基于EKF的无人机飞行控制系统故障检测

上海交通大学学报（自然版） ›› 2015, Vol. 49 ›› Issue (06): 884-888.

• 自动化技术、计算机技术 • 上一篇下一篇

基于EKF的无人机飞行控制系统故障检测

刘晓东，钟麦英，柳海

（北京航空航天大学仪器科学与光电工程学院，北京 100191）

收稿日期:2015-03-15
基金资助:
国家自然科学基金项目（61333005,61174121）资助

EKF-Based Fault Detection of Unmanned Aerial Vehicle Flight Control System

LIU Xiaodong,ZHONG Maiying,LIU Hai

(School of Instrumentation Science and OptoElectronics Engineering, Beihang University, Beijing 100191, China)

Received:2015-03-15

摘要/Abstract

摘要：

摘要：无人机飞行控制系统是一种典型的多传感器闭环控制系统，其执行机构与传感器故障会严重影响系统的安全性与可靠性，针对无人机飞行控制系统故障检测问题的研究具有重要的意义.本文考虑了一类无人机闭环非线性飞行控制系统的故障检测问题，针对风扰动影响下无人机纵向非线性系统模型，设计基于扩展卡尔曼滤波器的残差产生器，并应用χ2检验对残差进行评价，实现无人机闭环控制系统的故障检测.同时，基于某型无人机Simulink仿真平台进行仿真实验.结果表明,所提出的方法能够实现空速管堵塞故障和升降舵部分失效故障的检测.
关键词：无人机；飞行控制系统；扩展卡尔曼滤波；故障检测
中图分类号： TP 206文献标志码： A

Abstract:

Abstract： The unmanned aerial vehicle (UAV) flight control system is a typical multisensor closedloop system. Since actuator faults and sensor faults could seriously affect the security and reliability of the system, fault detection of the UAV flight control system is of great significance. This paper deals with the problem of fault detection of the closed-loop nonlinear model of the UAV flight control system. The nonlinear model of longitudinal motion of the UAV in the presence of wind disturbance was introduced. The extended Kalman filter (EKF) was utilized for the residual generation. The Chisquare test was selected for the residual evaluation and the fault detection task for UAV closedloop system was accomplished. Finally, based on the simulink platform of a certain type of UAV, simulation results are provided to illustrate the effectiveness of the approach proposed in the case of pitut fault and elevator fault.

Key words: unmanned aerial vehicle (UAV), flight control system, extended Kalman filter (EKF), fault detection

刘晓东，钟麦英，柳海. 基于EKF的无人机飞行控制系统故障检测[J]. 上海交通大学学报（自然版）, 2015, 49(06): 884-888.

LIU Xiaodong,ZHONG Maiying,LIU Hai. EKF-Based Fault Detection of Unmanned Aerial Vehicle Flight Control System[J]. Journal of Shanghai Jiaotong University, 2015, 49(06): 884-888.

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