采用自适应神经网络观测器的旋翼无人机容错控制  

Fault-Tolerant Control for Rotor UAV Based on Adaptive Neural Network Observer

作　　者：张启亚 刘婷婷 宋家友[2] ZHANG Qiya;LIU Tingting;SONG Jiayou(School of Electronic Information Engineering Sias University,Zhengzhou 451000 China;School of Information Engineering Zhengzhou University,Zhengzhou 450000 China)

机构地区：[1]郑州西亚斯学院电子信息工程学院,郑州451000 [2]郑州大学信息工程学院,郑州450000

出　　处：《电光与控制》2023年第1期29-34,共6页Electronics Optics & Control

基　　金：河南省科技攻关项目(212102210150);西亚斯学院校级项目(2019-YB-42)。

摘　　要：针对共轴多旋翼无人机中容易出现电机故障和复合干扰的问题,采用自适应神经网络观测器设计了容错控制算法。首先,建立了包含电机故障和复合干扰的共轴八旋翼无人机运动模型;然后,通过神经网络来逼近复合干扰,并利用自适应律估计故障因子,设计了自适应神经网络观测器对系统状态进行估计;最后,针对姿态角回路和角速度回路设计了反步容错控制律,并利用滤波器对虚拟指令信号进行滤波,抑制了微分爆炸现象,实现了共轴八旋翼UAV的渐近稳定。实验结果表明:所提方法与自适应容错控制方法相比表现出了更优的稳定性和准确性,最大跟踪误差仅为0.1°,有效补偿了复合干扰和旋翼电机故障的影响,提升了无人机的飞行稳定性和容错性能。Aiming at the problems of motor failure and composite disturbance in coaxial multi-rotor UAV,a fault-tolerant control algorithm is designed by using adaptive neural network observer.Firstly,the motion model of the coaxial eight-rotor UAV including motor fault and composite disturbance is established,then the composite disturbance is approached by neural network and the fault factor is estimated by adaptive law,and the adaptive neural network observer is designed to estimate the system state.Finally,the backstepping fault-tolerant control law is designed for the attitude angle loop and angular velocity loop, and a filter is adopted to filter the virtual command signal,which suppresses the differential explosion and realizes the gradual stability of the UAV.The experimental results show that the proposed method has better stability and accuracy compared with the adaptive fault-tolerant control method,and the maximum tracking error is only 0.1°,which effectively compensates for the influence of composite interference and rotor motor fault, and improves the flight stability and fault-tolerant performance of the UAV.

关 键 词：共轴八旋翼无人机 电机故障 复合干扰 自适应神经网络观测器 容错控制 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]