基于故障发生程度的四旋翼无人机故障诊断  

Fault diagnosis of quadrotor UAV based on fault occurrence degree

作　　者：戴凌宇 程赟 冯张棋 汪小利[1] DAI Lingyu;CHENG Yun;FENG Zhangqi;WANG Xiaoli

机构地区：[1]南通职业大学,江苏南通226000 [2]南通大学电气工程学院,江苏南通226000 [3]江苏大学汽车工程研究院,江苏镇江212000

出　　处：《现代机械》2024年第4期77-83,共7页Modern Machinery

基　　金：南通职业大学2022年校级项目(22ZK09)。

摘　　要：针对四旋翼无人机执行机构的部分失效故障诊断问题,构建了四旋翼无人机的单通道简化系统状态空间模型,分析了传统增强状态Kalman滤波器的算法流程和不足之处,提出了多阶段联合故障观测器对偏差系数以及系统原始状态量进行准确估计。仿真实验表明:多阶段联合故障观测器可以准确估计出不同工况下的故障系数,同时获取系统补偿偏差之后的原始真实状态量,展现了多阶段联合故障观测器在解决四旋翼无人机的故障诊断问题上的优越性。Aiming at the problem of partial failure diagnosis of the actuator of the quadrotor UAV,a single-channel simplified system state space model of the quadrotor UAV is constructed.The algorithm flow and shortcomings of the traditional enhanced state Kalman filter are analyzed,and a multi-stage joint fault observer is proposed to accurately estimate the deviation coefficient and the original state quantity of the system.The simulation results show that the multi-stage joint fault observer can accurately estimate the fault coefficients under different working conditions,and obtain the original real state quantity after the system compensation deviation.It can be seen that the multi-stage joint fault observer has advantages in solving the problem of fault diagnosis of the quadrotor UAV.

关 键 词：四旋翼无人机 故障诊断 多阶段故障联合观测器 KALMAN 

分 类 号：TP1[自动化与计算机技术—控制理论与控制工程]