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Observer-Based Self-Triggered Resilient Control for Multiagent Systems: A k-Connected Graph Construction Approach.

Shuo-Qiu Zhang, Wei-Wei Che

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    Summary
    This summary is machine-generated.

    This study introduces a resilient control scheme for multiagent systems (MASs) to counter denial-of-service attacks. The self-triggered method enhances security and reduces resource use in distributed systems.

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    Area of Science:

    • Control Theory
    • Networked Systems
    • Cybersecurity

    Background:

    • Multiagent systems (MASs) face vulnerabilities from communication link denial-of-service (CLDoS) attacks.
    • Existing control strategies often require extensive communication topology information, increasing susceptibility.
    • Distributed systems demand robust solutions for secure and efficient operation.

    Purpose of the Study:

    • To develop a fully distributed, self-triggered, secure synchronization control for MASs resilient to CLDoS attacks.
    • To minimize reliance on explicit communication topology information.
    • To reduce system resource consumption through event-triggered control.

    Main Methods:

    • Design of an algorithm for constructing k-connected graphs to mitigate CLDoS impacts.
    • Co-design of a fully distributed observer-based resilient control scheme.
    • Proposal of a self-triggered mechanism to avoid continuous system monitoring.

    Main Results:

    • The k-connected graph construction effectively reduces the impact of CLDoS attacks.
    • The observer-based resilient control scheme enhances system stability and security.
    • The self-triggered method successfully reduces communication and computational load.

    Conclusions:

    • The proposed control scheme and graph construction algorithm provide an effective solution for secure synchronization in MASs under CLDoS attacks.
    • The self-triggered approach offers a practical method for resource-efficient distributed control.
    • The study demonstrates superior performance compared to existing methods through simulation.