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基于NUIO的无人机作动器故障检测
  • ISSN号：1001-5965
  • 期刊名称：北京航空航天大学学报
  • 时间：2015
  • 页码：1300-1306
  • 分类：V448[航空宇航科学与技术—飞行器设计] TP273[自动化与计算机技术—控制科学与工程;自动化与计算机技术—检测技术与自动化装置]
  • 作者机构：[1]北京航空航天大学仪器科学与光电工程学院,北京100191
  • 相关基金：国家自然科学基金（61333005,61174121,61121003）
  • 相关项目：模型不确定线性离散时变系统鲁棒故障检测方法及应用研究
作者： 张鹤|钟麦英|
关键词： 无人机, 故障检测, 容积卡尔曼滤波, 非线性未知输入观测器, χ2检验, unmanned aerial vehicle （UAV） , fault detection, cubature Kalman filter （CKF） , nonlinear unknown input observer （NUIO） , chi-square test
中文摘要：

针对受未知气流干扰与随机噪声影响的无人机纵向系统进行作动器故障检测研究．在建立固定翼式无人机非线性系统纵向模型的基础上，设计了基于容积卡尔曼滤波（CKF）的非线性未知输入观测器（NUIO）．通过构造未知输入观测器结构来解耦未知气流干扰对残差的影响，同时，CKF被算法用于求解观测器增益矩阵，实现了在未知气流干扰解耦情况下残差对随机噪声的鲁棒性．最后，利用残差χ2。检验方法判断故障是否发生．仿真结果表明：此方法能有效解耦未知干扰对残差的影响，并快速、准确地检测出了无人机作动器故障．

英文摘要：

The actuator fault detection for an unmanned aerial vehicle （UAV） longitudinal system with unknown atmospheric disturbances and stochastic noise was studied. Based on introducing a nonlinear longitudinal model of the fixed UAV, a residual generation was designed by employing a nonlinear unknown input observer （NUIO） which is based on cubature Kalman filter （CKF）. The unknown input observer structure was constructed to decouple the unknown disturbances from residual. At the same time, the CKF was applied to calculate the gain matrix to achieve the requirement of robustness to noise. Finally, the occurrence of fault can be detected based on chi-square test about the residual sequence. The simulation results show that the proposed method can decouple the unknown disturbances from residual effectively and achieve the fast and accurate actuator fault detection.

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期刊信息
  • 《北京航空航天大学学报》
  • 北大核心期刊（2011版）
  • 主管单位:
  • 主办单位:北京航空航天大学
  • 主编：赵沁平
  • 地址：北京市海淀区学院路37号
  • 邮编：100083
  • 邮箱：JBUAA@buaa.edu.cn
  • 电话：010-82315594 82338922
  • 国际标准刊号：ISSN：1001-5965
  • 国内统一刊号：ISSN：11-2625/V
  • 邮发代号:
  • 获奖情况:
  • 第二届全国优秀科技期刊评比三等奖,全国优秀高等学校自然科学学报及教育部优秀科技期...
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  • 被引量:19939