Support Vector Machine Observer Based Fault Detection for Reconfigurable Manipulators

被引:0
|
作者
Zhao Bo [1 ]
Dong Bo [1 ]
Li Yuanchun
机构
[1] Jilin Univ, State Key Lab Automobile Dynam Simulat, Changchun 130022, Peoples R China
关键词
Reconfigurable Manipulators; SVM observer; Fault Detection; ROBOT MANIPULATORS; DIAGNOSIS;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A novel fault detection scheme for reconfigurable manipulators actuators based on support vector machine(SVM) observer which has good ability to estimate any functions is proposed to estimate the unknown term and uncertainty term. The reconfigurable manipulators system is fault-free when the error between true value and predict value is less than the given threshold, otherwise, the system is in failure. Then the fuzzy logic systems are proposed for approximating the interconnection term by using adaptive algorithm. Based on Lyapunov stability theorem, the system stability can be verified. And the simulation results illustrate the effectiveness of the proposed fault detection schemes.
引用
收藏
页码:3979 / 3984
页数:6
相关论文
共 50 条
  • [11] Support vector machine for fault detection in transmission line
    Malathi, V.
    Marimuthu, N. S.
    ENGINEERING INTELLIGENT SYSTEMS FOR ELECTRICAL ENGINEERING AND COMMUNICATIONS, 2009, 17 (01): : 13 - 18
  • [12] Fault detection in flotation processes based on deep learning and support vector machine
    Li, Zhong-mei
    Gui, Wei-hua
    Zhu, Jian-yong
    JOURNAL OF CENTRAL SOUTH UNIVERSITY, 2019, 26 (09) : 2504 - 2515
  • [13] Intelligent fault detection and analysis based on support vector machine and applications to Aeroengine
    Ren, Hongquan
    Fan, Quan-Yong
    Song, Xuekui
    Li, Hongxia
    2022 34TH CHINESE CONTROL AND DECISION CONFERENCE, CCDC, 2022, : 2680 - 2685
  • [14] Combination of model-based observer and support vector machines for fault detection of wind turbines
    Laouti N.
    Othman S.
    Alamir M.
    Sheibat-Othman N.
    International Journal of Automation and Computing, 2014, 11 (3) : 274 - 287
  • [15] Combination of Model-based Observer and Support Vector Machines for Fault Detection of Wind Turbines
    Nassim Laouti
    Sami Othman
    Mazen Alamir
    Nida Sheibat-Othman
    International Journal of Automation & Computing, 2014, 11 (03) : 274 - 287
  • [16] A support vector machine framework for fault detection in molecular pump
    Yuan, X. L.
    Kai, J.
    Chen, Y.
    Zuo, G. Z.
    Zhuang, H. D.
    Li, J. H.
    Hu, J. S.
    JOURNAL OF NUCLEAR SCIENCE AND TECHNOLOGY, 2023, 60 (01) : 72 - 82
  • [17] Use of Support Vector Machine to Fault Detection in Biomethanation Process
    Acosta-Pavas, J. C.
    Robles-Rodriguez, C. E.
    Dumas, C.
    Cockx, A.
    Morchain, J.
    Aceves-Lara, C. A.
    19TH INTERNATIONAL SYMPOSIUM ON DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE, 2023, 583 : 176 - 186
  • [18] Fault classification and ground detection using support vector machine
    Samantaray, S. R.
    Dash, P. K.
    Panda, G.
    TENCON 2006 - 2006 IEEE REGION 10 CONFERENCE, VOLS 1-4, 2006, : 2049 - +
  • [19] Fault diagnosis based on support vector machine ensemble
    Li, Y
    Cai, YZ
    Yin, RP
    Xu, XM
    PROCEEDINGS OF 2005 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-9, 2005, : 3309 - 3314
  • [20] Transformer Fault Diagnosis Based on Support Vector Machine
    Zhang, Yan
    Zhang, Bide
    Yuan, Yuchun
    Pei, Zichun
    Wang, Yan
    PROCEEDINGS OF 2010 3RD IEEE INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND INFORMATION TECHNOLOGY (ICCSIT 2010), VOL 6, 2010, : 405 - 408