时滞切换系统指数稳定性分析: 多Lyapunov函数方法

将多 Lyapunov 函数方法推广至时滞情形, 分析切换与时滞对于稳定性的影响. 以 Halanay 不等式为引理, 给出了与时滞相关的切换序列约束条件, 以保证系统的指数稳定性. 若时滞项消失, 本文关于切换对于稳定性影响的分析与无时滞情形的相关结论是一致的. 仿真结果说明了本文方法的有效性.     

模型相关时变时滞马尔可夫跳变系统低保守稳定性

本文研究了时变时滞与模型相关的随机马尔可夫跳变系统的时滞相关稳定性问题. 通过建立时变时滞与模型相关的系统模型, 构造不同的Lyapunov-Krasovskii函数, 并通过引入改进的积分等式, 以线性矩阵不等式的形式提出了具有较小保守性的时滞依赖稳定性条件. 最后用几个数值算例说明本文结论的有效性及较低的保守性.     

不确定奇异时滞系统的时滞相关型鲁棒∞弹性控制

讨论了不确定奇异时滞系统的时滞相关型鲁棒弹性控制器设计问题.在一个关于标称奇异时滞系统的新的时滞相关型稳定性判据的基础上给出了一种新的有界实引理(BRL:bounded real lemma);基于此给出了时滞相关型鲁棒弹性控制器存在的充分性条件,最后通过数值算例说明本文结果的有效性.     

多时变时滞系统的鲁棒稳定及有界实引理的时滞相关条件

对于多时变时滞系统,引入表示牛顿-莱布尼兹公式中各项的相互关系的自由权矩阵,获得了基于线性矩阵不等式(LMI)描述的系统鲁棒稳定的时滞相关条件,并说明了时滞相关条件和时滞无关条件的相互关系.在此基础上,将其推广到有界实引理的时滞相关条件.所得结果克服了已有结果的保守性.最后给出实例说明本文方法的有效性.     

线性时滞系统的时滞相关鲁棒控制

讨论了同时具有输入时滞与状态时滞的线性系统的时滞相关鲁棒控制问题.将矩阵分解思想应用于线性时滞系统的控制综合,借助于积分不等式,利用Lyapunov_Krasovskii泛函方法,得到了系统经无记忆状态反馈后可镇定的、基于LMI的时滞相关条件.既不要对原系统进行模型变换,也不要对交叉项进行界定.最后的实例说明了本文方法的有效性.     

一类新的Takagi-Sugeno模糊时滞系统的稳定性准则

本文提出一种新的时滞划分方法—变时滞划分法,以解决连续延时Takagi-Sugeno模糊系统的稳定性和镇定性问题.不同于已有的文献,用可变参数将时变时滞区间[0,d(t)]划分为若干个可变子区间,并得出模糊时滞系统的新的时滞相关稳定性准则.本文提出的新方法能充分利用时滞子区间的内部信息,因此新的时滞相关稳定性准则比以往结果具有更小的保守性.基于Lyapunov稳定性理论,以线性矩阵不等式形式给出T--S模糊系统的新的时滞相关稳定性准则,并将稳定性和镇定性研究结果扩展到具有不确定参数的T--S模糊系统.仿真实例证明了本文方法降低保守性的有效性.     

LURIE控制系统的时滞相关绝对稳定性判据

1 引言关于具有时滞的Lurie控制系统的绝对稳定性的讨论已有不少结果[1～4],其绝对稳定性条件有时滞无关条件和时滞相关条件两种.由于时滞无关条件缺少了时滞的信息,因此必然会使其稳定性具有保守性.下面对具有多个时变时滞的Lurie控制系统,利用不同于文献[1]的方法进行讨论,给出系统绝对稳定的时滞相关判据.算例表明,与文献[1]的结果相比本文结果可降低保守性.     

一类具有区间时变多状态时滞系统的稳定性分析

研究一类具有区间时变多状态时滞且时滞导数不确定的系统的稳定性问题. 通过选择合理的Lyapunov-Krasovskii函数结合辅助变量和广义状态法, 以LMI的形式给出了时滞相关的稳定性充分条件. 文中的结论对时滞的导数没有任何限制, 可用于具有快时变时滞系统. 与已有的相关研究成果相比, 结论更具有一般性, 保守性也更低. 最后通过仿真及数值算例说明了本文方法的有效性和优越性.     

随机时滞系统的时滞相关无源控制

研究随机时滞系统的时滞相关无源性分析和控制问题. 利用Lyapunov-Krasovskii方法和松弛矩阵方法, 得到时滞相关的无源性条件. 基于该条件设计时滞相关的随机无源控制器. 文中的结果以线性矩阵不等式(Linear matrix inequalities, LMIs)表示, 可以利用标准的凸优化算法进行有效求解. 通过一个数值例子说明本文方法的有效性.     

一类非线性广义系统的时滞相关耗散控制

针对一类带有非线性摄动的广义时滞系统,研究了时滞相关的鲁棒耗散问题.讨论了此类非线性广义时滞系统的鲁棒耗散性.同时对此类非线性广义时滞系统的二次稳定性进行了研究,分别用线性矩阵不等式（LMI）的方法给出了充分条件,也给出了时滞相关的鲁棒耗散的时滞上界.并且,给出了时滞相关的鲁棒耗散的状态反馈控制器.最后,通过例子验证了定理的可行性.     

