AI 中文总结
本文针对存在执行延迟的复杂网络，提出一种事件触发牵制脉冲控制方法，推导了保证渐近稳定的延迟依赖条件，建立了排除芝诺行为的事件间时间下界，并通过耦合蔡氏电路网络仿真验证了方法有效性。
AI 中文摘要
本文研究了存在执行延迟时，通过事件触发牵制脉冲控制实现复杂网络的镇定问题。与现有假设控制瞬时执行的事件触发脉冲控制方案不同，所提框架明确考虑了事件检测与脉冲执行之间的延迟。通过构造合适的李雅普诺夫函数并分析延迟区间内的网络动力学，推导了显式的依赖于延迟的充分条件，以保证渐近稳定性。所得条件刻画了网络拓扑、执行延迟、脉冲控制增益与触发参数之间的相互作用。此外，还建立了事件间时间的严格正下界，该下界排除了芝诺（Zeno）行为，确保了实际可实现性。同时，通过网络拉普拉斯矩阵的谱条件，开发了基于拓扑的牵制节点选择准则。对耦合蔡氏电路（Chua circuits）网络的数值仿真，验证了所提方法的设计流程与有效性。
英文摘要
This paper investigates the stabilization of complex networks via event-triggered pinning impulsive control in the presence of actuation delays. Unlike existing event-triggered impulsive control schemes that assume instantaneous implementation, the proposed framework explicitly accounts for the delay between event detection and impulse execution. By constructing suitable Lyapunov functions and analyzing the network dynamics during the delay intervals, explicit delay-dependent sufficient conditions are derived to guarantee asymptotic stability. The obtained conditions characterize the interplay among network topology, actuation delays, impulsive control gains, and triggering parameters. In addition, a strictly positive lower bound on inter-event times is established, which excludes Zeno behavior and ensures practical implementability. A topology-based criterion for selecting pinned nodes is also developed through a spectral condition on the network Laplacian. Numerical simulations on a network of coupled Chua circuits illustrate the design procedure and verify the effectiveness of the proposed method.
