Ge Chao, Liu Xin, Liu Yajuan, Hua Changchun
IEEE Trans Neural Netw Learn Syst. 2024 Feb;35(2):1750-1760. doi: 10.1109/TNNLS.2022.3185098. Epub 2024 Feb 5.
The synchronization for a class of switched uncertain neural networks (NNs) with frequent asynchronism based on event-triggered control is researched in this article. Compared with existing works that require one switching during an inter-event interval, frequent switching is allowed in this article. By employing controller-mode-dependent Lyapunov-Krasovskii functionals (LKFs), we devise the control strategy to guarantee that the switched NNs can be synchronized. The proposed LKFs can make full use of system information. Using an improved integral inequality, some sufficient stability conditions formed by linear matrix inequalities (LMIs) are derived for the synchronization of switched uncertain NNs. Average dwell time (ADT) is obtained in the form of inequality that includes the maximum inter-event interval. In addition, the existence of lower bound of inter-event interval is discussed to avoid Zeno behavior. At last, the feasibility of the proposed method is proven by a numerical example.
本文研究了一类基于事件触发控制的具有频繁异步性的切换不确定神经网络（NNs）的同步问题。与现有工作要求在事件间间隔内进行一次切换不同，本文允许频繁切换。通过采用依赖于控制器模式的Lyapunov-Krasovskii泛函（LKFs），我们设计了控制策略以确保切换神经网络能够同步。所提出的LKFs能够充分利用系统信息。利用一个改进的积分不等式，推导了一些由线性矩阵不等式（LMI）组成的用于切换不确定神经网络同步的充分稳定性条件。平均驻留时间（ADT）以包含最大事件间间隔的不等式形式获得。此外，还讨论了事件间间隔下界的存在性以避免芝诺行为。最后，通过一个数值例子证明了所提方法的可行性。
