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This article investigates a secure consensus control approach in multiagent systems under denial-of-service attacks, implying enhanced system reliability.
In this article, the secure consensus control problem is investigated for discrete-time multiagent systems (DTMASs) subjected to denial-of-service (DoS) attacks, where a model-free controller is proposed based on the Q-learning (QL) method. In an attack-free case, a dynamic decaying encryption key is designed to enable secure state transmission over communication channels through quantization-based encryption to prevent unauthorized access. Under DoS attacks, the system switches to a safe mode that partially halts communication, where the key transforms into a local scaling parameter to prevent quantizer saturation through dynamic expansion. The QL-driven algorithm is introduced to autonomously synthesize control gain matrices, without requiring system dynamics models. Moreover, sufficient conditions on the frequency and duration of DoS attacks are derived to ensure that the model-free controller guarantees consensus in DTMASs. Finally, simulation studies involving highly maneuverable aircraft technology vehicles (HiMATVs) are conducted, demonstrating that DTMASs equipped with the proposed approach exhibit significantly enhanced attack resistance compared to conventional methods.
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Zhang et al. (2026) studied this question.
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