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Finite‐time and fixed‐time stability of discontinuous fuzzy neural network system with time‐varying delay.

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Title: Finite‐time and fixed‐time stability of discontinuous fuzzy neural network system with time‐varying delay.
Authors: Zhang, Lingling1 (AUTHOR), Huang, Lihong1 (AUTHOR) z002005@163.com, Cai, Zuowei2 (AUTHOR)
Source: Asian Journal of Control. Nov2025, Vol. 27 Issue 6, p2857-2867. 11p.
Subjects: Fuzzy neural networks, Feedback control system stability, Time delay systems, Mathematical analysis, Lyapunov functions, State feedback (Feedback control systems), Dynamic stability
Abstract: This paper is concerned with the problem of generalized finite‐time/fixed‐time stabilization control for a class of fuzzy neural networks system with time‐varying delay and discontinuous activation. Firstly, considering the time delay and fuzzy logics, a discontinuous fuzzy neural networks system with time‐varying delay is formulated. Secondly, by introducing the finite‐time/fixed‐time stability lemmas, two switching state feedback control laws are designed, and a generalized framework of finite‐time/fixed‐time stabilization control for the discontinuous fuzzy neural networks system is presented. By relaxing the conditions of the Lyapunov function, the finite‐time/fixed‐time stabilization of the fuzzy neural networks system is proved by using inequality techniques. A more accurate settling time can be estimated by some special functions. Finally, the effectiveness of the developed method is verified by two typical numerical examples. [ABSTRACT FROM AUTHOR]
Copyright of Asian Journal of Control is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Label: Title
  Group: Ti
  Data: Finite‐time and fixed‐time stability of discontinuous fuzzy neural network system with time‐varying delay.
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  Data: <searchLink fieldCode="AR" term="%22Zhang%2C+Lingling%22">Zhang, Lingling</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Huang%2C+Lihong%22">Huang, Lihong</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> z002005@163.com</i><br /><searchLink fieldCode="AR" term="%22Cai%2C+Zuowei%22">Cai, Zuowei</searchLink><relatesTo>2</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Asian+Journal+of+Control%22">Asian Journal of Control</searchLink>. Nov2025, Vol. 27 Issue 6, p2857-2867. 11p.
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  Label: Subjects
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  Data: <searchLink fieldCode="DE" term="%22Fuzzy+neural+networks%22">Fuzzy neural networks</searchLink><br /><searchLink fieldCode="DE" term="%22Feedback+control+system+stability%22">Feedback control system stability</searchLink><br /><searchLink fieldCode="DE" term="%22Time+delay+systems%22">Time delay systems</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+analysis%22">Mathematical analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Lyapunov+functions%22">Lyapunov functions</searchLink><br /><searchLink fieldCode="DE" term="%22State+feedback+%28Feedback+control+systems%29%22">State feedback (Feedback control systems)</searchLink><br /><searchLink fieldCode="DE" term="%22Dynamic+stability%22">Dynamic stability</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This paper is concerned with the problem of generalized finite‐time/fixed‐time stabilization control for a class of fuzzy neural networks system with time‐varying delay and discontinuous activation. Firstly, considering the time delay and fuzzy logics, a discontinuous fuzzy neural networks system with time‐varying delay is formulated. Secondly, by introducing the finite‐time/fixed‐time stability lemmas, two switching state feedback control laws are designed, and a generalized framework of finite‐time/fixed‐time stabilization control for the discontinuous fuzzy neural networks system is presented. By relaxing the conditions of the Lyapunov function, the finite‐time/fixed‐time stabilization of the fuzzy neural networks system is proved by using inequality techniques. A more accurate settling time can be estimated by some special functions. Finally, the effectiveness of the developed method is verified by two typical numerical examples. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Asian Journal of Control is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1002/asjc.3630
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 11
        StartPage: 2857
    Subjects:
      – SubjectFull: Fuzzy neural networks
        Type: general
      – SubjectFull: Feedback control system stability
        Type: general
      – SubjectFull: Time delay systems
        Type: general
      – SubjectFull: Mathematical analysis
        Type: general
      – SubjectFull: Lyapunov functions
        Type: general
      – SubjectFull: State feedback (Feedback control systems)
        Type: general
      – SubjectFull: Dynamic stability
        Type: general
    Titles:
      – TitleFull: Finite‐time and fixed‐time stability of discontinuous fuzzy neural network system with time‐varying delay.
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            NameFull: Zhang, Lingling
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            NameFull: Huang, Lihong
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            NameFull: Cai, Zuowei
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          Dates:
            – D: 01
              M: 11
              Text: Nov2025
              Type: published
              Y: 2025
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              Value: 27
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              Value: 6
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            – TitleFull: Asian Journal of Control
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