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Improved Event-Triggered Adaptive Neural Network Control for Multi-agent Systems Under Denial-of-Service Attacks 被引量:1

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摘要 This paper addresses the consensus problem of nonlinear multi-agent systems subject to external disturbances and uncertainties under denial-ofservice(DoS)attacks.Firstly,an observer-based state feedback control method is employed to achieve secure control by estimating the system's state in real time.Secondly,by combining a memory-based adaptive eventtriggered mechanism with neural networks,the paper aims to approximate the nonlinear terms in the networked system and efficiently conserve system resources.Finally,based on a two-degree-of-freedom model of a vehicle affected by crosswinds,this paper constructs a multi-unmanned ground vehicle(Multi-UGV)system to validate the effectiveness of the proposed method.Simulation results show that the proposed control strategy can effectively handle external disturbances such as crosswinds in practical applications,ensuring the stability and reliable operation of the Multi-UGV system.
出处 《Artificial Intelligence Science and Engineering》 2025年第2期122-133,共12页 人工智能科学与工程(英文)
基金 The National Natural Science Foundation of China(W2431048) The Science and Technology Research Program of Chongqing Municipal Education Commission,China(KJZDK202300807) The Chongqing Natural Science Foundation,China(CSTB2024NSCQQCXMX0052).
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