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基于双频扩张状态观测器的无人机抗扰控制

夏笠城 王姝旸 张晶 杨凌宇

夏笠城,王姝旸,张晶,等. 基于双频扩张状态观测器的无人机抗扰控制[J]. 北京航空航天大学学报,2023,49(5):1201-1208 doi: 10.13700/j.bh.1001-5965.2021.0411
引用本文: 夏笠城,王姝旸,张晶,等. 基于双频扩张状态观测器的无人机抗扰控制[J]. 北京航空航天大学学报,2023,49(5):1201-1208 doi: 10.13700/j.bh.1001-5965.2021.0411
XIA L C,WANG S Y,ZHANG J,et al. Bi-bandwidth extended state observer based disturbance rejection control method and its application on UAV[J]. Journal of Beijing University of Aeronautics and Astronautics,2023,49(5):1201-1208 (in Chinese) doi: 10.13700/j.bh.1001-5965.2021.0411
Citation: XIA L C,WANG S Y,ZHANG J,et al. Bi-bandwidth extended state observer based disturbance rejection control method and its application on UAV[J]. Journal of Beijing University of Aeronautics and Astronautics,2023,49(5):1201-1208 (in Chinese) doi: 10.13700/j.bh.1001-5965.2021.0411

基于双频扩张状态观测器的无人机抗扰控制

doi: 10.13700/j.bh.1001-5965.2021.0411
基金项目: 国家自然科学基金(61273099,61304030)
详细信息
    作者简介:

    夏笠城 男,硕士研究生。主要研究方向:飞行器控制

    杨凌宇 男,博士,副教授,硕士生导师。主要研究方向: 先进飞行器控制,容错控制,先进布局飞机多操纵控制方法

    通讯作者:

    E-mail:yanglingyu@buaa.edu.cn

  • 中图分类号: V249.12

Bi-bandwidth extended state observer based disturbance rejection control method and its application on UAV

Funds: National Natural Science Foundation of China (61273099,61304030)
More Information
  • 摘要:

    针对实际系统中普遍存在的非匹配快变扰动和量测噪声问题,提出了一种基于双频扩张状态观测器(BESO)的反步抗扰控制方法。双频扩张状态观测器通过方向转换因子和双带宽比例因子调整观测器的带宽,在准确估计快变扰动的同时可避免放大量测噪声。在此基础上结合反步控制,形成一种逐级补偿的控制结构,通过Lyapunov方法设计了控制律,可保证系统对非匹配扰动的渐进稳定。针对工程应用,进一步给出了控制器参数调节的建议。将所提控制律应用于微型四旋翼无人机的定高控制,仿真结果验证了其补偿非匹配扰动和抑制量测噪声方面的有效性。

     

  • 图 1  基于BESO的反步控制律

    Figure 1.  Backstepping control based on BESO

    图 2  基于LESO的反步控制律

    Figure 2.  Backstepping control based on LESO

    图 3  ${d_1}$估计结果

    Figure 3.  Estimation results of ${d_1}$

    图 4  ${d_2}$估计结果

    Figure 4.  Estimation results of ${d_2}$

    图 5  未补偿扰动的反步法闭环响应

    Figure 5.  Closed-loop response of backstepping controller without disturbance compensation

    图 6  补偿扰动的反步法闭环响应

    Figure 6.  Closed-loop responses of two backstepping disturbance compensation

    图 7  BESO+反步法实际输入

    Figure 7.  Input of backstepping control based on BESO

    表  1  BESO与LESO估计${d_1}, {d_2}$性能指标

    Table  1.   Performance indexes of BESO and LESO on ${d_1}$

    估计${J_1}$${J_2}$${J_3}$$\dfrac{J_{1{\rm{LESO} } } }{J_{1{\rm{BESO} } } }$/%$\dfrac{J_{2{\rm{LESO} } } }{J_{2{\rm{BESO} } } }$/%$\dfrac{J_{3{\rm{LESO} } } }{J_{3{\rm{BESO} } } }$/%
    BESOLESOBESOLESOBESOLESO
    d10.2100.2410.2330.2560.1630.211114.8109.9129.4
    d20.58830.75890.68930.91800.38660.4410129.0133.2114.1
    下载: 导出CSV

    表  2  BESO与LESO实际输入性能指标

    Table  2.   Performance indexes of BESO and LESO on actual input

    J4$\dfrac{J_{4{\rm{LESO}}}}{J_{4{\rm{BESO}}}} $/%
    BESOLESO
    1.68732.2236131.8
    下载: 导出CSV
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  • 被引次数: 0
出版历程
  • 收稿日期:  2021-07-20
  • 录用日期:  2021-09-30
  • 网络出版日期:  2021-11-20
  • 整期出版日期:  2023-05-31

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