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    Area of Science:

    • Control Systems Engineering
    • Cyber-Physical Systems Security
    • Networked Systems

    Background:

    • Cyber-physical systems (CPSs) are vulnerable to denial-of-service (DoS) attacks, compromising state estimation.
    • Distributed state estimation in CPSs faces challenges with network resource utilization and transmission efficiency.

    Purpose of the Study:

    • To develop an event-triggered distributed state estimation scheme for CPSs under independent channel DoS attacks.
    • To enhance transmission efficiency and network resource utilization in distributed state estimation for CPSs.

    Main Methods:

    • An observer-based event-triggered transmission scheme is proposed.
    • A distributed Kalman filter is designed for state estimation.
    • Covariance intersection fusion and matrix rank properties are used to analyze estimation error covariance.

    Main Results:

    • A relationship between estimation error covariance, attack intensity, and transmission efficiency is established.
    • The proposed event-triggered scheme improves network resource utilization.
    • Simulation results validate the effectiveness of the developed methods against DoS attacks.

    Conclusions:

    • The event-triggered distributed state estimation is effective for CPSs under independent channel DoS attacks.
    • The proposed approach balances estimation performance with network resource efficiency.