一类时滞动力网络的时滞相关稳定性

研究了节点含时滞的复杂动力网络在平衡点的稳定性.基于时滞微分不等式和李雅普诺夫稳定性理论,提出了此网络的时滞相关的局部渐近稳定的充分条件,并给出了时滞上界的具体表达式.最后的数值模拟分析表明结果是可行且有效的.     

多延时线性中立型系统的稳定性的代数判据

近年来多延时线性中立型微分系统的稳定性被广泛研究,大量的充分条件被得到,这些条件互为补充,使得很多这类系统的稳定性通过这些充分条件得以判定(参见文献[1-4]),我们借助于矩阵理论得到了依赖于延时的稳定性代数判据;进而给出了独立于延时的稳定性代数判据,最后给出例子来说明所给判据是对文献[1-4]所给判据的补充。     

New results on the robust stability analysis of neural networks with discrete and distributed time delays

Delay-dependent robust stability of cellular neural networks with time-varying discrete and distributed time-varying delays is considered. Based on Lyapunov stability theory and the linear matrix inequality （LMIs） technique, delay-dependent stability criteria are derived in terms of LMIs avoiding bounding certain cross terms, which often leads to conservatism. The effectiveness of the proposed stability criteria and the improvement over the existing results are illustrated in the numerical examples.     

Input-to-State Stability of Switched Nonlinear Delay Systems Based on a Novel Lyapunov-Krasovskii Functional Method

In this paper, the input-to-state stability (ISS) analysis is addressed for switched nonlinear delay systems. By introducing a novel Lyapunov-Krasovskii functional with indefinite derivative and the merging switching signal techniques, some new criteria are established for switched nonlinear delay systems under asynchronous switching, which extends the existing results to the nonlinear systems with switching rules and delays. The ISS problem is also considered under synchronous switching for switched nonlinear systems by employing the similar techniques. Finally, a nonlinear delay model is provided to show the effectiveness of the proposed results.     

变时滞广义神经网络的指数稳定性

讨论具有可变时滞的Cohen Grossberg广义神经网络平衡态的稳定性问题。以推广的Halanay微分不等式为工具,通过构造合适的Lyapunov函数,结合Dini导数和不等式技巧,对具有可变时滞(适合于任何时滞有界情况)的广义神经网络平衡态的指数稳定性进行分析。在适当的假设条件下,得到了系统渐近指数稳定的几个充分性判据,与此同时也给出了相应的Lyapunov指数。     

Study on Robust Uniform Asymptotical Stability for Uncertain Linear Impulsive Delay Systems

In the area of control theory the time-delay systems have been investigated. It's well known that delays often result in instability, therefore, stability analysis of time-delay systems is an important subject in control theory. As a result, many criteria for testing the stability of linear time-delay systems have been proposed. Significant progress has been made in the theory of impulsive systems and impulsive delay systems in recent years. However, the corresponding theory     

Existence and Global Exponential Stability of Pseudo Almost Periodic Solutions of a General Delayed BAM Neural Networks

This paper studies a class of general BAM neural networks with multiple delays. Employing the exponential dichotomy theory and fixed point method, together with constructing suitable Lyapunov functionals, easily verifiable delay-independent criteria are established to ensure the existence and global exponential stability of pseudo almost periodic solutions, which not only generalize but also complement some existing ones. These theoretical results are also supported with numerical simulations.     

Networked Learning Predictive Control of Nonlinear Cyber-Physical Systems

Cyber-physical systems integrate computing, network and physical environments to make the systems more efficient and cooperative, and have important and extensive application prospects, such as the Internet of things. This paper studies the control problem of nonlinear cyber-physical systems with unknown dynamics and communication delays. A networked learning predictive control scheme is proposed for unknown nonlinear cyber-physical systems. This scheme recursively learns unknown system dynamics, actively compensates for communication delays and accurately tracks a desired reference. Learning multi-step predictors are presented to predict various step ahead outputs of the unknown nonlinear cyber-physical systems. The optimal design of controllers minimises a performance cost function which measures the tracking error predictions and control input increment predictions. The system analysis leads to the stability criteria of closed-loop nonlinear cyber-physical systems employing the networked learning predictive control scheme. An example illustrates the outcomes of the proposed scheme.

