卫星姿控系统基于模糊基函数网络与自回归模型的故障预测
Fault prognosis in control system for satellite attitudes based on fuzzy basis function networks and autoregression model
摘要点击 1316  全文点击 1357  投稿时间:2010-05-16  修订日期:2010-07-19
查看全文  查看/发表评论  下载PDF阅读器
DOI编号  10.7641/j.issn.1000-8152.2011.4.CCTA100569
  2011,28(4):472-478
中文关键词  故障预测  卫星姿态控制系统  模糊基函数网络  自回归模型  故障发生率  置信因子
英文关键词  fault prognosis  satellite attitude control system  FBFN  AR model  failure probability  confidence factor
基金项目  国家自然科学基金资助项目(61074082); 空间智能控制技术国防科技重点实验室基金资助项目(SIC07030101); 民航科研基金资助项目(MHRD07Z16).
作者单位E-mail
张茂林 北京航空航天大学 自动化科学与电气工程学院  
宋华 北京航空航天大学 自动化科学与电气工程学院
空间智能控制技术国家级重点实验室 
mltrees@163.com 
朱新宇 中国民航飞行学院 航空工程学院  
中文摘要
      针对卫星姿态控制系统的故障预测问题, 给出了模糊基函数网络(FBFN)与自回归模型(AR)相结合的故障预测方法, 并提出了预测置信因子的概念, 对故障预测的准确性进行评价. 首先利用卫星正常运行时的姿态数据训练FBFN, 将训练好的FBFN作为卫星姿控系统的标准输出模型; 然后把卫星实时姿态数据与FBFN输出数据之间的差值作为残差, 利用AR模型对残差序列进行建模, 进而对未来的残差进行预测; 最后依据预测残差的统计分布给出了故障发生概率, 利用故障预测置信因子来描述预测步长不同时故障预测结果的可信性.
英文摘要
      A new method based on fuzzy basis function networks(FBFN) and autoregression(AR) model is proposed for predicting faults in the control system for satellite attitudes. Firstly, normal satellite attitude data are used to train FBFN which is used as the standard model of the control system for satellite attitudes. Secondly, the real-time attitude residual errors are obtained by subtracting the FBFN output from the real-time data of satellite attitudes. Thirdly, the time series of the residual errors is used to build an AR model. Therefore, the faults in the control system for satellite attitudes are predicted by using the AR model, and the failure probability is given according to the statistical distribution of the prediction errors of the AR model. Finally, the confidence factor is determined which shows the confidence measure of the fault prognosis.