航空学报 > 2020, Vol. 41 Issue (4): 323534-323534   doi: 10.7527/S1000-6893.2019.23534

基于角加速度估计的非线性增量动态逆控制及试飞

党小为1, 唐鹏2, 孙洪强2, 郑琛1   

  1. 1. 北京航空航天大学 能源与动力工程学院, 北京 100083;
    2. 北京航空航天大学 交通科学与工程学院, 北京 100083
  • 收稿日期:2019-09-29 修回日期:2020-01-10 出版日期:2020-04-15 发布日期:2020-01-10
  • 通讯作者: 唐鹏 E-mail:tangpeng@buaa.edu.cn

Incremental nonlinear dynamic inversion control and flight test based on angular acceleration estimation

DANG Xiaowei1, TANG Peng2, SUN Hongqiang2, ZHENG Chen1   

  1. 1. School of Energy and Power Engineering, Beihang University, Beijing 100083, China;
    2. School of Transportations Science and Engineering, Beihang University, Beijing 100083, China
  • Received:2019-09-29 Revised:2020-01-10 Online:2020-04-15 Published:2020-01-10

摘要: 针对非线性增量动态逆(INDI)控制方法运用到飞行试验时需要进行状态量导数(角加速度)的实时估计并且存在延迟等问题进行了研究,并给出了工程应用上的实际解决方案。对试飞无人机(UAV)平台进行了动力学建模,利用非线性增量动态逆控制方法和控制器分层设计方法设计了无人机姿态控制系统。采用卡尔曼滤波器设计了角加速度估计器为控制律提供角加速度实时反馈。通过基于模型的控制系统设计方法将控制律实现,并进行实际试飞试验。结果表明:该控制方法工程上可实现,具备良好的鲁棒性和指令跟踪能力。

关键词: 飞行控制, 非线性增量动态逆, 角加速度估计, 卡尔曼滤波, 基于模型设计

Abstract: The Incremental Nonlinear Dynamic Inversion (INDI) control law requires estimation of state derivative (angular acceleration) for real-time feedback and exists time delay caused by angular acceleration estimation, This paper proposes research and practical engineering solutions to the above problems. The dynamic model of the flight test Unmanned Aerial Vehicle (UAV) platform was established. The incremental nonlinear dynamic inversion control law and the controller layered design method were used to design the UAV attitude control system. Using Kalman filter, the angular acceleration estimator is designed to provide real-time feedback of angular acceleration for the control law. The control law is implemented by a model-based control system design method, and the actual flight test is performed. The test results show that the control method is achievable in engineering and show good robustness and command tracking capability.

Key words: flight control, incremental nonlinear dynamic inversion, angular acceleration estimation, Kalman filter, model-based design

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