基于实测数据的飞机飞行姿态随机动力学模型辨识

IF 1.1 4区 工程技术 Q3 ENGINEERING, AEROSPACE
Haiquan Li, Xiaoqian Chen, Jiatu Zhang, Bochen Wang, Jiahui Peng, Liang Wang
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引用次数: 0

摘要

随机干扰无处不在。随机因素对飞行器飞行动力学建模和仿真的影响是必须考虑的问题。因此,本文在传统飞行器飞行姿态随机微分方程的基础上,建立了飞行器飞行姿态随机微分方程的模型。在此基础上,提出了一种基于未知参数和随机干扰稀疏识别思想的辨识方法。最后,利用一组实测飞行数据验证了所识别的随机模型在飞机飞行机动时比传统的确定性模型具有明显的优势。该方法可以提高飞机飞行动力学模型的精度和可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of a Stochastic Dynamic Model for Aircraft Flight Attitude Based on Measured Data
Stochastic disturbances are everywhere. The influence of stochastic factors on the modeling and simulation of aircraft flight dynamics should be considered. Therefore, a stochastic differential equation for aircraft flight attitude is modeled based on the traditional one in this paper. After that, an identification method based on the idea of sparse recognition for unknown parameters and stochastic disturbance is proposed. Finally, a set of measured flight data is used to verify that the identified stochastic model has obvious advantages over the traditional deterministic model when the aircraft is maneuvering in flight. This method can improve the accuracy and reliability of the aircraft flight dynamic model.
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来源期刊
CiteScore
2.70
自引率
7.10%
发文量
195
审稿时长
22 weeks
期刊介绍: International Journal of Aerospace Engineering aims to serve the international aerospace engineering community through dissemination of scientific knowledge on practical engineering and design methodologies pertaining to aircraft and space vehicles. Original unpublished manuscripts are solicited on all areas of aerospace engineering including but not limited to: -Mechanics of materials and structures- Aerodynamics and fluid mechanics- Dynamics and control- Aeroacoustics- Aeroelasticity- Propulsion and combustion- Avionics and systems- Flight simulation and mechanics- Unmanned air vehicles (UAVs). Review articles on any of the above topics are also welcome.
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