Online identification method for morphing vehicles with time-varying aerodynamic parameters

被引：0
|
作者：
Lu, Xinyue [1 ]
Zhang, Pengyu [2 ]
Huo, Wenxia [2 ]
Zhang, Yanxue [2 ]
Wang, Jianying [1 ]
机构：
[1] School of Aeronautics and Astronautics, Sun Yat-Sen University, Guangzhou
[2] Science and Technology on Space Physics Laboratory, Beijing
来源：
Harbin Gongcheng Daxue Xuebao/Journal of Harbin Engineering University | 2024年 / 45卷 / 08期
关键词：
aerodynamic parameter identification; fast time-varying aerodynamic parameters; intelligent identification; Kalman filter; morphing vehicle; neural network; nonlinear dynamic model; online identification;
D O I：
10.11990/jheu.202205069
中图分类号：
学科分类号：
摘要：
Owing to environmental variations and shape changes during actual flight, the complex aerodynamic characteristics of morphing vehicles are time-varying and highly nonlinear. This paper proposes an online identification method based on a BP neural network model to obtain the time-varying aerodynamic parameters of morphing vehicles with high precision. First, a BP neural network model was established to approximate the aerodynamic model within a certain precision range based on the nonlinear relationship between input and output. Then, the neural network was trained online using the extended Kalman filter method with observed data from actual aerodynamic parameter tests. The BP neural network model could quickly calculate and predict the aerodynamic parameters after real-time correction and obtaining the neural network parameters. This enabled the tracking of changes in the rapidly time-varying and nonlinear aerodynamic model. Finally, a mathematical simulation was conducted to identify the aerodynamic parameters of a morphing air vehicle during successive deformation / structure mutation. The results verified that the proposed method has a fast convergence speed and high accuracy, demonstrating its effectiveness in identifying the aerodynamic parameters of morphing vehicles. © 2024 Editorial Board of Journal of Harbin Engineering. All rights reserved.
引用
收藏
页码：1520 / 1526
页数：6
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