Fault Detection for Fuzzy Semi-Markov Jump Systems Based on Interval Type-2 Fuzzy Approach

被引:174
|
作者
Zhang, Linchuang [1 ,2 ]
Lam, Hak-Keung [3 ]
Sun, Yonghui [2 ]
Liang, Hongjing [4 ]
机构
[1] Bohai Univ, Coll Informat Sci & Technol, Jinzhou 121013, Peoples R China
[2] Hohai Univ, Coll Energy & Elect Engn, Nanjing 211100, Jiangsu, Peoples R China
[3] Kings Coll London, Dept Informat, London WC2R 2LC, England
[4] Bohai Univ, Coll Engn, Jinzhou 121013, Peoples R China
基金
中国国家自然科学基金;
关键词
Fault detection; fuzzy semi-Markov jump systems (FSM[!text type='JS']JS[!/text]s); interval type-2 (IT2) fuzzy method; sensor saturation; WAVELET-NEURAL-NETWORK; STABILITY ANALYSIS; DESIGN; ALGORITHM; TRACKING; OBSERVER;
D O I
10.1109/TFUZZ.2019.2936333
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This article studies the fault detection problem for continuous-time fuzzy semi-Markov jump systems (FSMJSs) by employing an interval type-2 (IT2) fuzzy approach. First, the continuous-time FSMJSs model is designed and the parameter uncertainty is addressed by the IT2 fuzzy approach, where the characteristic of sensor saturation is taken into account in the control system. Second, the IT2 fuzzy semi-Markov mode-dependent filter is constructed, which is employed to deal with the fault detection problem. Then, by using the Lyapunov theory, it can be guaranteed that the constructed fault detection model based on this filter and IT2 FSMJSs is stochastically stable with H8 performance. Moreover, the quantization strategy is applied to the fault detection plant to dispose of the problem of limited network bandwidth. Compared with the existing literature, the differences mainly lie in two aspects, one is that the IT2 fuzzy method is utilized for FSMJSs to tackle the parameter uncertainty of system, and the other is to detect the fault signal of IT2 FSMJSs by using the fault detection system that is constructed based on the IT2 fuzzy semi-Markovmode-dependent filter and IT2 FSMJSs. Finally, two simulation examples are provided to illustrate the effectiveness and the usefulness of the proposed theoretical method.
引用
下载
收藏
页码:2375 / 2388
页数:14
相关论文
共 50 条
  • [21] Interval type-2 fuzzy hidden Markov models
    Zeng, J
    Liu, ZQ
    2004 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-3, PROCEEDINGS, 2004, : 1123 - 1128
  • [22] Adaptive Event-Triggered Asynchronous Control for Interval Type-2 Fuzzy Markov Jump Systems With Cyberattacks
    Ran, Guangtao
    Li, Chuanjiang
    Sakthivel, Rathinasamy
    Han, Chunsong
    Wang, Bohui
    Liu, Jian
    IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS, 2022, 9 (01): : 88 - 99
  • [23] Interval Type-2 fuzzy voter design for fault tolerant systems
    Linda, Ondrej
    Manic, Milos
    INFORMATION SCIENCES, 2011, 181 (14) : 2933 - 2950
  • [24] Interval Type-2 Fuzzy Markov Chains: Type Reduction
    Figueroa-Garcia, Juan C.
    Kalenatic, Dusko
    Amilcar Lopez, Cesar
    ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS: WITH ASPECTS OF ARTIFICIAL INTELLIGENCE, 2012, 6839 : 211 - +
  • [25] Fuzzy decision making systems based on interval type-2 fuzzy sets
    Chen, Shyi-Ming
    Wang, Cheng-Yi
    INFORMATION SCIENCES, 2013, 242 : 1 - 21
  • [26] Control Synthesis of Fuzzy Semi-Markov Jump Systems With Incomplete Transition Information: A Homogeneous Polynomial-Based Approach
    Shao, Xingchen
    Xie, Xiangpeng
    Rubio, Jose de Jesus
    Wu, Xiaoming
    IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2025, 55 (03) : 1784 - 1793
  • [27] Interval type-2 fuzzy automata and Interval type-2 fuzzy grammar
    S. Sharan
    B. K. Sharma
    Kavikumar Jacob
    Journal of Applied Mathematics and Computing, 2022, 68 : 1505 - 1526
  • [28] Interval type-2 fuzzy automata and Interval type-2 fuzzy grammar
    Sharan, S.
    Sharma, B. K.
    Jacob, Kavikumar
    JOURNAL OF APPLIED MATHEMATICS AND COMPUTING, 2022, 68 (03) : 1505 - 1526
  • [29] A New Fault Estimation Observer Design for Nonlinear Markovian Jump Systems: An Interval Type-2 Fuzzy Method
    Xiaohang Li
    Dunke Lu
    Yanhui Tong
    Haibo Li
    International Journal of Fuzzy Systems, 2023, 25 : 302 - 315
  • [30] A New Fault Estimation Observer Design for Nonlinear Markovian Jump Systems: An Interval Type-2 Fuzzy Method
    Li, Xiaohang
    Lu, Dunke
    Tong, Yanhui
    Li, Haibo
    INTERNATIONAL JOURNAL OF FUZZY SYSTEMS, 2023, 25 (01) : 302 - 315