对带控制器饱和的Markovian跳跃双线性系统稳定时滞估计

研究了带有饱和控制器的时滞Markovian跳跃双线性系统随机镇定问题. 文章先给出了采用无记忆控制的相应无时滞系统局部指数稳定的充分性条件, 然后给出了采用该无记忆控制的时滞系统保持随机稳定性的最大时滞上界估计. 数值算例验证了该方法的有效性.     

脉冲时滞Hopfield神经网络的全局指数稳定性

研究一类具有脉冲控制的时滞Hopfideld神经网络的全局指数稳定性,通过Lyapunov-Krasovskii稳定性理论和Halanay不等式等方法,构造合适的Lyapunov泛函,利用不等式技巧得到了确保时滞神经网络在脉冲控制下全局指数稳定的一个充分条件,保证了Hofidd神经网络在脉冲控制下的全局指数稳定,并估计了系统的指数收敛率.为了便于计算和验证结论的有效性,给出一个简化的充分条件.最后通过数值实例的实验仿真证实了结论的有效性、可行性.     

离散广义时滞系统的时滞依赖稳定性分析

讨论离散广义时滞系统的稳定性问题. 在不使用系统分解和等价转换的情况下, 利用线性矩阵不等式方法, 给出保证系统正则、因果和稳定的时滞依赖条件. 与已有的方法相比, 本文的方法更加充分地利用时滞的信息, 因此所得结果具有较小的保守性. 数值例子说明本文结果的有效性.     

一类不确定中立型系统的时滞相关稳定准则

本文讨论了一类定常系数时变时滞中立型系统的时滞相关稳定性. 以线性矩阵不等式形式给出了新的时滞相关渐近稳定标准. 二个数值例子表明本文结果比先前结论有较小的保守性.     

时滞诱发的忆阻型Hopfield神经网络的复杂动力学

本文研究含时滞的忆阻型环状Hopfield神经网络的稳定性、Hopf分岔以及复杂振荡模式.根据特征方程根分布情况,获得了系统全时滞稳定条件和与时滞相关的稳定条件.通过数值计算揭示了丰富的动力学现象,如多种周期运动和混沌吸引子等,并给出了Poincaré截面上的分岔图.设计了电路实验平台,取得了与理论分析和数值计算高度吻合的实验结果.     

离散时滞大系统的无条件稳定性

本文研究一类线性定常离散时滞大系统的无条件稳定性问题。首先利用m阵的性质,给出了一般离散时滞系统无条件渐近稳定的充分条件;接着建立了适应于离散时滞系统的比较原理,最后用向量李雅普诺夫函数法和集结(aggregatioa)方法,推得了线性定常离散时滞大系统无条件稳定的充分条件。这一条件归结为判定一个阶数等于子系统个数的实矩阵是否是一个m阵。一个简单的数值例子说明了本文得出的结果的应用。     

具有时滞的不确定鲁里叶控制系统的绝对鲁棒稳定性

讨论了具有时滞的非线性不确定鲁里叶控制系统的鲁棒绝对稳定性问题,应用Bellman-Gronwell不等式和Lyapunov泛函方法研究了不确定鲁里叶控制系统的鲁棒绝对稳定性并给出了系统的滞相关稳定和时滞无关稳定的充分判据,运用这些条件可以直接估计具有时滞的非线性不确定鲁里叶控制系统的鲁棒绝对稳定界和时滞界。     

时变中立型Lurie系统的稳定性分析

文章考虑时变时滞的中立型Lurie系统的绝对稳定性问题。系统的中立时滞是常时滞,离散时滞是变时滞,系统的变时滞上界为一个未知的常数。在无限的扇形区间条件下,将变时滞区间划分成小的片段。通过利用Lyapunov-Krasovskii函数引入自由权矩阵的方法,并进行时滞分解,从而得到使系统绝对稳定的充分条件。最后给出数值算例,证实算法的有效性。     

单观测时滞线性不确定系统最优鲁棒估计

针对带有单个观测时滞的线性不确定系统, 最优鲁棒估计问题被考虑. 基于新息重组分析的方法, 给出最优鲁棒估计器. 它的计算最后归结为计算与原始系统同维的两个 Riccati 方程和一个 Lyapunov 递推等式. 我们给出一个数值例子来验证所提出新方法的有效性.     

非相称多时滞奇异系统的有记忆状态反馈控制

针对一类非相称多时滞奇异系统, 研究其时滞相关稳定性问题. 给出了易于数值检验的时滞无关正则条件. 基于Lyapunov-Krasovskii泛函方法和广义积分引理给出了系统时滞相关稳定的充分条件. 本文的主要思想是利用矩阵不等式方法, 设计有记忆状态反馈控制器, 使相应的闭环系统时滞无关正则、无脉冲、渐进稳定, 并直接给出了有记忆状态反馈控制器参数化的表达形式. 最后通过数值仿真验证了所提方法的有效性.     

Improved global robust asymptotic stability criteria for delayed cellular neural networks.

