Fault-Tolerant Active Disturbance Rejection Control of Plant Protection of Unmanned Aerial Vehicles Based on a Spatio-Temporal RBF Neural Network

Applied Sciences

Dejie Li¹  Lianghao Hua²  Jianfeng Zhang²  Xiaobo Xi² 

[1] School of Automation, Nanjing University of Aeronautics and Astronautics, 29 Yudao Street, Nanjing 211106, China;School of Mechanical Engineering, Yangzhou University, No. 196 West Huayang Road, Yangzhou 225009, China;

关键词: actuator fault;    active fault-tolerant control;    active disturbance rejection control;    model uncertainty;    RBF neural network;   

DOI  :  10.3390/app11094084

来源: DOAJ

【 摘 要 】

This paper presents a fault-tolerant flight control method for a multi-rotor UAV under actuator failure and external wind disturbances. The control method is based on an active disturbance rejection controller (ADRC) and spatio-temporal radial basis function neural networks, which can be used to achieve the stable control of the system when the parameters of the UAV mathematical model change. Firstly, an active disturbance rejection controller with an optimized parameter design is designed for rthe obust control of a multi-rotor vehicle. Secondly, a spatio-temporal radial basis function neural network with a new adaptive kernel is designed. In addition, the output of the novel radial basis function neural network is used to estimate fusion parameters containing actuator faults and model uncertainties and, consequently, to design an active fault-tolerant controller for a multi-rotor vehicle. Finally, fault injection experiments are carried out with the Qball-X4 quadrotor UAV as a specific research object, and the experimental results show the effectiveness of the proposed self-tolerant, fault-tolerant control method.

【 授权许可】

Unknown