Decentralized Adaptive Event-Triggered Synchronization of Neutral Neural Networks with Time-Varying Delays
Decentralized Adaptive Event-Triggered Synchronization of Neutral Neural Networks with Time-Varying Delays
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DOI：
10.1007/s00034-018-0889-2
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发表时间：
2018-06
期刊：
影响因子：
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通讯作者：
Tao Li;Yaobao Yu;Ting Wang;S. Fei
中科院分区：
文献类型：
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作者：
Tao Li;Yaobao Yu;Ting Wang;S. Fei
本文研究了一类主从式时变时滞神经网络的自适应事件触发同步问题。提出了分布式事件触发方案的设计，该方案只利用局部可用信息来确定从多个传感器到一个集中控制器的释放时刻。与现有的触发阈值不同的是，触发阈值取决于被控系统的实时性能。结合一些新的Lyapunov项，构造了一个增广的Lyapunov-Krasovskii泛函，该泛函可以充分利用时滞之间的相互联系。特别地，以线性矩阵不等式的形式得到了控制器增益的一个较不保守的条件。最后，通过两个数值算例对所得结果进行了验证。
In this work, the adaptive event-triggered synchronization in a class of master–slave neutral neural networks with time-varying delay is studied. The design of decentralized event-triggered scheme is proposed, which only utilizes local available information to determine the released instants from multiple sensors to a centralized controller. Different from existing ones, the triggering thresholds depend on real-time performance of controlled system. Together with some novel Lyapunov terms, an augmented Lyapunov–Krasovskii functional is constructed, in which the interconnection between time delays can be fully utilized. In particular, a less conservative condition on controller gain is obtained in terms of linear matrix inequalities. Finally, the derived results are verified by resorting to two numerical examples.