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<p>This study introduces a new architecture to improve the security and resilience of autonomous coordination and affine formation control in multi-agent autonomous underwater vehicle (AUV) systems, especially against cyberattacks. The complexity of sustaining coordinated maneuverability among multiple AUVs is increased by nonlinear terms associated with dynamical models, particularly under challenging circumstances including common threats such as Denial-of-Service (DoS) and Distributed Denial-of-Service (DDoS) attacks. The proposed solution successfully integrates graph-theoretic consensus approaches with a robust L1 adaptive control strategy for addressing this issue. This integration guarantees precise trajectory monitoring and robust formation management, even under impaired communication. The architecture is enhanced by the proposed Data Distribution Service (DDS) middleware layer that enables secure, scalable, and interoperable data transmission, facilitating real-time communication and strengthening security measures against data manipulation and service disruption. A rigorous mathematical proof is provided to guarantee system stability and performance under attack settings. Extensive simulation results validate the effectiveness of the proposed architecture in mitigating the adverse impacts of DoS attacks and maintaining the desired formation of AUVs in dynamic underwater environments.</p>

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Robust Adaptive Affine Formation Control of Autonomous Underwater Vehicles with Data Distribution Services Middleware Framework

  • 期刊论文

  • 发表日期：

    2025年12月1日

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  • Siddig M. Elkhider,
  • Imil Hamda Imran

摘要

This study introduces a new architecture to improve the security and resilience of autonomous coordination and affine formation control in multi-agent autonomous underwater vehicle (AUV) systems, especially against cyberattacks. The complexity of sustaining coordinated maneuverability among multiple AUVs is increased by nonlinear terms associated with dynamical models, particularly under challenging circumstances including common threats such as Denial-of-Service (DoS) and Distributed Denial-of-Service (DDoS) attacks. The proposed solution successfully integrates graph-theoretic consensus approaches with a robust L1 adaptive control strategy for addressing this issue. This integration guarantees precise trajectory monitoring and robust formation management, even under impaired communication. The architecture is enhanced by the proposed Data Distribution Service (DDS) middleware layer that enables secure, scalable, and interoperable data transmission, facilitating real-time communication and strengthening security measures against data manipulation and service disruption. A rigorous mathematical proof is provided to guarantee system stability and performance under attack settings. Extensive simulation results validate the effectiveness of the proposed architecture in mitigating the adverse impacts of DoS attacks and maintaining the desired formation of AUVs in dynamic underwater environments.