@inproceedings{82ca27383f324c22bcb64f0670728d48,
title = "Backstepping control for quadrotor with BP neural network based thrust model",
abstract = "This paper presents a nonlinear backstepping control scheme for quadrotor with BP neural network based thrust model. The thrust in quadrotor system is difficult to calculate or measure, so the paper build a BP based thrust model to approximate the mapping between thrust with factors of altitude, voltage and the high level time of PWM. Through the model, the control input for each rotor can be calculate accurately to gain the desired thrust. The controller is designed by backstepping method and verified by Lyapunov stability theorem. Hovering experimental results are presented to show the effectiveness of the proposed controller.",
keywords = "BP nerual network, Thrust model, backstepping, hovering, quadrotor",
author = "Xuerao Wang and Xiaobo Lin and Yao Yu and Qing Wang and Changyin Sun",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 32nd Youth Academic Annual Conference of Chinese Association of Automation, YAC 2017 ; Conference date: 19-05-2017 Through 21-05-2017",
year = "2017",
month = jun,
day = "30",
doi = "10.1109/YAC.2017.7967422",
language = "英语",
series = "Proceedings - 2017 32nd Youth Academic Annual Conference of Chinese Association of Automation, YAC 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "292--297",
booktitle = "Proceedings - 2017 32nd Youth Academic Annual Conference of Chinese Association of Automation, YAC 2017",
}