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    Summary
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    This study introduces a new adaptive control method for nonlinear cyber-physical systems (CPSs) to combat jamming attacks. The approach ensures system stability and data integrity using predictive compensation and efficient event-triggering mechanisms.

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    Area of Science:

    • Cyber-Physical Systems (CPSs)
    • Control Theory
    • Network Security

    Background:

    • Nonlinear cyber-physical systems face significant security challenges from jamming attacks.
    • Existing control methods may struggle with data loss and consecutive attacks.
    • Efficient resource utilization in control systems is crucial.

    Purpose of the Study:

    • To develop a robust security control framework for nonlinear CPSs against jamming attacks.
    • To enhance system resilience against data loss caused by jamming.
    • To optimize control system performance while minimizing resource consumption.

    Main Methods:

    • A novel event-based model-free adaptive control (MFAC) framework was established.
    • A multistep predictive compensation algorithm (PCA) was developed to handle data loss.
    • An event-triggering mechanism with a dead-zone operator was integrated into the adaptive controller.

    Main Results:

    • The proposed framework effectively compensates for data lost due to jamming, including consecutive attacks.
    • The event-triggering mechanism reduced communication and computation burdens without compromising control performance.
    • The boundedness of the tracking error was mathematically ensured in the mean-square sense.

    Conclusions:

    • The developed event-based MFAC with PCA offers a robust solution for securing nonlinear CPSs against jamming attacks.
    • The method demonstrates effectiveness using only input/output data, simplifying practical implementation.
    • Simulation results validate the proposed approach's superiority over existing methods.