi Feng Nio
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引用次数: 0

Abstract

This paper presents models for UAV aerial-towed cables in free-end and fixed-end configurations, crucial for tasks like communication and aerial charging. By establishing a quasi steady-state model, computational results on cable shapes are obtained. To accelerate computations, a backpropagation (BP) neural network prediction model is trained, significantly reducing the computation time. An evaluation function has been developed that integrates both aircraft performance and cable shape considerations to evaluate circling parameters across various states. This function integrates techniques such as BP neural networks and particle swarm optimization (PSO) to refine parameters such as velocities and bank angles for both free-end and fixed-end cables. The results show that the BP neural network accurately predicts cable shapes, achieving a maximum error of 5% in towing force and verticality. Additionally, PSO efficiently optimizes circling parameters, thereby enhancing the effectiveness of the evaluation function in identifying optimal solutions. This approach significantly improves the efficiency of determining optimal circling parameters for UAV aerial-towed cables, thereby contributing to their operational efficacy.
基于 BP 神经网络预测的稳态空中牵引电缆绕行策略优化研究
本文介绍了无人机空中牵引电缆的自由端和固定端配置模型,这些配置对于通信和空中充电等任务至关重要。通过建立准稳态模型,获得了电缆形状的计算结果。为了加快计算速度,对反向传播(BP)神经网络预测模型进行了训练,从而大大减少了计算时间。已开发出一种评估功能,可综合考虑飞机性能和缆索形状,评估不同状态下的盘旋参数。该功能整合了 BP 神经网络和粒子群优化(PSO)等技术,以完善自由端和固定端缆索的速度和倾角等参数。结果表明,BP 神经网络能准确预测缆线形状,在牵引力和垂直度方面的最大误差为 5%。此外,PSO 还能有效优化绕航参数,从而提高评估功能在确定最优解方面的有效性。这种方法大大提高了确定无人机空中牵引电缆最佳盘旋参数的效率,从而有助于提高其运行效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Aerospace
Aerospace ENGINEERING, AEROSPACE-
CiteScore
3.40
自引率
23.10%
发文量
661
审稿时长
6 weeks
期刊介绍: Aerospace is a multidisciplinary science inviting submissions on, but not limited to, the following subject areas: aerodynamics computational fluid dynamics fluid-structure interaction flight mechanics plasmas research instrumentation test facilities environment material science structural analysis thermophysics and heat transfer thermal-structure interaction aeroacoustics optics electromagnetism and radar propulsion power generation and conversion fuels and propellants combustion multidisciplinary design optimization software engineering data analysis signal and image processing artificial intelligence aerospace vehicles'' operation, control and maintenance risk and reliability human factors human-automation interaction airline operations and management air traffic management airport design meteorology space exploration multi-physics interaction.
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