时延细胞神经网络的全局渐近稳定性

通过构造新的Lyapunov泛函,在Lyapunov泛函中巧妙引入可调的实参数,并结合不等式运用的一些技巧,讨论了时延细胞神经网络的全局渐近稳定性问题,得到了该模型的平衡点全局渐近稳定的一些新的充分条件。所得的结果改进推广了已有文献中相应的一些结论,并且可应用于以前所不能处理的若干情形。理论分析和数学推导表明,全局渐近稳定性的一个简单充分判据与时延是有关的。所得结果突出了时延对于细胞神经网络的全局渐近稳定性的影响,这对于设计带时延的细胞神经网络有着重要的参考价值。此外,通过实例说明了相应结果的应用,这在理论上和应用中都有着重要的意义。     

切换系统输入对状态稳定性的充分条件

研究了切换系统输入对状态的稳定性.在所有子系统都是输入对状态稳定的条件下,利用各子系统的KY函数和K函数构造出切换系统所需的KY函数和X函数,从而给出了切换系统输入对状态稳定的充分条件.对于一类常见的切换系统,计算出保证输入对状态稳定性的切换停留时间的下界,所有结果都是构造性的.     

一类离散BAM神经网络的全局渐近稳定性分析--LMI方法

提出一种新的神经网络模型--标准神经网络模型(SNNM),并给出基于线性矩阵不等式(LMI)的SNNM平衡点的全局渐近稳定性定理.通过状态的线性变换,将推广的离散BAM神经网络转化为SNNM,利用SNNM的稳定性结论,判定该离散BAM的全局渐近稳定性.该方法扩展了以前的稳定性结果,保守性低,容易验证,同时也适用于其它类型的递归神经网络的稳定性分析.     

Hopfield神经网络系统的全局稳定性分析

研究一类Hopfield神经网络系统的平衡状态的存在性、唯一性与全局稳定性, 这类系统放弃了以前对激励函数的有界性、单调性和可微性要求. 利用M矩阵理论, 通过构造适当的Lyapunov函数, 得到了系统全局渐近稳定的充分条件.     

无穷时滞神经网络的全局稳定性

本文研究具有无穷时滞的神经网络的全局稳定性问题。通过拓广泛函数微分方程理论中的Ｒａｚｕｍｉｋｈｉｎ思想，获得了无十分简洁的稳定性准则。     

非线性控制系统的输入-状态稳定性及有关问题

输入-状态稳定性是80年代末对非线性控制系统提出的一个有用的概念,由于其具有广泛的应用前景,而得到普遍的重视,本文介绍进入90年代以来对这种稳定性以及由此派生出来的其他稳定性研究的主要成果,讨论了相关的镇定问题,同时给出作者的评注。     

一类时滞切换系统的输入-状态稳定性分析

利用多Lyapunov函数方法、驻留时间法和Gronwall-Bellman不等式研究了一类时滞切换系统的输入-状态稳定性分析问题．从系统输入-状态稳定定义出发,给出了使得一类时滞切换系统输入-状态稳定的充分条件．与已有的方法相比,无需同时满足构造输入-状态稳定控制Lyapunov函数和所有子系统都是输入-状态稳定的条件,为控制器的设计提供了便利．最后,通过算例仿真验证了所提出方法的可行性．     

一类中立型时滞神经网络的全局渐近稳定性

讨论了一类带有时滞的中立型神经网络的稳定性问题。通过构造Lyapunov-Krasovskii泛函,利用矩阵Schur补性质研究了此类中立型时滞神经网络模型的全局渐近稳定性,得出基于矩阵特征值的稳定性的充分判据,并给出基于矩阵特征值的时滞Hopfield神经网络全局渐近稳定性的充分条件;数值仿真检验了结果的有效性。     

针对随机控制系统数值解的均方指数输入状态稳定性

分析了随机控制系统数值解的均方指数输入状态稳定性. 首先, 针对随机控制系统, 随机θ-方法满足有限时间强收敛条件. 然后, 我们证实, 在有限时间强收敛条件下, 随机控制系统是均方指数输入状态稳定的当且仅当随机θ-方法(充分小步长)是均方指数输入状态稳定的. 另外, 对一类满足单边Lipschitz条件的随机控制系统, 有两类隐式欧拉方法(对任意步长)能够继承原系统的均方指数输入状态稳定性. 最后, 一些数值实例证实了本文所获结论的正确性.     

