This paper addresses the input-to-state formation stabilization problem of nonlinear multi-agent systems within a hybrid impulsive framework, considering delay-dependent impulses, strong nonlinearity, and deception attack signals. By leveraging Lyapunov functionals, impulsive comparison theory, average impulsive interval methods, and graph theory, we develop novel criteria for possessing locally input-to-state and integral input-to-state formation stabilization across different impulse sequence classes. These criteria are expressed in terms of continuous/impulsive feedback gains, time delay size, nonlinearity strength, uniform upper bound of impulsive interval, and length of average impulsive interval. Notably, the design of control impulses benefit the destabilizing continuous dynamics in the formation stabilization process. To demonstrate the effectiveness and validity of the analytical results, we provide numerical simulation examples involving various types of external attack signals.

中文翻译：

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具有脉冲延迟的多智能体系统的输入到状态混合脉冲形成稳定


本文解决了混合脉冲框架内非线性多智能体系统的输入到状态形成稳定问题，考虑了延迟相关脉冲、强非线性和欺骗攻击信号。通过利用李雅普诺夫泛函、脉冲比较理论、平均脉冲区间方法和图论，我们开发了新的标准，用于在不同的脉冲序列类别中拥有局部输入状态和积分输入状态形成稳定性。这些标准用连续/脉冲反馈增益、时间延迟大小、非线性强度、脉冲间隔的统一上限和平均脉冲间隔的长度来表达。值得注意的是，控制脉冲的设计有利于地层稳定过程中的不稳定连续动态。为了证明分析结果的有效性和有效性，我们提供了涉及各种类型的外部攻击信号的数值模拟示例。