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    Area of Science:

    • Robotics
    • Control Systems
    • Cybersecurity

    Background:

    • Multirobot systems (MRSs) face challenges in source-seeking tasks due to cyberattacks.
    • Mixed attacks include misbehavior (false data, Byzantine) and Denial-of-Service (DoS), disrupting network connectivity.

    Purpose of the Study:

    • To develop a resilient source-seeking algorithm for second-order MRSs under mixed cyberattacks.
    • To ensure reliable coordination and source localization despite network vulnerabilities.

    Main Methods:

    • A novel algorithm transforms the source-seeking problem into an auxiliary point-tracking problem.
    • Reference velocity guides benign robots using historical optimal positions.
    • Control signals are maintained using the latest pre-attack data during DoS attacks.

    Main Results:

    • The proposed algorithm ensures auxiliary points converge to the source, clustering benign robots.
    • The system demonstrates resilience against combined misbehaving and DoS attacks.
    • Sufficient conditions for stability are rigorously established.

    Conclusions:

    • The algorithm extends existing resilient consensus methods to discrete-time second-order MRSs.
    • It effectively addresses resilient source seeking under complex, mixed cyber threats.
    • Simulation and experimental results validate the algorithm's efficacy.