     

Improved delay-dependent stability criteria for systems with interval delay

This paper deals with the problem of stability for systems with delay varying in an interval.A new Lyapunov functional,which makes use of the information of both the lower and upper bounds of the interval time-varying delay,is proposed to derive some new stability criteria.Furthermore,the relationship of the time-varying delay and its lower bound and upper bound is taken into account.As a result,some less conservative delay-dependent stability criteria are obtained without ignoring any useful information in the derivative of Lyapunov functional,which are established in the forms of linear matrix inequalities.Numerical examples are provided to show that the obtained results are better than existing ones.     

Pinning Synchronization of Discrete-Time Complex Networks with Different Time-Varying Delays

This paper investigates pinning synchronization of discrete-time complex networks with different time-varying delays. An important lemma is presented and proved, then detailed analysis is given to yield some synchronization criteria for this kind of networks. The results provide an effective way to synchronize discrete-time complex networks by reducing control cost. Furthermore, these theoretical results are illustrated by a complex network via two kinds of pinning schemes. Numerical simulations verify the feasibility of the proposed methods.     

延时耦合复杂动力网络的全局混沌同步

利用Lyapunov稳定性理论,结合线性矩阵不等式方法,给出了具有耦合延时的复杂动力网络全局指数同步的时滞无关和时滞相关的若干条件.同时以Duffing混沌系统为例,应用时滞相关条件,得到了保证同步状态全局指数稳定的时滞上界,并与已有结论作比较,验证了结论的保守性有所减弱.数值仿真结果也说明理论分析的正确性.     

一类多状态时滞不确定系统的鲁棒预测控制

针对一类多状态时滞多面体不确定对象,提出了一种鲁棒预测控制算法。基于参数相关的李亚普诺夫函数,给出了系统稳定的充分条件。通过求解满足若干线性矩阵不等式条件的上界值的最优化问题,获得了约束范围内满足系统鲁棒性能的最优控制律。优化问题的可行性保证了算法的鲁棒稳定性。仿真实例证明了该算法的有效性。     

Robust stability and stabilization for uncertain discrete-time switched singular systems with time-varying delays

The problems of robust stability and stabilization via memoryless state feedback for a class of discrete-time switched singular systems with time-varying delays and linear fractional uncertainties are investigated. By constructing a novel switched Lyapunov–Krasovskii functional, a delay-dependent criterion for the unforced system to be regular, causal and uniformly asymptotically stable is established in terms of linear matrix inequalities (LMIs). An explicit expression for the desired memoryless state feedback stabilization controller is also given. The merits of the proposed criteria lie in their less conservativeness and relative simplicity, which are achieved by considering additionally useful terms (ignored in previous methods) when estimating the upper bound of the forward difference of the Lyapunov–Krasovskii functional and by avoiding utilizing any model augmentation transformation. Some numerical examples are provided to illustrate the validity of the proposed methods.     

STABILITY OF N-DIMENSIONAL LINEAR SYSTEMS WITH MULTIPLE DELAYS AND APPLICATION TO SYNCHRONIZATION

This paper further investigates the stability of the n-dimensional linear systems with multiple delays. Using Laplace transform, we introduce a definition of characteristic equation for the n-dimensional linear systems with multiple delays. Moreover, one sufficient condition is attained for the Lyapunov globally asymptotical stability of the general multi-delay linear systems. In particular, our result shows that some uncommensurate linear delays systems have the similar stability criterion as that of the commensurate linear delays systems. This result also generalizes that of Chen and Moore （2002）. Finally, this theorem is applied to chaos synchronization of the multi-delay coupled Chua＇s systems.     

