A Quantitative Method for the Fault Diagnosability of Affine Nonlinear System

被引:3
|
作者
Hu, Xiaoqiang [1 ]
Luo, Shifan [1 ]
Xu, Dongsheng [2 ]
Wan, Binhao [3 ]
机构
[1] Wenzhou Univ, Coll Elect & Elect Engn, Wenzhou 325035, Peoples R China
[2] Xiamen Univ, Sch Aeronaut & Astronaut, Xiamen 361005, Peoples R China
[3] Peoples Liberat Army PLA, Unit 31121, Xiamen 361005, Peoples R China
来源
2022 34TH CHINESE CONTROL AND DECISION CONFERENCE, CCDC | 2022年
关键词
Fault Diagnosability; Affine Nonlinear Systems; Differential Geometry; Quantification Indexes; DETECTABILITY;
D O I
10.1109/CCDC55256.2022.10034199
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The fault diagnosability can guide the construction of diagnosis system and thereby influence the reliability of control system. But it is hard to evaluated the fault diagnosability of affine nonlinear system by using linear system theory, especially when the system noise is taken into consider. Base on the differential geometry theory, an evaluation method is proposed to quantitate the fault diagnosability of affine nonlinear system. Firstly, a qualitative judgment method for fault detectability and isolability is introduced for single fault system. Secondly, a series of quantitative indexes are designed to evaluate the complexity of fault detectability and isolability through system outputs, measuring the influence of the distribution similarity, the fault amplitude and the system states. Lastly, a validation example is presented to demonstrate the effectiveness of the proposed method.
引用
收藏
页码:5974 / 5979
页数:6
相关论文
共 50 条
  • [1] Fault diagnosability quantitative evaluation and method of fault diagnosis for nonlinear system
    Jiang D.
    Li W.
    Wang J.
    Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition), 2016, 44 (12): : 102 - 108
  • [2] Evaluation Methods for Fault Diagnosability of Affine Nonlinear System
    Huang Yonglong
    Liu Chengrui
    Zhong Xunyu
    2015 34TH CHINESE CONTROL CONFERENCE (CCC), 2015, : 6336 - 6339
  • [3] A Fault Diagnosability Evaluation Method for A Class of Affine Nonlinear Systems Considering Sensor Faults
    Qin, Yufeng
    Shi, Xianjun
    Long, Yufeng
    Lv, Jiapeng
    Zhang, Zhilong
    Zhao, Li
    PROCEEDINGS OF THE 33RD CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2021), 2021, : 6608 - 6613
  • [4] Methods for Fault Diagnosability Analysis of a Class of Affine Nonlinear Systems
    Peng, Xiafu
    Lin, Lixiong
    Zhong, Xunyu
    Liu, Chengrui
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2015, 2015
  • [5] An approach to fault diagnosability quantitative evaluation for a class of nonlinear systems
    Li, Wen-Bo
    Wang, Da-Yi
    Liu, Cheng-Rui
    Yuhang Xuebao/Journal of Astronautics, 2015, 36 (04): : 455 - 462
  • [6] A Data Driven Method for Quantitative Fault Diagnosability Evaluation
    Hua, Yongzhao
    Li, Qingdong
    Ren, Zhang
    Liu, Chengrui
    PROCEEDINGS OF THE 28TH CHINESE CONTROL AND DECISION CONFERENCE (2016 CCDC), 2016, : 1890 - 1894
  • [7] A method for fault diagnosability evaluation of spacecraft control system
    Yin, Chen
    He, Zhangming
    Wang, Jiongqi
    Zhou, Haiyin
    PROCEEDINGS OF THE 2016 JOINT INTERNATIONAL INFORMATION TECHNOLOGY, MECHANICAL AND ELECTRONIC ENGINEERING, 2016, 59 : 611 - 614
  • [8] Evaluation and design of actuator fault diagnosability for nonlinear affine uncertain systems with unknown indeterminate inputs
    Xing, Zirui
    Xia, Yuanqing
    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, 2017, 31 (01) : 122 - 137
  • [9] Quantitative Stochastic Fault Diagnosability Analysis
    Eriksson, Daniel
    Krysander, Mattias
    Frisk, Erik
    2011 50TH IEEE CONFERENCE ON DECISION AND CONTROL AND EUROPEAN CONTROL CONFERENCE (CDC-ECC), 2011, : 1563 - 1569
  • [10] A method for quantitative fault diagnosability analysis of stochastic linear descriptor models
    Eriksson, Daniel
    Frisk, Erik
    Krysander, Mattias
    AUTOMATICA, 2013, 49 (06) : 1591 - 1600