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Fuzzy fault detection of conic-type nonlinear systems within the finite frequency domain

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  • Wang, Jiancheng
  • He, Shuping
  • Luan, Xiaoli
  • Liu, Fei

Abstract

In this paper, we focused on the issue of fault detection subject to a class of conic-type nonlinear systems in the finite frequency domain (FFD). Applying Takagi Sugeno (T-S) fuzzy models, the conic-type dynamic error system is established. To prove that the residual vector is robust to external disturbances and sensitive to faults, we provide some conditions to realize H− fault sensitivity performance and H∞ disturbance attenuation performance within the FFD. Then, utilizing linear matrix inequalities techniques, the fuzzy fault detection observer design problem is transformed into an optimization algorithm. Finally, a numerical example related to a tunnel diode-circuit is given to confirm the validity of the designed scheme.

Suggested Citation

  • Wang, Jiancheng & He, Shuping & Luan, Xiaoli & Liu, Fei, 2020. "Fuzzy fault detection of conic-type nonlinear systems within the finite frequency domain," Applied Mathematics and Computation, Elsevier, vol. 378(C).
    • Handle: RePEc:eee:apmaco:v:378:y:2020:i:c:s0096300320301508
    DOI: 10.1016/j.amc.2020.125181
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    References listed on IDEAS

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    1. Du, Dongsheng, 2017. "Fault detection for discrete-time linear systems based on descriptor observer approach," Applied Mathematics and Computation, Elsevier, vol. 293(C), pages 575-585.
    2. Chang, Xiao-Heng & Xiong, Jun & Park, Ju H., 2016. "Fuzzy robust dynamic output feedback control of nonlinear systems with linear fractional parametric uncertainties," Applied Mathematics and Computation, Elsevier, vol. 291(C), pages 213-225.
    3. Yingqi Zhang & Yan Shi & Xiaowu Mu & Caixia Liu, 2017. "control for conic non-linear jump systems with partially unknown transition probabilities," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(14), pages 2976-2984, October.
    4. Qiang Liu & Hao Zhang & Jiewu Leng & Xin Chen, 2019. "Digital twin-driven rapid individualised designing of automated flow-shop manufacturing system," International Journal of Production Research, Taylor & Francis Journals, vol. 57(12), pages 3903-3919, June.
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