@inproceedings{ca6c86118a594d2eb4835c24d2efb460,
title = "Adaptive Neural Network Zeta-Backstepping Control for Quadrotor UAVs with Prescribed Damping Characteristics",
abstract = "This paper investigates a damping-oriented adaptive tracking scheme for quadrotor attitude channels in the presence of uncertain nonlinear dynamics and external disturbances. A radial basis function neural network is employed to approximate the lumped unknown term in the attitude channel. Different from conventional backstepping where control gains are commonly tuned empirically, a zeta-backstepping mechanism is adopted to shape the dominant transient response through explicit parameter-selection rules, so that the closed-loop damping ratio can be prescribed by relating the error dynamics to a standard second-order model. A Lyapunov-based analysis is developed to guarantee practical stability of the tracking errors. Simulation results on the pitch and yaw channels demonstrate accurate tracking under disturbances while providing flexible regulation of the damping characteristics.",
keywords = "Adaptive tracking, damping ratio, neural network, quadrotor attitude channels, zeta-backstepping control",
author = "Jian Wang and Jiaxing Yang and Xiaolong Zheng and Xuebo Yang",
note = "Publisher Copyright: {\textcopyright} 2026 IEEE.; 38th Chinese Control and Decision Conference, CCDC 2026 ; Conference date: 15-05-2026 Through 18-05-2026",
year = "2026",
doi = "10.1109/CCDC69976.2026.11559868",
language = "英语",
series = "38th Chinese Control and Decision Conference, CCDC 2026",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "6082--6087",
booktitle = "38th Chinese Control and Decision Conference, CCDC 2026",
address = "美国",
}