具有漏泄时滞的随机神经网络的均方指数稳定性

在实现复杂的人工神经网络模型的过程中,随机噪声是不可避免的。建立具有随机噪声干扰的神经网络模型不但是设计上的需要,而且能够更加真实地反映生物神经网络的特点。本文利用构造合适的Lyapunov泛函,应用It?微分公式及Jensen不等式性质等,研究了一类具有漏泄时滞的随机神经网络的动力学行为,得到了确保该系统均方指数稳定的充分判别条件。最后, 通过两个数值计算的例子,说明所得结论的有效性。     

具有有界时滞的脉冲随机泛函微分系统的有限时间稳定

本文研究了具有有界时滞的脉冲随机泛函微分系统的有限时间稳定和有限时间渐近稳定问题. 基于Lyap-unov函数、Razumikhin技巧以及平均脉冲区间条件, 本文建立了关于该系统有限时间稳定和有限时间渐近稳定的相关性准则. 最后, 给出例子说明结论的有效性.     

具有滞后耦合特性的线性随机大系统的时滞无关均方稳定性*

本文研究具有滞后耦合特性的时不变线性Ｉｔｏ随机大系统的稳定性，得到了大系统平衡态滞后无关的均方渐近稳定性代数判据．文中所考虑的子系统是随机子系统，对它们的假设正好是它们均方渐近稳定的充要条件．另外，文中采用的Ｌｙａｐｕｎｏｖ泛函是确定型的Ｌｙａｐｕｎｏｖ泛函．     

时滞线性随机系统的均方稳定性与反馈镇定*

本文研究Ｉｔｏｏ型随机滞后系统的均方稳定性与反馈镇定。文中首先建立了Ｉｔｏ型随机滞后系统的新型稳定性定理，然后采用适当的Ｌｙａｐｕｎｏｖ泛函得到了时滞线性随机系统零解均方渐近稳定的一个充分性判据，该判据适用于完全滞后型的随机系统，据此判据，文中给出了时滞线性随机系统的滞后反馈镇定方法。     

具有状态时滞的切换随机系统的指数稳定条件

考虑由具有状态时滞的线性It(o)随机子系统构成的切换系统,基于多Lyapunov泛函方法研究切换与时滞对于稳定性的共同影响,并以此建立均方指数稳定条件.在均方意义下噪声对于稳定性的影响基本是负面的,因此构造一类形式较为一般的Lyapunov泛函并运用噪声的统计特性于其解析过程中,以减少噪声所引起的保守性.最后,通过一个仿真算例描述切换与时滞的相互制约关系表明了所提出方法的有效性.     

分布时滞随机偏微分系统的均方指数稳定性

针对一类同时具有分布时滞和维纳过程的随机偏微分系统, 首先基于It?o微分公式, 通过计算弱无穷小算 子, 得到了随机微分导数; 其次利用Green公式和积分不等式及Schur补引理对矩阵不等式进行处理; 然后对微分两 边积分并同时取数学期望处理随机交叉项; 获得了分布时滞随机偏微分系统是均方指数稳定的充分条件. 在此基础 上, 进一步考虑了离散变时滞和分布变时滞在一定约束情形下的分布时滞随机偏微分系统的均方指数稳定性问题. 最后给出仿真实例, 仿真结果表明所获得的线性矩阵不等式条件保证了系统的稳定性, 验证了所得结论的有效性.     

一类带有随机、有界时滞网络控制系统的脉冲控制

如何在信道约束下设计控制器对于网络控制系统的研究具有重要意义,为此提出将脉冲控制思想应用于网络控制系统,通过减少反馈过程的通信次数来降低控制策略对信道传输能力的依赖.首先构建网络脉冲控制系统模型;继而利用Lyapunov函数方法得到一类带有随机、有界时滞的网络控制系统的指数稳定性条件,并给出了脉冲控制器参数与系统收敛速度之间的定量关系;最后通过数值仿真结果验证了所提出方法的有效性.     

不确定变时滞随机系统的鲁棒均方指数稳定性

研究了不确定变时滞随机系统的鲁棒均方指数稳定性问题, 不确定性是范数有界的. 通过构造Lyapunov泛函, 得到了基于线性矩阵不等式的鲁棒均方指数稳定的充分条件. 最后给出实例加以验证所提出方法的有效性.     

非线性滞后Ito随机系统的滞后无关均方渐近稳定性

研究非线性滞后Ｉｔｏ随机系统的滞后无关均方渐近稳定性，将关于线性时滞不等式的Ｈａｌａｎａｙ不等式推广到非线性情形，用Ｌｙａｐｕｎｏｖ函数和关于时滞随机系统的比较原理，得到了非线性滞后Ｉｔｏ随机系统滞后无关均方渐近稳定性的一些判据。     

具有状态时滞的Markov切换系统的指数稳定性新结果

考虑具有状态时滞的Markov切换系统的均方指数稳定性分析问题. 为此, 我们构造了一类较为一般的与模态相关的Lyapunov-Krasovskii泛函, 并利用Markonv过程的统计性质计算泛函的微分. 进而, 通过引入自由权矩阵建立了以线性矩阵不等式表述的稳定性准则. 仿真算例验证了方法的有效性.     