带区间时变时滞的BAM神经网络渐近稳定性

针对一类具有区间时滞和随机干扰的BAM神经网络的全局渐近稳定性问题,通过构造合适的Lyapunov-Krasovskii泛函,应用随机分析和自由权值矩阵方法,并考虑时滞区间范围,得到了新的稳定性充分条件。该条件能够保证时滞BAM神经网络在均方意义下是全局渐近稳定的,同时适用于快时滞和慢时滞,其适用范围更广。最后,通过一个仿真实例证明了定理的有效性。     

非线性切换广义系统的输入– 状态稳定性

针对一类非线性切换广义系统,分两种情况对其输入-状态稳定性问题进行了研究.采用平均驻留时间方法,通过设计适当的切换规则,给出了非线性切换广义系统整体输入-状态稳定的充分条件.相较于已有的控制方法,该方法无需构造输入-状态稳定的Lyapunov函数以及无需设计控制器的具体结构,这在一定程度上方便了控制器的设计.最后,两个仿真算例表明了所提方法的有效性.     

Input-to-state practical stability analysis and controller design of switched affine systems: An observer-based approach

This paper addresses the problems of the input-to-state practical stability (ISPS) analysis and output feedback controller design for switched affine systems (SASs) subject to external disturbances. First, a switched affine observer is developed to estimate unmeasurable states. Then by combining the sampled-data control approach, a less conservative mode-dependent dynamic event-triggered mechanism (ETM) is established. The proposed dynamic ETM cannot only avoid Zeno behavior but also reduce the network transmission burden effectively. Further, based on time-dependent Lyapunov-Krasovskii functional and state-dependent switching laws, a set of feasible ISPS conditions are presented in the LMI forms by means of singular value decomposition. The designed switching law depends upon the sampled-data information of the estimated state and gets rid of the chattering phenomenon. Finally, an application example of the DC-DC flyback converter is given to verify the efficacy of the proposed algorithm.     

Input-to-state stability of switched nonlinear systems

The input-to-state stability （ISS） problem is studied for switched systems with infinite subsystems. By using multiple Lyapunov function method, a sufficient ISS condition is given based on a quantitative relation of the control and the values of the Lyapunov functions of the subsystems before and after the switching instants. In terms of the average dwell-time of the switching laws, some sufficient ISS conditions are obtained for switched nonlinear systems and switched linear systems, respectively.     

Estimates of equilibrium points and global asymptotic stability of Cohen–Grossberg neural networks with delays

This article studies a class of Cohen–Grossberg neural networks (CGNNs) with variable and distributed delays. Some novel conditions guaranteeing the existence, uniqueness and the estimated location of the equilibrium points are obtained. Using these results, the global asymptotic stability of the CGNNs can be derived without demanding the boundedness and the globally Lipschitz condition of the activation functions. Two numerical examples are demonstrated to verify the theoretical results.     

Input-to-state stability and integral input-to-state stability of nonlinear impulsive systems with delays

This paper is concerned with analyzing input-to-state stability (ISS) and integral-ISS (iISS) for nonlinear impulsive systems with delays. Razumikhin-type theorems are established which guarantee ISS/iISS for delayed impulsive systems with external input affecting both the continuous dynamics and the discrete dynamics. It is shown that when the delayed continuous dynamics are ISS/iISS but the discrete dynamics governing the impulses are not, the ISS/iISS property of the impulsive system can be retained if the length of the impulsive interval is large enough. Conversely, when the delayed continuous dynamics are not ISS/iISS but the discrete dynamics governing the impulses are, the impulsive system can achieve ISS/iISS if the sum of the length of the impulsive interval and the time delay is small enough. In particular, when one of the delayed continuous dynamics and the discrete dynamics are ISS/iISS and the others are stable for the zero input, the impulsive system can keep ISS/iISS no matter how often the impulses occur. Our proposed results are evaluated using two illustrative examples to show their effectiveness.