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Fault detection for uncertain nonlinear systems via recursive observer and tight threshold

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  • Zhang, Zhi-Hui
  • Hao, Li-Ying
  • Guo, Mingjie

Abstract

This paper presents an fault detection (FD) method for a class of uncertain nonlinear systems with unmatched nonlinear fault functions and disturbances. A recursive FD observer is designed with predetermined and small output estimation error. The nonlinear observer gain function is achieved by introducing predetermined output estimation accuracy-dependent nonnegative functions. Combining Lyapunov functions, it is shown that the absolute value of the residual signal is equal or lesser than tight threshold before fault occurrence. The FD scheme is proposed following fault detectability analysis, simulation example indicates the validity of the proposed method.

Suggested Citation

  • Zhang, Zhi-Hui & Hao, Li-Ying & Guo, Mingjie, 2022. "Fault detection for uncertain nonlinear systems via recursive observer and tight threshold," Applied Mathematics and Computation, Elsevier, vol. 414(C).
    • Handle: RePEc:eee:apmaco:v:414:y:2022:i:c:s0096300321007499
    DOI: 10.1016/j.amc.2021.126665
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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. Zhao, Nan-Nan & Wu, Li-Bing & Ouyang, Xin-Yu & Yan, Yan & Zhang, Rui-Yan, 2019. "Finite-time adaptive fuzzy tracking control for nonlinear systems with disturbances and dead-zone nonlinearities," Applied Mathematics and Computation, Elsevier, vol. 362(C), pages 1-1.
    3. Li, Jian & Guo, Xinxin & Chen, Cong & Su, Qingyu, 2019. "Robust fault diagnosis for switched systems based on sliding mode observer," Applied Mathematics and Computation, Elsevier, vol. 341(C), pages 193-203.
    4. Sun, Shaoxin & Wang, Yingchun & Zhang, Huaguang & Sun, Jiayue, 2020. "Multiple intermittent fault estimation and tolerant control for switched T-S fuzzy stochastic systems with multiple time-varying delays," Applied Mathematics and Computation, Elsevier, vol. 377(C).
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    Cited by:

    1. Gao, Ming & Niu, Yichun & Sheng, Li & Zhou, Donghua, 2022. "Quantitative analysis of incipient fault detectability for time-varying stochastic systems based on weighted moving average approach," Applied Mathematics and Computation, Elsevier, vol. 434(C).

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