Stochastic Adaptive Control for a Kind of Fixed-Wing UAV with State Constraints

Yu Bai, Sheng Luo, Gonghao Sun, Wenxing Fu, Bo Han

科研成果: 书/报告/会议事项章节会议稿件同行评审

1 引用 (Scopus)

摘要

Fixed-wing unmanned aerial vehicles (UAVs) fly in a complex environment, which leads to multiple uncertainties in the flight control system. Furthermore, nonlinear disturbances are inevitable in the dynamics of fixed-wing UAVs. In this paper, we focus on neural network-based adaptive attitude control for fixed-wing UAVs subjected to stochastic multiple uncertainties and state constraints. In the control scheme, radial basis function neural networks are used to approximate unknown nonlinear uncertainties, which can effectively reduce the adverse impact caused by unknown time-varying disturbances and random uncertainties. All the signals in the closed-loop system are allowed to be semi-globally uniformly ultimately bounded, and the state constraints are guaranteed by establishing a stochastic Lyapunov function. Simulation results show the effectiveness of the proposed control scheme in this paper.

源语言英语
主期刊名Proceedings of the 41st Chinese Control Conference, CCC 2022
编辑Zhijun Li, Jian Sun
出版商IEEE Computer Society
878-883
页数6
ISBN(电子版)9789887581536
DOI
出版状态已出版 - 2022
活动41st Chinese Control Conference, CCC 2022 - Hefei, 中国
期限: 25 7月 202227 7月 2022

出版系列

姓名Chinese Control Conference, CCC
2022-July
ISSN(印刷版)1934-1768
ISSN(电子版)2161-2927

会议

会议41st Chinese Control Conference, CCC 2022
国家/地区中国
Hefei
时期25/07/2227/07/22

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