This paper considers the problem of global robust stability analysis of delayed cellular neural networks (DCNNs) with norm-bounded parameter uncertainties. In terms of a linear matrix inequality, a new sufficient condition ensuring a nominal DCNN to have a unique equilibrium point which is globally asymptotically stable is proposed. This condition is shown to be a generalization and improvement over some previous criteria. Based on the stability result, a robust stability condition is developed, which contains an existing robust stability result as a special case. An example is provided to demonstrate the reduced conservativeness of the proposed results.     

非线性奇摄动系统的小增益增长条件

给出小增益增长条件使得在此条件下快慢子系统的渐近稳定性能够保证其原奇摄动系统的相应稳定性,并给出估计摄动参数的稳定界的解析表示及其应用例子.     

Computation of robust stability bounds for time-delay systems with nonlinear time-varying perturbations

This paper is concerned with the computation of robust stability bounds for time-delay systems with nonlinear time-varying perturbations. Firstly, a delay-independent condition on the robust stability is presented and a method to determine the maximum upper bound of robust stability is given. Then, a delay-dependent robust stability condition is provided. All results are given in terms of linear matrix inequalities where efficient solution procedures are available. Numerical examples have shown that the results are less conservative than some previous established bounds.     

Improved delay-dependent stability criteria for time-delay systems

This note provides an improved asymptotic stability condition for time-delay systems in terms of a strict linear matrix inequality. Unlike previous methods, the mathematical development avoids bounding certain cross terms which often leads to conservatism. When time-varying norm-bounded uncertainties appear in a delay system, an improved robust delay-dependent stability condition is also given. Examples are provided to demonstrate the reduced conservatism of the proposed conditions.     

A necessary and sufficient condition for robust asymptoticstability of time-variant discrete systems

A necessary and sufficient condition for the stability of time-variant interval matrices is presented. This condition allows stability to be tested by checking only products of vertex (extreme) matrices. The implementation of the test in the form of an algorithm and two illustrative examples are provided     

Stability of Neutral Impulsive Nonlinear Stochastic Evolution Equations with Time Varying Delays

In this paper, we consider the stability of mild solutions to neutral impulsive nonlinear stochastic evolution equations with time varying delays. With the non‐Lipschitz condition, the Lipschitz condition being taken as a special case, on the impulsive term, the existence, uniqueness and sufficient conditions for the exponential stability in the pth moment and the almost sure exponential stability of the mild solutions are derived by employing a fixed point approach. An example is provided to illustrate the efficiency of the obtained theorems.     

Stability tests and stabilization for piecewise linear systems based on poles and zeros of subsystems

This paper provides several stability tests for piecewise linear systems and proposes a method of stabilization for bimodal systems. In particular, we derive an explicit and exact stability test for planar systems, which is given in terms of coefficients of transfer functions of subsystems. Restricting attention to the bimodal and planar case, we show simple stability tests. In addition, we drive a necessary stability condition and a sufficient stability condition for higher-order and bimodal systems. They are given in terms of the eigenvalue loci and the observability of subsystems. All the stability tests provided in this paper are computationally tractable, and our results are applied to the stabilizability problem. We confirm the exactness and effectiveness of our approach by illustrative examples.     

Stability analysis for fractional-order neural networks with time-varying delay

This paper focuses on the stability analysis for fractional-order neural networks with time-varying delay. A novel Lyapunov's asymptotic stability determination theorem is proved, which can be used for fractional-order systems directly. Different from the classical Lyapunov stability theorem, constraint condition on the derivative of Lyapunov function is revised as an uniformly continuous class-K function in the fractional-order case. Based on this novel Lyapunov stability theorem and free weight matrix method, a new sufficient condition on Lyapunov asymptotic stability of fractional-order Hopfield neural networks is derived by constructing a suitable Lyapunov function. Moreover, two numerical examples are provided to illustrate the effectiveness of these criteria.     

具有多个时滞的积分时滞系统的稳定性分析

首先,针对具有多个时滞的积分时滞系统,建立新的基于线性矩阵不等式的稳定性条件.该条件与正整数k有关,给出$k=1$时该条件与现有结果间的关系.该关系表明所提出条件在$k\geqslant2$时的保守性比现有结果小;然后,基于所提出的稳定性条件,进一步研究具有参数不确定性的积分时滞系统的鲁棒稳定性问题,建立基于线性矩阵不等式的充分条件;最后,利用所提出方法,研究具有多个离散时滞和分布时滞的积分时滞系统的稳定性问题.数值算例结果表明了所提出稳定性判据的有效性.     

New Exponential Estimates for Time-Delay Systems

This note considers the problem of exponential stability for time-delay systems. In terms of linear matrix inequalities, a new sufficient condition for exponential stability is obtained. Based on this, an improved upper bound of the decay rate can be easily calculated. When time-varying norm-bounded parameter uncertainties appear, a new sufficient condition for robust exponential stability of uncertain time-delay systems is also provided. The reduced conservatism of the proposed conditions is illustrated via two numerical examples.