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悬停状态下小型无人直升机飞行动力学模型辨识

武梅丽文 陈铭 王放

武梅丽文, 陈铭, 王放等 . 悬停状态下小型无人直升机飞行动力学模型辨识[J]. 北京航空航天大学学报, 2019, 45(3): 546-559. doi: 10.13700/j.bh.1001-5965.2018.0384
引用本文: 武梅丽文, 陈铭, 王放等 . 悬停状态下小型无人直升机飞行动力学模型辨识[J]. 北京航空航天大学学报, 2019, 45(3): 546-559. doi: 10.13700/j.bh.1001-5965.2018.0384
WU Meiliwen, CHEN Ming, WANG Fanget al. Identification of flight dynamics models of a small-scale unmanned helicopter in hover condition[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(3): 546-559. doi: 10.13700/j.bh.1001-5965.2018.0384(in Chinese)
Citation: WU Meiliwen, CHEN Ming, WANG Fanget al. Identification of flight dynamics models of a small-scale unmanned helicopter in hover condition[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(3): 546-559. doi: 10.13700/j.bh.1001-5965.2018.0384(in Chinese)

悬停状态下小型无人直升机飞行动力学模型辨识

doi: 10.13700/j.bh.1001-5965.2018.0384
详细信息
    作者简介:

    武梅丽文, 女, 博士研究生。主要研究方向:飞行动力学与控制

    陈铭, 男, 博士, 教授, 博士生导师。主要研究方向:直升机总体设计、直升机飞行动力学等

    通讯作者:

    陈铭, E-mail:chenming@buaa.edu.cn

  • 中图分类号: V212.4

Identification of flight dynamics models of a small-scale unmanned helicopter in hover condition

More Information
  • 摘要:

    为了更好地研究小型无人直升机悬停状态动力学特性,对一个8.1 kg三轴陀螺仪增稳的电动直升机,从线性系统辨识方面及非线性建模方面,进行了动力学模型深入研究。在线性系统辨识过程中,应用频域辨识方法,在飞行中同时采集陀螺仪之前及之后的操纵数据进行双系统辨识。在非线性建模过程中,机体、旋翼及尾桨动力学被分别建模。尾桨动力学应用3阶段辨识法单独提取基底、陀螺仪及整体增稳模型。结合2种分析过程,应用非线性-线性模型结合修正方法,提高相互的仿真精度。结果表明:13阶高阶模型在线性辨识过程中相对比11阶模型表现更优;双系统线性模型的基底模型数据具有高质量高频特性,最高频率限制可达30 rad/s;除挥舞方程参数和尾桨参数以外,非线性数学模型(NMM)进行了7个非线性变量的修正,有效地拟合了悬停实验数据。

     

  • 图 1  JR700直升机系统

    Figure 1.  JR700 helicopter system

    图 2  尾桨动力学结构

    Figure 2.  Tail rotor dynamics configuration

    图 3  信号系统示意图

    Figure 3.  Signal system illustration

    图 4  Model A 13阶高阶模型频域辨识结果与悬停实验数据对比

    Figure 4.  Comparison of frequency-domain identification results of 13-state high-order model with experimental hover data for Model A

    图 5  Model B 13阶高阶模型频域辨识结果与悬停实验数据对比

    Figure 5.  Comparison of frequency-domain identification results of 13-state high-order model with experimental hover data for Model B

    图 6  Model A 13阶高阶模型时域仿真结果与悬停实验数据对比

    Figure 6.  Comparison of time-domain simulation results of 13-state high-order model with experimental hover data for Model A

    图 7  Model B 13阶高阶模型时域仿真结果与悬停实验数据对比

    Figure 7.  Comparison of time-domain simulation results of 13-state high-order model with experimental hover data for Model B

    表  1  JR700与3种小型无人直升机结构参数对比

    Table  1.   JR700 structural parameters compared with three kinds of small-scale unmanned helicopters

    参数 JR700 Raptor 50[8] X-cell[3] HeLion[7]
    质量/kg 8.1 4.8 8.15 9.75
    旋翼实度 0.052 0.05 0.05 0.055
    桨叶转动惯量/(kg·m2) 0.04 0.035 0.02 0.055
    主旋翼直径/cm 153.4 134.37 152.4 141
    旋翼转速/(rad·s-1) 178 191 167 193.73
    下载: 导出CSV

    表  2  JR700悬停纵横向耦合模型辨识结果

    Table  2.   Identified results of coupled roll-pitch model for JR700 in hover condition