Mahalanobis distance-based two new feature evaluation criteria

In this paper two Mahalanobis distance-based criteria are proposed for feature evaluation. Because of certain theoretical properties of these two criteria which are discussed in the paper, they are expected to perform better than the direct use of the Mahalanobis distance in a multiclass pattern recognition problem. Experimental results also suggest their superiority.     

离散Hopfield神经网络的稳定性研究

推广了前人关于离散Hopfield神经网络的稳定性定理及周期为2极限环的存在定 理,并从理论上给出了新的严格的证明.进一步,提出了关于部分变元稳定和部分变元为极限 环的新概念,并给出了判别定理.最后给出了几个有趣的例子,揭示这类网络渐近行为的复杂 性.     

离散Hopfield神经网络的 稳定性研究1)

推广了前人关于离散Hopfield神经网络的稳定性定理及周期为2极限环的存在定理,并从理论上给出了新的严格的证明.进一步,提出了关于部分变元稳定和部分变元为极限环的新概念,并给出了判别定理.最后给出了几个有趣的例子,揭示这类网络渐近行为的复杂性.     

On the stability of uncertain systems with multiple time-varyingdelays

In this paper, criteria for the global asymptotic stability of a class of uncertain systems with multiple time-varying delays are proposed. Based on the improved Razumikhin-type theorem, delay-dependent and delay-independent criteria are provided to guarantee the global asymptotic stability of such systems. Our main results are generalizations of some recent results reported in the literature in the case with multiple time-varying delays. A numerical example Is also given to illustrate our results     

Effectiveness of involutive criteria in computation of polynomial Janet bases

In this paper, effectiveness of involutive criteria in the elimination of useless prolongations when computing polynomial Janet bases, which are typical representatives of involutive bases, is discussed. One of the results of this study is that the role of the criteria in an involutive algorithm is not as important as in the Buchberger algorithm. It is shown also that these criteria affect the growth of intermediate coefficients.     

具有任意未知常时滞系统的鲁棒稳定性(英)

本文采用李雅普诺夫泛函法和一个矢量不等式建立了若干具有任意未知常时滞系统的鲁棒稳定性判据．所获得结果是时滞无关的、文中示例说明了所得稳定性判据减少了现存结果的保守性．     

Stabilization of stochastically singular nonlinear jump systems with unknown parameters and continuously distributed delays

In this paper, the problem of robustly asymptotic stabilization for a class of stochastically nonlinear singular jump systems is investigated. The jumping parameters are modeled as a continuous-time, finite-state Markov chain. Based on the Lyapunov-Krasovskii functional and stochastic analysis theory as well as a state feedback control technique, some new sufficient conditions are derived to ensure the asymptotic stability of the trivial solution in the mean square. A key feature of this paper is that singular, nonlinear, noise perturbations, unknown parameters and continuously distributed delays are all considered. In particular, the obtained stabilization criteria in this paper are expressed in terms of LMIs, which can be solved easily by recently developed algorithms. Finally, two numerical examples are presented to illustrate the effectiveness of the theoretical results. Moreover, the second example shows that delay-dependent stabilization criteria are less conservative than delay-independent criteria.     

A new way to detect arrows in line drawings

A new way of detecting arrows in line drawings is proposed in this paper. We provide a set of criteria which are aggregated using the Choquet integral. These criteria are defined from the geometric properties of an arrow. Experimental results on two kinds of line-drawing documents show the interest of our approach.     

基于LMI方法的时滞细胞神经网络稳定性分析

神经网络是一个复杂的大规模非线性系统，而时滞神经网络的动态行为更为丰富和复杂．现有的研究时滞神经网络稳定性的方法中最为流行的是Lyapunov方法．它把稳定性问题变为某些适当地定义在系统轨迹上的泛函，通过这些泛函相应的稳定性条件就可以获得．该文得到了时滞细胞神经网络渐近稳定性的一些充分条件．作者利用了泛函微分方程的Lyapunov—Krasovskii稳定性理论和线性矩阵不等式(LMI)方法，精炼和推广了一些已有的结果．它们比目前文献报道的结果更少保守．该文还给出了确定时滞细胞神经网络稳定性更多的判定准则．     

A Study on Acquiring Underlying Behavioral Criteria for Manipulator Motion by Focusing on Learning Efficiency

Conventional humanoid robotic behaviors are directly programmed depending on the programmer's personal experience. With this method, the behaviors usually appear unnatural. It is believed that a humanoid robot can acquire new adaptive behaviors from a human, if the robot has the criteria underlying such behaviors. The aim of this paper is to establish a method of acquiring human behavioral criteria. The advantage of acquiring behavioral criteria is that the humanoid robots can then autonomously produce behaviors for similar tasks with the same behavioral criteria but without transforming data obtained from morphologically different humans every time for every task. In this paper, a manipulator robot learns a model behavior, and another robot is created to perform the model behavior instead of being performed by a person. The model robot is presented some behavioral criteria, but the learning manipulator robot does not know them and tries to infer them. In addition, because of the difference between human and robot bodies, the body sizes of the learning robot and the model robot are also made different. The method of obtaining behavioral criteria is realized by comparing the efficiencies with which the learning robot learns the model behaviors. Results from the simulation have demonstrated that the proposed method is effective for obtaining behavioral criteria. The proposed method, the details regarding the simulation, and the results are presented in this paper.