一类区间时变时滞T-S模糊系统的鲁棒控制

针对一类区同时变时滞T-S模糊系统,研究了其时滞相关渐近稳定性以及控制器设计问题.基于Lyapunov稳定性理论和线性矩阵不等式(LMI)工具,并结合自由权矩阵方法,设计一个包含时滞区间均值在内的新Lyapunov-Krasovskii泛函,给出了改进的时滞T-S模糊系统渐近稳定的时滞相关准则.同时,根据并行分布补偿算法,给出了带有记忆的状态反馈模糊控制器的设计方法.最后,实例仿真表明了方法的有效性.     

一类线性时滞系统的鲁棒稳定性分析

针对一类具有范数有界不确定性和2个继发时变时滞的线性时滞不确定系统,研究了其时滞依赖鲁棒稳定性问题.通过定义充分利用时变时滞上下界信息的新型Lyapunov-Krasovskii泛函,并结合时滞系统相关处理方法和线性矩阵不等式方法,得到了时滞线性不确定系统鲁棒渐近稳定所满足的条件.为了降低结论的保守性,对某些项进行了较紧致的估计.此外,并未引入自由权矩阵.最后并通过2个数值仿真证实了方法的有效性和优越性.     

变时滞不确定中立型系统鲁棒稳定新判据

在工程实际当中,时变时滞和不确定的存在往往使得系统的性能变差甚至不稳定。针对一类含混合变时滞的不确定中立系统,研究了时滞相关鲁棒稳定性问题。在考虑不确定性为泛数有界的条件下,首先通过构造包含三重积分项的Lyapunov-Krasovskii(L-K)的泛函,其次利用新的积分不等式更紧的界定条件,引入相关项自由权矩阵的方法,处理泛函沿系统的导数产生的交叉项,建立了基于线性矩阵不等式(LMI)形式的鲁棒稳定新判据。该方法不涉及复杂的模型变换,减小了理论推导和计算上的复杂性,所提出判据与离散时滞和中立时滞均相关,且扩大了系统稳定所允许的最大时滞上界范围,具有更低的保守性。仿真算例表明所提出的稳定性判据是有效的。     

时变时滞Lurie非线性系统绝对稳定新判据

针对时变时滞Lurie非线性系统,应用增广Lyapunov-Krasovskii泛函结合自由权矩阵方法,研究其时滞相关绝对稳定性问题.通过保留Lyapunov-Krasovskii泛函导数中常被忽略的有用信息,充分考虑时变时滞、时滞上界及它们的差三者之间的关系,得到了具有更低保守性的基于线性矩阵不等式的时滞相关绝对稳定条件.数值实例表明,该方法得出的结果优于已有文献的结果.     

基于改进自由权矩阵方法的神经网络时滞相关稳定性分析

针对具有不确定参数的时变时滞神经网络系统,利用改进的自由权矩阵方法,研究其时滞相关稳定性问题。通过考虑时变时滞及其上界和它们的差三者之间关系,同时保留Lyapunov—Krasovskii泛函导数中的有用项,得到具有更低保守性的基于线性矩阵不等式的神经网络系统时滞相关渐近稳定的充分条件。最后,数值例子表明该方法的有效性。     

含未知输入的时滞系统的函数观测器及输出反馈镇定

考虑了含未知输入的时滞系统的线性函数观测器设计.在一个不失一般性的秩条件假定下,以线性矩阵不等式(LMI)的形式给出了观测器存在的时滞无关型及时滞相关型判据,进而得到函数观测器改进的设计方法.此外,还讨论了降维状态观测器的设计,给出了基于观测器的反馈镇定控制器,实现了闭环的特征根分离及内稳定.具体算例说明了本文方法的有效性.     

基于T—S的时滞模糊系统的鲁棒稳定与镇定问题

讨论同时具有输入及状态时滞且多个范数有界不确定的非线性时滞模糊系统的时滞相关鲁棒稳定及镇定问题。利用通用的Lyapunov—Krasovskii泛函方法,结合自由权矩阵思想和对不确定项的更精确描述,获得基于线性矩阵不等式的时滞相关稳定的充分条件并给出状态反馈控制器的设计。该条件较已有结论不仅形式简单,而且具有更小的保守性。利用Matlab软件中的LMI工具箱求解,得到保证系统鲁棒渐近稳定的最大可允许时滞上界。数值算例表明该方法是有效性的。     

不确定时滞系统的稳定条件

利用比较定理、矩阵范数和矩阵测度的有关性质,提出了简单不确定时滞系统及对称组合不确定时滞系统的稳定条件.指出若带有时滞的系统稳定,则去掉时滞时系统一定稳定.在组合系统的情况下给出了时滞相关型的稳定条件.所研究对象的不确定矩阵的范数有一定限制.     

具有混合故障模型的时滞系统的可靠控制

针对线性定常时滞系统,基于Lyapunov稳定性理论,讨论考虑执行器具有混合故障的系统存在可靠控制器的充分条件,并结合时滞系统相关处理方法和线性矩阵不等式完成状态反馈可靠控制器的设计.数值仿真验证了本文控制器设计方法的可行性.     