    参数 Model A Model B
    数值 CR(Cramer-Rao)/% 敏感度/% 数值 CR(Cramer-Rao)/% 敏感度/%
    τf 0.078 41 10.01 0.895 9 0.055 95 8.32 1.066
    Ma 195.10 11.54 2.248 440.4 6.59 2.656
    Lb 224.12 20.05 2.010 740.2 5.765 2.521
    Ba 0.275 6 10.44 2.241 0.252 2 17.47 8.066
    Ab 0.275 6 0.252 2
    Aδlat 0.034 64 11.88 2.444 0.083 12 9.017 2.165
    Aδlon 0.386 3 8.710 1.693 0.446 2 8.122 1.962
    Bδlat 0.407 4 9.563 1.538 0.508 9 7.983 1.859
    Bδlon -0.042 43 14.75 3.415 -0.093 63 9.941 2.373
    价值函数 107.092 29.686 5
    下载: 导出CSV

    表  3  13阶IDM悬停辨识参数

    Table  3.   Identified parameters in 13-state IDM in hover condition

    参数 Model A Model B
    数值 CR/% 敏感度/% 数值 CR/% 敏感度/%
    τf 0.071 30 7.425 0.681 8 0.055 60 8.204 0.856 0
    Xu -0.060 20c -0.060 20c
    Xa -9.8a -9.8a
    Yv -0.142 0c -0.142 0c
    Yb 9.8a 9.8a
    Zw -1.714 12.09 5.473 -1.714 12.67 5.795
    Mu 0.037 10a 0.045 80a
    Mv -0.001 62a -0.004 42a
    Ma 191.3 6.422 1.714 448.4 7.465 3.006
    Lu -0.002 21a -0.002 81a
    Lv -0.102 2a -0.158 0a
    Lb 237.2 6.753 1.735 740.9 5.905 2.530
    Nr 0.409 3 19.85 5.892 -1.084 28.2 13.47
    Kxr -403.70 21.23 1.779
    Kxx -20.47 15.36 1.965
    Ba -0.426 6 4.567 1.425 0.208 6 20.03 9.650
    Ab -0.426 6 0.208 6
    Aδlat 0.025 47 7.875 2.553 -0.032 70 24.62 5.610
    Aδlon -0.343 2 6.999 1.430 -0.456 8 7.78 1.78
    Bδlat 0.391 3 7.242 1.094 0.504 6 8.011 1.655
    Bδlon -0.021 31 23.06 7.520 -0.053 30 18.46 4.161
    Zδcol -45.87 4.251 1.925 -45.87 4.253 1.944
    Nδcol -10.58 19.93 9.765 0b
    Nδped 176.01 11.47 1.874 75.28 2.844 3.778
    价值函数 49.098 9 39.907 8
      注:上标a表示理论值;b表示由模型结构考虑移除的参数;c表示单独辨识参数并在模型中固定不变。
    下载: 导出CSV

    表  4  NMM主要修正参数

    Table  4.   Main modified parameters in NMM

    参数 数值
    a0 5.75
    Kcol 0.293 2
    Kβ 160.57
    Ixx 0.396
    Iyy 0.653
    ΔXu -0.041
    ΔYv -0.048 5
    下载: 导出CSV

    表  5  JR700悬停模型与3种小型无人直升机主要参数对比

    Table  5.   JR700 key parameters compared with three kinds of small-scale unmanned helicopter in hover model

    参数 JR700 13阶 Raptor 50 X-cell HeLion
    Model A Model B
    τf 0.071 30 0.055 60 0.043 0.052
    τs+τf 0.127 0.272 0.299
    Lb 237.2 740.9 735.5 320 583.5
    Ma 191.3 448.4 228 204 265.3
    Aδlat 0.025 47 -0.032 70 0.008 9a 0 0
    Aδlon -0.343 2 -0.456 8 -0.242 2a -0.53a -0.42a
    Bδlat 0.391 3 0.504 6 0.031 5a 0.42a 0.4a
    Bδlon -0.021 31 -0.053 30 -0.011 2a 0 0
      注:上标a表示原始数值[3, 7-8]按本文单位标准换算。
    下载: 导出CSV

    表  6  JR700悬停模型主要特征值与模态

    Table  6.   Main eigenvalues and modes of JR700 hover model

    模态 13阶Model A 13阶Model B
    俯仰耦合模态 [0.673 7, 14.666 0] [0.426 1, 21.621 4]
    滚转耦合模态 [0.285 9, 14.593 5] [0.328 8, 26.942 2]
    航向模态 [0.504 5, 19.883 2] (-1.084 0)
    垂向模态 (-1.713 6) (-1.713 6)
    纵向速度模态 [0.257 8, 0.139 7] [0.357 6, 0.192 2]
    横向速度模态 [0.240 8, 0.256 6] [0.239 0, 0.131 9]
    下载: 导出CSV
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出版历程
  • 收稿日期:  2018-06-21
  • 录用日期:  2018-09-19
  • 网络出版日期:  2019-03-20

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