Open AccessFault Detection of UAV Fault Based on a SFUKF
Author(s) -
Wang Zhong,
Xin Chen
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/563/5/052099
Subject(s) - robustness (evolution) , fault detection and isolation , airspeed , kalman filter , control theory (sociology) , actuator , computer science , nonlinear system , elevator , engineering , control engineering , control (management) , artificial intelligence , biochemistry , chemistry , physics , structural engineering , quantum mechanics , gene , aerospace engineering
The UAV system is a typical closed-loop control system. Its good robustness can inhibit the fault signal, which poses certain difficulties for the detection of early or small amplitude faults. In this paper, a nonlinear longitudinal control system model of a class of UAVs is established, and a fault detection method based on the suboptimal fading unscented Kalman filter (SFUKF) is designed. Aiming at the common failure of actuators and sensors of the drone, this paper proves that the method realizes the fault detection of the airspeed tube blockage and the elevator part failure by simulation.