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中文摘要：
讨论了一类具有区间时变时滞的不确定随机系统的稳定性问题．利用区间时滞的上、下界信息，构造了一个新颖的Lyapunov—Krasovskii泛函．以线性矩阵不等式（LMIs）形式给出了时滞相关稳定性的充分判据，利用Matlab工具箱可以很容易对这些判据进行检验．推导过程基于Jensen积分不等式方法，避免了系统模型变换和交叉项有界等易于产生保守性的方法的使用，故得出判据的保守性小于文献中已有的结果．由于在获得的稳定性条件中没有引入多余的矩阵变量，因此所得判据的计算复杂度明显降低．最后，用一个数值例子说明了该方法的有效性和具有的优势．
英文摘要：
The problem of the stability for a class of stochastic systems with time-varying interval delay and the norm-bounded uncertainty is investigated. Utilizing the information of both the lower and the upper bounds of the interval time-varying delay, a novel Lyapunov-Krasovskii functional is constructed. The delay-dependent sufficient criteria are derived in terms of linear matrix inequalities （LMIs）, which can be easily checked by the LMI in the Matlab toolbox. Based on the Jensen integral inequality, neither model transformations nor bounding techniques for cross terms is employed, so the derived criteria are less conservative than the existing results. Meanwhile, the computational complexity of the obtained stability conditions is reduced because no redundant matrix is introduced. A numerical example is given to show the effectiveness and the benefits of the proposed method.
同期刊论文项目
同项目期刊论文
Further results on mean square exponential stability of uncertain stochastic delayed neural networks
Improved results on passivity analysis of discrete-time stochastic neural networks with time-varying
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