A New ANN Method of Aggregation and Stability Analtsis for Large－Scale System with Time Delay

ＡＮｅｗＡＮＮＭｅｔｈｏｄｏｆＡｇｇｒｅｇａｔｉｏｎａｎｄＳｔａｂｉｌｉｔｙＡｎａｌｔｓｉｓｆｏｒＬａｒｇｅ－ＳｃａｌｅＳｙｓｔｅｍｗｉｔｈＴｉｍｅＤｅｌａｙ￥ＺＨＡＮＧＪｉａｎ；ＬＩＵＹｏｎｇｑｉｎｇ；ＳＨＥＮＪｉａｎｊｉｎｇ（Ｄｅｐｔ．ｏｆＡｕｔ...     

New Results on Stability and Stabilization of Delayed Caputo Fractional Order Systems with Convex Polytopic Uncertainties

In this paper, the problems of robust stability and stabilization, for the first time, are studied for delayed fractional-order linear systems with convex polytopic uncertainties. The authors derive some sufficient conditions for the problems based on linear matrix inequality technique combined with fractional Razumikhin stability theorem. All the results are obtained in terms of linear matrix inequalities that are numerically tractable. The proposed results are quite general and improve those given in the literature since many factors, such as discrete and distributed delays, convex polytopic uncertainties, global stability and stabilizability, are considered. Numerical examples and simulation results are given to illustrate the effectiveness of the effectiveness of our results.     

Delay-dependent robust H∞ control of convex polyhedral uncertain fuzzy systems

The robust H∞ control problem for a class of uncertain Takagi-Sugeno fuzzy systems with time-varying state delays is studied. The uncertain parameters are supposed to reside in a polytope. Based on the delay-dependent Lyapunov functional method, a new delay-dependent robust H∞ fuzzy controller, which depends on the size of the delays and the derivative of the delays, is presented in term of linear matrix inequalities (LMIs). For all admissible uncertainties and delays, the controller guarantees not only the asymptotic stability of the system but also the prescribed H∞ attenuation level. In addition, the effectiveness of the proposed design method is demonstrated by a numerical example.     

考虑时延与丢包的网络控制系统分析与综合

针对具有时变网络诱导时延和丢包问题的网络控制系统稳定性分析与控制器设计问题,通过考虑网络诱导时延是时变和有界的情形,并分析网络诱导时延与其上界之间的关系,应用Lyapunov-Krasovskii泛函结合积分不等式方法,提出了一种改进的、同时考虑了网络诱导时延和丢包问题的网络控制系统稳定条件,并基于改进的锥补线性化迭代算法（improved cone complementary linearization, ICCL）给出了一种具有更低保守性的控制器设计方法。数值实例表明上述方法的有效性。     

随机时延网络控制系统的鲁棒H∞状态反馈控制

研究了含有双随机时延的不确定网络控制系统的鲁棒H_∞状态反馈控制问题。将传感器到控制器和控制器到执行器的网络时延建模为相互独立的连续时间离散状态的马尔可夫随机过程。基于此网络环境,构造时延依赖的控制器,将不确定网络控制系统转化为马尔可夫跳变系统。通过Lyapunov Krasovskii泛函方法和新的矩阵不等式技术,给出了系统随机稳定且满足H_∞性能的充分条件,并以矩阵不等式形式给出了相应的控制器设计方法。最后,给出了仿真算例,验证了该方法的有效性。     

时滞细胞神经网络的全局渐近鲁棒稳定性分析

针对一类具有时滞的细胞神经网络系统,利用新的Lyapunov Krasovskii函数,给出了系统全局渐近鲁棒稳定的时滞相关稳定性条件。其结果以线性矩阵不等式的形式给出,可以很容易求出系统稳定的时滞上界。进而可以很容易得到时滞无关稳定性结果,且该结果包含了现有文献中许多关于时滞无关稳定性分析的结果。数值算例说明了结论的有效性。