变时滞模糊随机细胞神经网络新的鲁棒稳定性  

New robust stability of fuzzy stochastic cellular neural networks with time-varying delay

作　　者：李亚军[1,2] 邓飞其[1] 彭云建[1] 

机构地区：[1]华南理工大学自动化科学与工程学院,广州510640 [2]顺德职业技术学院电子与信息工程系,广东佛山528300

出　　处：《控制与决策》2011年第8期1197-1202,共6页Control and Decision

基　　金：国家杰出青年科学基金项目(51685168);教育部重点科研基金项目(02152)

摘　　要：研究一类具有参数不确定时滞模糊随机细胞神经网络的鲁棒稳定性问题.利用模糊规则,基于Lyapunov-Krasovskii范函方法和随机稳定性理论,结合自由权矩阵,给出并证明了使系统鲁棒稳定的充分条件,所有结果以线性矩阵不等式形式给出.仿真算例表明了所提出方法的有效性和低保守性.The robust stability problem of stochastic fuzzy cellular neural networks with parameter uncertainties and timevarying delays is investigated. By using fuzzy rules, based on the Lyapunov-Krasovsldi method and stochastic stability theory, combining with the the free weight matrix technique, the sufficient condition for making the system robustly stable is given and derived. All results are given in terms of linear matrix inequalities（LMIs）. Numerical example shows the effectiveness and the low conservation of the proposed method.

关 键 词：鲁棒稳定性:模糊细胞神经网络 随机系统 线性矩阵不等式 变时滞 自由权矩阵 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]