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Event-Driven-Based Fault Detection Filter Design via Membership Functions Iteration Strategy

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Abstract

This paper deals with the issue of adaptive event-driven (AED) fault detection (FD) filter design for discrete-time networked control systems which is modeled by the Takagi–Sugeno (T–S) fuzzy model. First, a new AED scheme is designed to reduce the utilization of limited network resources. Compared with the existing works, the threshold of the AED scheme can be dynamically adjusted in real time by an adaptive law which utilizes the latest released data and the historical released data information. Then, an FD fuzzy filter with mismatched membership functions and AED mechanism is designed, which is used to generate a residual signal and detect system faults. A membership functions iteration strategy is utilized to optimize the membership functions of the FD fuzzy filter in real time, which can achieve better system performance. Furthermore, the sufficient conditions for designing the FD fuzzy filter are obtained in terms of the Lyapunov stability theory. Finally, a simulation example of the tunnel diode circuit system is utilized for proving the effectiveness and showing the advantages of the proposed AED FD strategy. By giving the initial values of relevant parameters, the MATLAB LMI toolbox is used to solve the result experiment.

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Funding

This work was partially supported by the National Natural Science Foundation of China (62003290, 62003052).

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Authors and Affiliations

  1. College of Control Science and Engineering, Bohai University, Jinzhou, 121013, Liaoning, China

    Fan Huang & Yingnan Pan

  2. College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing, 210037, Jiangsu, China

    Qing Lu

  3. School of Mathematics and Statistics, Xinyang Normal University, Xinyang, 464000, Henan, China

    Yanhui Jing

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  1. Fan Huang
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Correspondence to Yingnan Pan.

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Huang, F., Pan, Y., Lu, Q. et al. Event-Driven-Based Fault Detection Filter Design via Membership Functions Iteration Strategy. Int. J. Fuzzy Syst. 25, 2684–2698 (2023). https://doi.org/10.1007/s40815-023-01514-0

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  • DOI: https://doi.org/10.1007/s40815-023-01514-0

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