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山东大学学报(工学版) ›› 2017, Vol. 47 ›› Issue (5): 166-172.doi: 10.6040/j.issn.1672-3961.0.2017.195

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X尾翼无人机的故障诊断和容错控制方法

邓俊武,张玉民*,张红娣,杜晓坤   

  1. 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:2017-02-10 出版日期:2017-10-20 发布日期:2017-02-10
  • 通讯作者: 张玉民(1971— ),男,山东东营人,副教授,硕士生导师,主要研究方向为飞行控制,故障诊断和神经网络等.E-mail: zhyminus@163.com E-mail:dengjw1990@163.com
  • 作者简介:邓俊武(1990— ),男,山西临汾人,硕士研究生,主要研究方向为飞行控制,故障诊断等. E-mail:dengjw1990@163.com
  • 基金资助:
    国家自然科学基金资助项目(61374131,61333005)

Fault diagnosis and fault-tolerant control methods of X-tail UAV

DENG Junwu, ZHANG Yumin*, ZHANG Hongdi, DU Xiaokun   

  1. School of Instrumentation Science and Opto-electronics Engineering, Beihang University, Beijing 100191, China
  • Received:2017-02-10 Online:2017-10-20 Published:2017-02-10

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摘要： 作动器是无人机的关键执行机构,针对作动器卡死、增益损失、偏差等故障问题,采用检测滤波器和卡尔曼滤波相结合的方法进行故障检测和故障参数估计:使用检测滤波器输出带有作动器故障信息的残差向量,并利用阈值检测和残差方向特性检测和隔离故障;在得到故障警报后使用卡尔曼滤波方法对故障参数进行在线估计,得出故障的具体性质和程度;针对不同的故障形式,采用控制命令补偿或重构的方法进行容错控制。 基于X型尾翼无人机的转弯速率模型进行仿真试验,结果验证该方法有效可行,能够实现较快的故障诊断,容错策略可以较好的恢复系统性能。

关键词: 作动器故障, 控制量重构, 检测滤波器, 遗忘因子卡尔曼滤波

Abstract: Actuators are the key agency of the UAV. For fault detection and fault diagnosis purpose of problems such as the dead, gain loss and deviation of the actuator, the fault detection filter and Kalman filter were presented in this contribution. The residual vector with actuator fault information was output by using the detection filter, then the threshold detection and residual direction characteristics were used to detect and isolate the fault. After the fault alarm, the Kalman filter was used to estimate the fault parameters, and the nature and extent of the fault were obtained. According to the different forms of fault, the method of control command compensation or reconstruction was finally used for fault-tolerant control purpose. Based on the turning rate model of the X-tails UAV, simulation test showed that the fault diagnosis method was effective and feasible, which could rapidly obtain the fault information, and the fault-tolerant strategy could well restore the system performance.

Key words: forgetting-factor Kalman filter, control reconstruction, actuator fault, detection filter

中图分类号: 

  • V249.1
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