非线性扰动时滞神经网络的鲁棒镇定方法

Ruliang Wang, Hong Lei, Jin Wang
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引用次数: 1

摘要

本文考虑了一类具有非线性扰动的时滞动力系统。假设非线性扰动函数是有界的。通过设计具有非线性扰动的时滞动态神经网络的无记忆状态反馈控制器,给出了鲁棒镇定判据。用线性矩阵不等式(LMI)给出了充分判据。用本文的结果对具有非线性扰动的时滞动态神经网络的鲁棒镇定性进行了简单的检验,便于应用。通过两个具体的例子证明了我们的结果的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Method of Robust Stabilization for the Delay Neural Networks with Nonlinear Perturbations
In this paper, we consider a class of time-delay dynamical systems with nonlinear perturbation. The nonlinear perturbation functions are assumed bounded. we provide a robust stabilization criterion via designing a memoryless state feedback controller for the time-delay dynamical neural networks with nonlinear perturbation. The sufficient criterion is given in terms of linear matrix inequality (LMI). The checking for robust stabilization of time-delay dynamical neural networks with nonlinear perturbation by our result can be carried out rather simply, and convenient for the application. The applicability of our results is demonstrated by means of two specific examples.
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