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Dynamic Event‐Triggered Prescribed Performance Optimal Secure Control for Nonlinear Systems Under DoS Attacks.

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Title: Dynamic Event‐Triggered Prescribed Performance Optimal Secure Control for Nonlinear Systems Under DoS Attacks.
Authors: Hu, Lin‐Xiao1 (AUTHOR), Li, Yuan‐Xin1 (AUTHOR) yxinly@126.com
Source: International Journal of Robust & Nonlinear Control. Jun2026, Vol. 36 Issue 9, p5044-5060. 17p.
Subjects: Denial of service attacks, Optimal control theory, Adaptive fuzzy control, Reinforcement learning, Nonlinear systems, Lyapunov stability, Real-time control, Fault-tolerant control systems
Abstract: This paper focuses on the problem of optimized fuzzy prescribed performance control for nonlinear strict‐feedback systems under denial‐of‐service (DoS) attacks. DoS attacks disrupt communication channels, leading to the output signal and states of the system unavailable. A switched fuzzy observer is adopted to reconstruct unmeasurable states under DoS attacks. Simultaneously, a simpler prescribed performance error transformation is constructed to constrain the tracking error within a prescribed boundary, which can improve the transient and steady‐state performance of the control system. To achieve optimized fuzzy prescribed performance control under DoS attacks, an event‐based secure optimal control strategy is proposed. Specifically, the controller at each backstepping layer is designed as the optimal solution for the corresponding subsystem, such that the entire backstepping control process is optimized. Due to the difficulty in directly solving optimal solutions, a reinforcement learning (RL) algorithm with an actor‐critic architecture is incorporated into the control design process to obtain approximate optimal controllers. In addition, a dynamic event‐triggering mechanism (DETM) is proposed to improve the utilization rate of the communication resource. Through Lyapunov stability analysis, it is proved that the tracking error always evolves within the performance envelope, and the consumed control resources are minimized. Meanwhile, the Zeno behavior can be effectively eliminated. Finally, the effectiveness of the proposed strategy is verified via a simulation example. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Robust & Nonlinear 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.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 193491460
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PubTypeId: academicJournal
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  Label: Title
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  Data: Dynamic Event‐Triggered Prescribed Performance Optimal Secure Control for Nonlinear Systems Under DoS Attacks.
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  Data: <searchLink fieldCode="AR" term="%22Hu%2C+Lin‐Xiao%22">Hu, Lin‐Xiao</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Yuan‐Xin%22">Li, Yuan‐Xin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> yxinly@126.com</i>
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Robust+%26+Nonlinear+Control%22">International Journal of Robust & Nonlinear Control</searchLink>. Jun2026, Vol. 36 Issue 9, p5044-5060. 17p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Denial+of+service+attacks%22">Denial of service attacks</searchLink><br /><searchLink fieldCode="DE" term="%22Optimal+control+theory%22">Optimal control theory</searchLink><br /><searchLink fieldCode="DE" term="%22Adaptive+fuzzy+control%22">Adaptive fuzzy control</searchLink><br /><searchLink fieldCode="DE" term="%22Reinforcement+learning%22">Reinforcement learning</searchLink><br /><searchLink fieldCode="DE" term="%22Nonlinear+systems%22">Nonlinear systems</searchLink><br /><searchLink fieldCode="DE" term="%22Lyapunov+stability%22">Lyapunov stability</searchLink><br /><searchLink fieldCode="DE" term="%22Real-time+control%22">Real-time control</searchLink><br /><searchLink fieldCode="DE" term="%22Fault-tolerant+control+systems%22">Fault-tolerant control systems</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This paper focuses on the problem of optimized fuzzy prescribed performance control for nonlinear strict‐feedback systems under denial‐of‐service (DoS) attacks. DoS attacks disrupt communication channels, leading to the output signal and states of the system unavailable. A switched fuzzy observer is adopted to reconstruct unmeasurable states under DoS attacks. Simultaneously, a simpler prescribed performance error transformation is constructed to constrain the tracking error within a prescribed boundary, which can improve the transient and steady‐state performance of the control system. To achieve optimized fuzzy prescribed performance control under DoS attacks, an event‐based secure optimal control strategy is proposed. Specifically, the controller at each backstepping layer is designed as the optimal solution for the corresponding subsystem, such that the entire backstepping control process is optimized. Due to the difficulty in directly solving optimal solutions, a reinforcement learning (RL) algorithm with an actor‐critic architecture is incorporated into the control design process to obtain approximate optimal controllers. In addition, a dynamic event‐triggering mechanism (DETM) is proposed to improve the utilization rate of the communication resource. Through Lyapunov stability analysis, it is proved that the tracking error always evolves within the performance envelope, and the consumed control resources are minimized. Meanwhile, the Zeno behavior can be effectively eliminated. Finally, the effectiveness of the proposed strategy is verified via a simulation example. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Robust & Nonlinear 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/rnc.70480
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 17
        StartPage: 5044
    Subjects:
      – SubjectFull: Denial of service attacks
        Type: general
      – SubjectFull: Optimal control theory
        Type: general
      – SubjectFull: Adaptive fuzzy control
        Type: general
      – SubjectFull: Reinforcement learning
        Type: general
      – SubjectFull: Nonlinear systems
        Type: general
      – SubjectFull: Lyapunov stability
        Type: general
      – SubjectFull: Real-time control
        Type: general
      – SubjectFull: Fault-tolerant control systems
        Type: general
    Titles:
      – TitleFull: Dynamic Event‐Triggered Prescribed Performance Optimal Secure Control for Nonlinear Systems Under DoS Attacks.
        Type: main
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      – PersonEntity:
          Name:
            NameFull: Hu, Lin‐Xiao
      – PersonEntity:
          Name:
            NameFull: Li, Yuan‐Xin
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      – BibEntity:
          Dates:
            – D: 01
              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
          Identifiers:
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              Value: 10498923
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              Value: 36
            – Type: issue
              Value: 9
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            – TitleFull: International Journal of Robust & Nonlinear Control
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