Improved Robust Stability Criteria for Delayed Cellular Neural Networks via the LMI Approach
Improved Robust Stability Criteria for Delayed Cellular Neural Networks via the LMI Approach
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DOI：
10.1109/tcsii.2009.2036544
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发表时间：
2010
期刊：
影响因子：
--
通讯作者：
Chengde Zheng;Huaguang Zhang;Zhanshan Wang
中科院分区：
文献类型：
--
作者：
Chengde Zheng;Huaguang Zhang;Zhanshan Wang
分析了一类具有时变时滞的不确定细胞神经网络的唯一性和鲁棒指数稳定性。通过将时滞的变化区间划分为两个长度相等的子区间，引入了一种新的Lyapunov-Krasovskii泛函。利用自由加权矩阵法，得到了一种新的与时滞相关的稳定性判据，该判据的保守性比一些文献要小。由于结果是用线性矩阵不等式的形式表示的，因此该条件易于验证。最后，通过一个算例说明了所提方法的有效性。
Uniqueness and robust exponential stability are analyzed for a class of uncertain cellular neural networks with time-varying delays. By dividing the variation interval of the time delay into two subintervals with equal length, a novel Lyapunov-Krasovskii functional is introduced. Using the free-weighting matrix method, a new delay-dependent stability criterion is obtained, which is less conservative than some previous literature. Since the result is presented in terms of linear matrix inequalities, the condition is easy to be verified. Finally, an example is given to illustrate the effectiveness of our proposed method.