不确定多状态滞后系统时滞相关鲁棒稳定与镇定

针对具有范数有界参数不稳定性的多态性滞后系统,本文提出了与系统时滞相关的鲁棒稳定性判据,并给出了一种无记忆的时滞相关的鲁棒稳定控制率的设计方法,本文的结果与系统的时滞大小有关,并采用ＬＭＩ描述。     

Delay-range-dependent stability criterion for interval time-delay systems with nonlinear perturbations

In this paper, we consider the problem of robust stability for a class of linear systems with interval time-varying delay under nonlinear perturbations using Lyapunov-Krasovskii (LK) functional approach. By partitioning the delay-interval into two segments of equal length, and evaluating the time-derivative of a candidate LK functional in each segment of the delay-interval, a less conservative delay-dependent stability criterion is developed to compute the maximum allowable bound for the delay-range within which the system under consideration remains asymptotically stable. In addition to the delay-bi-segmentation analysis procedure, the reduction in conservatism of the proposed delay-dependent stability criterion over recently reported results is also attributed to the fact that the time-derivative of the LK functional is bounded tightly using a newly proposed bounding condition without neglecting any useful terms in the delay-dependent stability analysis. The analysis, subsequently, yields a stable condition in convex linear matrix inequality (LMI) framework that can be solved non-conservatively at boundary conditions using standard numerical packages. Furthermore, as the number of decision variables involved in the proposed stability criterion is less, the criterion is computationally more effective. The effectiveness of the proposed stability criterion is validated through some standard numerical examples.     

New delay-dependent stability results for discrete-time recurrent neural networks with time-varying delay

This paper studies the problem of stability analysis for discrete-time recurrent neural networks (DRNNs) with time-varying delays. By using the discrete Jensen inequality and the sector bound conditions, a new less conservative delay-dependent stability criterion is established in terms of linear matrix inequalities (LMIs) under a weak assumption on the activation functions. By using a delay decomposition method, a further improved stability criterion is also derived. It is shown that the newly obtained results are less conservative than the existing ones. Meanwhile, the computational complexity of the newly obtained stability conditions is reduced since less variables are involved. A numerical example is given to illustrate the effectiveness and the benefits of the proposed method.     

Further improvement of stability criterion and BRL for Markovian jump systems with interval time-varying delay

This paper deals with delay-dependent stochastic stability and bounded real lemma(BRL)for Markovian jump linear systems with interval time-varying delays.By constructing some new Lyapunov functionals and using the Jensen’s integral inequality method,the free weighting matrix method,the convex combination method and the delay decomposition approach integratedly,some less conservative delay-dependent stability criteria and BRL are established. Numerical examples are given to show the effectiveness of the proposed method.     

Improved delay-dependent stability criteria for neutral-type systems with time-varying delays: a delayed decomposition approach

This paper discusses the neutral system with time-varying delay. Firstly, by developing a delayed decomposition approach and introducing integral inequality approach, the information of the delayed plant states can be taken into full consideration, and new delay-dependent sufficient stability criteria are obtained in terms of linear matrix inequalities (LMIs). Then, based on the Lyapunov method, delay-dependent stability criteria are devised by taking the relationship between the terms in the Leibniz–Newton formula into account. The criteria are derived in terms of LMIs, which can be easily solved by using various convex optimization algorithms. Three illustrative numerical examples are given to show the less conservatism of our obtained results and the effectiveness of the proposed method.     

含时变时延的多智能体的包容控制器设计

针对一类含时变通讯时延的多智能体系统,基于时滞依赖法提出了其在有向网络拓扑下的一类包容控制器设计的方法,该设计能有效地驱使多智能体系统中所有跟随者的状态渐近一致地收敛到领导者运动过程中形成的几何凸包．结合李亚普诺夫稳定性理论和线性矩阵不等式（LMI）方法,推导了多智能体系统包容控制率存在的充分条件,并将包容控制器的设计最终转化成求解线性矩阵不等式可行解的问题．结果表明,该方法对多智能体系统中的时变通讯时延具有良好的补偿效果．最后通过仿真算例验证了此方法的有效性和可行性．     

Delay-dependent exponential stability for uncertain neutral stochastic neural networks with interval time-varying delay

This paper is mainly concerned with the problem for the robustly exponential stability in mean square moment of uncertain neutral stochastic neural networks with interval time-varying delay. With an appropriate augmented Lyapunov–Krasovskii functional (LKF) formulated, the convex combination method is utilised to estimate the derivative of the LKF. Some new delay-dependent exponential stability criteria for such systems are obtained in terms of linear matrix inequalities, which involve fewer matrix variables and have less conservatism. Finally, two illustrative numerical examples are given to show the effectiveness of our obtained results.     

New LMT-based delay-dependent criterion for global asymptotic stability of cellular neural networks

The problem of global asymptotic stability analysis is studied for a class of cellular neural networks with time-varying delay. By defining a Lyapunov–Krasovskii functional, a new delay-dependent stability condition is derived in terms of linear matrix inequalities. The obtained criterion is less conservative than some previous literature because free-weighting matrix method and the Jensen integral inequality are considered. Three illustrative examples are given to demonstrate the effectiveness of the proposed results.