An analysis of the exponential stability of linear stochastic neutral delay systems

This paper is concerned with the analysis of the mean square exponential stability and the almost sure exponential stability of linear stochastic neutral delay systems. A general stability result on the mean square and almost sure exponential stability of such systems is established. Based on this stability result, the delay partitioning technique is adopted to obtain a delay‐dependent stability condition in terms of linear matrix inequalities (LMIs). In obtaining these LMIs, some basic rules of the Ito calculus are also utilized to introduce slack matrices so as to further reduce conservatism. Some numerical examples borrowed from the literature are used to show that, as the number of the partitioning intervals increases, the allowable delay determined by the proposed LMI condition approaches h_max, the maximal allowable delay for the stability of the considered system, indicating the effectiveness of the proposed stability analysis. Copyright © 2013 John Wiley & Sons, Ltd.     

Mean square exponential stability of stochastic nonlinear delay systems

In this paper, we are concerned with the stability of stochastic nonlinear delay systems. Different from the previous literature, we aim to show that when the determinate nonlinear delay system is globally exponentially stable, the corresponding stochastic nonlinear delay system can be mean square globally exponentially stable. In particular, we remove the linear growth condition and introduce a new polynomial growth condition for g(x(t), x(t ? τ(t))), which overcomes the limitation of application scope and the boundedness of diffusion term form. Finally, we provide an example to illustrate our results.     

Mean square stability of linear stochastic neutral‐type time‐delay systems with multiple delays

This paper studies mean square exponential stability of linear stochastic neutral‐type time‐delay systems with multiple point delays by using an augmented Lyapunov‐Krasovskii functional (LKF) approach. To build a suitable augmented LKF, a method is proposed to find an augmented state vector whose elements are linearly independent. With the help of the linearly independent augmented state vector, the constructed LKF, and properties of the stochastic integral, sufficient delay‐dependent stability conditions expressed by linear matrix inequalities are established to guarantee the mean square exponential stability of the system. Differently from previous results where the difference operator associated with the system needs to satisfy a condition in terms of matrix norms, in the current paper, the difference operator only needs to satisfy a less restrictive condition in terms of matrix spectral radius. The effectiveness of the proposed approach is illustrated by two numerical examples.     

Mean square exponential stability analysis of impulsive stochastic switched systems with mixed delays

In this paper, a class of impulsive stochastic switched systems with mixed delays is considered. On the basis of some integro-differential inequalities and stochastic analysis techniques, some general criteria for mean square exponential stability are obtained. An example is given to illustrate the theory.     

Robust exponential stability conditions for retarded systems with Lipschitz nonlinear stochastic perturbations

This paper investigates robust mean‐square exponential stability of a class of uncertain stochastic state‐delayed systems with Lipschitz nonlinear stochastic perturbation. Based on Lyapunov–Krasovskii functional (LKF) method and free‐weighting matrix technique, some new delay‐dependent stability conditions are established in terms of linear matrix inequalities (LMIs). In order to reduce the conservatism, (1) the delay is divided into several segments, i.e. the delay decomposition method is applied; (2) cross terms estimation is avoided; (3) some information of the cross terms relationships which has not been involved in Reference (IET Control Theory Appl. 2008; 2(11):966–973) is considered. Moreover, from the mathematical point of view, the results obtained by free‐weighting matrix technique can be equivalently re‐formulated by simpler ones without involving any additional free matrix variables. The effectiveness of the method is demonstrated by numerical examples. Copyright © 2010 John Wiley & Sons, Ltd.     

Exponential stability and exponential stabilization of singularly perturbed stochastic systems with time‐varying delay

In this paper, the problems of exponential stability and exponential stabilization for linear singularly perturbed stochastic systems with time‐varying delay are investigated. First, an appropriate Lyapunov functional is introduced to establish an improved delay‐dependent stability criterion. By applying free‐weighting matrix technique and by equivalently eliminating time‐varying delay through the idea of convex combination, a less conservative sufficient condition for exponential stability in mean square is obtained in terms of ε‐dependent linear matrix inequalities (LMIs). It is shown that if this set of LMIs for ε=0 are feasible then the system is exponentially stable in mean square for sufficiently small ε?0. Furthermore, it is shown that if a certain matrix variable in this set of LMIs is chosen to be a special form and the resulting LMIs are feasible for ε=0, then the system is ε‐uniformly exponentially stable for all sufficiently small ε?0. Based on the stability criteria, an ε‐independent state‐feedback controller that stabilizes the system for sufficiently small ε?0 is derived. Finally, numerical examples are presented, which show our results are effective and useful. Copyright © 2010 John Wiley & Sons, Ltd.     

On exponential stability conditions of linear neutral stochastic differential systems with time‐varying delay

We consider a class of neutral stochastic systems with time‐varying delay and study the exponential stability in the mean square sense. We derive sufficient stability conditions via applying Lyapunov functional method along with some practical techniques. Firstly, in computing the constructed Lyapunov functional, we make use of some basic rules of Itô calculus to reduce the conservatism produced by noise because it, in principle, plays a negative role for preserving stability in the mean square sense. Also, it is an important observation that, using some slack matrices, we can create convex conditions to accommodate the computation to time‐varying delay. In the sequel, we use a perturbation approach to estimate the decay rate of state and come to the conclusion of stability. Finally, we include an example to demonstrate the effectiveness of the method. Copyright © 2012 John Wiley & Sons, Ltd.