期刊文献+

基于自适应观测器的飞轮故障诊断方法 被引量:1

Reaction wheel fault diagnosis based on adaptive observer
原文传递
导出
摘要 研究了反作用飞轮的故障诊断问题.针对反作用飞轮的非线性数学模型,分析了其故障模式,建立了故障的参数化描述方法,并在此基础上提出了一种基于参数自适应投影的反作用飞轮故障诊断方法,通过构造观测器,利用参数自适应投影算法更新参数信息,以保证观测器稳定及与故障相关的参数收敛到其真值.最后对飞轮的各种故障模式进行了仿真,结果表明提出的方法有效可行. The design of fault diagnosis for reaction wheel(RW) is presented in this paper.First,based on nonlinear RW mathematic model,the failure modes of RW is analyzed and a parameterized description for fault is established.By using an adaptive algorithm with projection,the observer for fault diagnosis of RW is brought forward then.The parameters are updated by the adaptive algorithm,which ensure the observer to be stable and the parameters related to fault converge to the actual value.Finally numerical simulations with the entire failure modes demonstrate that the proposed approach is effective and feasible.
出处 《华中科技大学学报(自然科学版)》 EI CAS CSCD 北大核心 2009年第S1期184-186,193,共4页 Journal of Huazhong University of Science and Technology(Natural Science Edition)
基金 国家自然科学基金资助项目(60874055)
关键词 故障诊断 自适应算法 投影 故障模式 飞轮 fault detection adaptive algorithms projection failure modes wheels
  • 相关文献

参考文献8

  • 1Bialke B.High fidelity mathematical modeling of re-action wheel performance. 21st Annual AmericanAstronautical Society Guidance and Control Confer-ence . 1998
  • 2Jovan D,Raman K.A decentralized scheme for au-tonomous compensation of multiple simultaneousflight-critical failures. AIAA Guidance,Naviga-tion,and Control Conference and Exhibit . 2002
  • 3Jovan D,Joshua R,Raman K.Integrated healthmonitoring and adaptive reconfigurable control. AIAA Guidance,Navigation,and ControlConference and Exhibit . 2007
  • 4Tafazoli M.A study of on-orbit spacecraft failures. Proceeding of the 58th International Astronau-tical Congress . 2007
  • 5Li Z Q,Ma L,Khorasani K.A dynamic neural net-work-based reaction wheel fault diagnosis for satel-lites. Proceeding of International Joint Confer-ence on Neural Networks . 2006
  • 6Li Z Q,Ma L,Khorasani K.Fault diagnosis of anactuator in the attitude control subsystem of a satel-lite using neural networks. Proceeding of Inter-national Joint Conference on Neural Networks . 2007
  • 7Li J,Zhang H Y.Controller reconfiguration againstreaction wheel failure based on predictive filters. Proceeding of 1th International Symposium onSystems a Control in Aerospace and Astronautics . 2006
  • 8Dein I A,Zyoud A,Khorasani K.Detection of actua-tor faults using a dynamic neural network for the atti-tude control subsystem of a satellite. Proceedingof International Joint Conference on Neural Net-works . 2005

同被引文献12

  • 1LI Zhongqi, MA Liying, KHORASANI Khashayar. Fault detection in reaction wheel of a satellite using observer-based dynamic neural networks [ J ]. Lecture Notes in Computer Science, 3498 ( 3 ) : 584 - 590.
  • 2HENRY D. Fault diagnosis of microscope satellite thrusters using H∞/H _ filters[ J ]. Journal of guidance, control, and dynamics, 2008, 31(3): 699-711.
  • 3VALDES A, KHORASANI K. A pulsed plasma thruster fault de- tection and isolation strategy for formation flying of satellites [ J ]. Applied Soft Computing Journal, 2010, 10 ( 3 ) : 746 - 758.
  • 4PIRMORADI F N, SASSANI F, DE SILVA C W. Fault detection and diagnosis in a spacecraft attitude determination system [ J]. Acta Astronautica, 2009,65 ( 5 - 6 ) :710 - 729.
  • 5TIPPING Michael E. Bayesian inference : an introduction to prin- ciples and practice in machine learning [ J ]. Advanced lectures on machine learning, 2006, 3176:1 -19.
  • 6TIPPING Michael E. Sparse bayesian learning and the relevance vector machine [ J ]. Journal of Machine Learning Reaserch, 2001,1 : 211 -244.
  • 7LEI Liangyu, ZHANG Qing. Relevance vector machine based bearing fault diagnosis [ C ]//2006 International Conference on Machine Learning and Cybernetics, August 13 - 16, 2006, Dalian, China. 2006:3492 - 3496.
  • 8王剑非,姜斌,冒泽慧.基于LSSVM的卫星姿态控制系统故障诊断[J].控制工程,2008,15(3):334-336. 被引量:6
  • 9赵石磊,张迎春.SVM回归估计方法在卫星故障诊断中的应用[J].电机与控制学报,2008,12(4):483-486. 被引量:9
  • 10金磊,徐世杰.基于扩张状态观测器的飞轮故障检测与恢复[J].北京航空航天大学学报,2008,34(11):1272-1275. 被引量:11

引证文献1

二级引证文献6

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部