中文摘要：

在实际问题中,系统发生过程的实质是一个随机过程。实际系统模型中随机性和模糊性通常是并存的,然而关于随机模糊系统的研究还相对较少。研究了基于T-S模糊模型的中立型随机时滞系统的鲁棒镇定问题。首先,利用Lyapunov-Krasovskii泛函方法设计Lyapunov泛函;其次,由于中立型随机系统中的差分算子较难处理,所以应用It微分公式来处理Lyapunov泛函并将其带入到中立型随机模糊系统中得到其随机微分;再次,运用Schur补引理及并行分布补偿法（PDC）将所得的随机微分进行阶数的扩充并以线性矩阵不等式（LMI）形式给出了基于T-S模糊模型的中立型随机时滞系统鲁棒镇定的新方法,同时所给线性矩阵不等式满足所有允许的不确定性;最后,通过一个数值算例说明了所提方法的有效性。

英文摘要：

In practical problems,the essence of process systems is a stochastic process.So the stochastic and fuzziness are usually exist in the actual system model.However,study of stochastic fuzzy system is still relatively less.This paper discuss the problem of robust stabilization for neutral T-S stochastic fuzzy time-delay systems.First of all,by using the Lyapunov-Krasovskii functional method design the Lyapunov functional.Secondly,it is difficult for difference operator in neutral stochastic systems.So by using Itodifferential equation to deal with the Lyapunov functional and turn it into neutral stochastic fuzzy system to get the stochastic differential.Then using Schur complement lemma and parallel distributed compensation（PDC）to expand the order of stochastic differential.The closed loop system of robust stabilization is given by linear matrix inequality（LMI）.Linear matrix inequality is meet all allow uncertainties.Finally,numerical example shows that our method is efficient.