@inproceedings{303c27fc82194bdc94a774814e1b2991,
title = "Adaptive Flight Control Design for Fixed-wing UAV based on Neural Network",
abstract = "This paper presents an adaptive flight control approach based on dynamic inversion and neural network with sliding mode technique for a fixed-wing unmanned aerial vehicle (UAV). A nonlinear dynamic model which has been decoupled into three independent single-input single-output channels is investigated. Unknown certainties of the aircraft dynamic are estimated by the neural network, which adaptively provides online parameter regulation, and the close stability analysis is also derived by using Lyapunov theory. Simulation and experiment results indicate that the proposed control scheme can perform well in tracking problem.",
keywords = "Adaptive control, Fixed-wing UAV, Neural network, Trajectory tracking",
author = "Jinhua Liu and Xiaoli Wang and Peiqi Zhao",
note = "Publisher Copyright: {\textcopyright} 2022 Technical Committee on Control Theory, Chinese Association of Automation.; 41st Chinese Control Conference, CCC 2022 ; Conference date: 25-07-2022 Through 27-07-2022",
year = "2022",
doi = "10.23919/CCC55666.2022.9902299",
language = "英语",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "2363--2368",
editor = "Zhijun Li and Jian Sun",
booktitle = "Proceedings of the 41st Chinese Control Conference, CCC 2022",
address = "美国",
}