滞后动态系统广义指数稳定的充要条件

本语文针对一般的滞后动态系统建立了广义指数稳定性的充分和必要条件，并由所建立的充要条件得出了系统过渡过程的时变指数衰减估计，作为所建结果的应用，基于矩阵工给出了一类滞后动态系统过渡过程的相应指数衰减估计，本文揭示了所建衰减估计可好于那些仅基于充分稳定性条件所得的估计。     

一类线性时变大系统的运动稳定性

本文运用向量李雅普诺夫函数和比较原理的方法研究一类线性时变大系统的运动稳定性同时扩大了文[1]所研究的n阶常系数线性方程组和文[2]所研究的一类时变大系统的参数稳定性区域。     

String stability of infinite-dimension stochastic interconnected large-scale systems with time-varying delay

The exponential string stability for a class of nonlinear interconnected large-scale systems with time-varying delay is analysed by using the box theory and constructing a vector Lyapunov function. Under the assumption that the time delay is bounded and continuous, a criterion for exponential string stability of the systems is obtained by analysing the stability of differential inequalities with time-varying delay. The large-scale system is exponential string stable when the conditions associating with the coefficient matrices of the system and the solutions of the Lyapunov equations, interconnected with the system, are satisfied. Since it is independent of the delays and simplifies the calculation, the criterion is easy to apply.     

Growth conditions for exponential stability of time-varying perturbed systems

In this paper, we derive some sufficient conditions for practical uniform exponential stability of time-varying perturbed systems based on Lyapunov techniques, whose dynamics are in general unbounded in time, in the sense that the solutions are uniform stable and converge to a small neighbourhood of the origin. Under quite general assumptions, we first present a new converse stability theorem for a large class of time-varying systems, which will be used to prove certain stability properties of nonlinear systems with perturbation. Therefore, a new Lyapunov function is presented that guarantees practical uniform exponential stability of perturbed systems. Furthermore, some illustrative examples are presented.     

An improved stability test and stabilisation of linear time-varying systems governed by second-order vector differential equations

In this article, the problems of exponential stability analysis and stabilisation of linear time-varying systems described by a class of second-order vector differential equations are considered. Using bounding techniques on the trajectories of a linear time-varying system, the stability problem of the time-varying system is transformed to that of a time-invariant system and a new sufficient condition for the exponential stability is obtained. Moreover, the new criterion is proven to be superior to a test presented in the recent literature. Finally, the proposed criterion is applied to the exponential stabilisation problem via state feedback. The results are illustrated by several numerical examples.     

Robust stability of discrete systems

The objective of this paper is to show how to choose a Liapunov function to obtain the best and sometimes exact estimates of the degree of exponential stability for linear time-invariant discrete systems. The choice is interesting because it is also shown that it provides the largest robustness bounds on non-linear time-varying perturbations which can be established by either norm-like or quadratic Liapunov functions. By applying the results obtained to large-scale systems, where the role of perturbations is played by the interconnections among the subsystems, the least conservative stability conditions are derived for the overall system which are available in the context of vector Liapunov functions and M-matrices.     

Global exponential stability of Hopfield reaction-diffusion neural networks with time-varying delays

The authors analyze the existence of the equilibrium point and global exponential stability for Hopfield reaction-diffusion neural networks with time-varying delays by means of the topological degree theory and generalized Halanay inequality. Since the diffusion phenomena and time delay could not be ignored in neural networks and electric circuits, the model presented here is close to the actual systems, and the sufficient conditions on global exponential stability established in this paper, which are easily verifiable, have a wider adaptive range.     

Exponential stability and stabilization of uncertain linear time-varying systems using parameter dependent Lyapunov function

In this paper, the problem of exponential stability and stabilization for a class of uncertain linear time-varying systems is considered. The system matrix belongs to a polytope and the time-varying parameter as well as its time derivative are bounded. Based on a time-varying version of Lyapunov stability theorem, new sufficient conditions for the exponential stability and stabilization via parameter dependent state feedback controllers (i.e., a gain scheduling controllers) are given. Using parameter dependent Lyapunov function, the conditions are formulated in terms of two linear matrix inequalities without introducing extra useless decision variables and hence are simply verified. The results are illustrated by numerical examples.     

线性定常大系统参数稳定域的一个新结论

本文应用标量李亚普诺夫函数分解法结合Balley不等式对线性定常大系统的参数稳定域进行了讨论,得到参数稳定域的一种新形式,并以具有两个子系统的n阶大系统为例,指出新的参数稳定域与用向量李亚普诺夫函数分解法得到的参数稳定域互不包含这一新的结论。     

Nonlinear measures: a new approach to exponential stabilityanalysis for Hopfield-type neural networks

In this paper, a new concept called nonlinear measure is introduced to quantify stability of nonlinear systems in the way similar to the matrix measure for stability of linear systems. Based on the new concept, a novel approach for stability analysis of neural networks is developed. With this approach, a series of new sufficient conditions for global and local exponential stability of Hopfield type neural networks is presented, which generalizes those existing results. By means of the introduced nonlinear measure, the exponential convergence rate of the neural networks to stable equilibrium point is estimated, and, for local stability, the attraction region of the stable equilibrium point is characterized. The developed approach can be generalized to stability analysis of other general nonlinear systems.     

Stability problem of a periodically varying system

In this paper we investigate the problem of stability for periodically time-varying systems. This study is needed, for instance, to determine robustness and stability of repetitive learning systems used in the control of complex systems such as robotic manipulators. We use classical and new results for the stability of linear time-varying systems to re-establish an upper bound on the rate of parameter variations of the periodically time-varying systems, We then examine in detail the effects of these variations on the asymptotic and exponential stability of a special class of systems.     

Coherence,vector Liapunov functions and large-scale power systems

Large-scale power systems considered in this paper can be decomposed into their coherent part of the reduced dimension and the non-coherent one. The coherence property of the former is used for the first hierarchical level aggregation of the system. A new system is obtained with essentially reduced order, which is then aggregated on the second hierarchical level by applying the vector Liapunov function concept of Bellman.

A new vector Liapunov function aggregation form is developed to suit the properties of the coherent large-scale power systems, which require also usage of new comparison functions. As a result, a one-shoot stability test on the higher hierarchical level is established. The criterion is stated in terms of negative definiteness of a symmetric aggregation matrix of the order equal to the number of subsystems of the reduced order system. Essential order reduction is achieved.

The theory developed in the paper is illustrated by an example.     

Stabilization of sets with application to multi-vehicle coordinated motion

In this paper, we develop stability and control design framework for time-varying and time-invariant sets of nonlinear dynamical systems using vector Lyapunov functions. Several Lyapunov functions arise naturally in multi-agent systems, where each agent can be associated with a generalized energy function which further becomes a component of a vector Lyapunov function. We apply the developed control framework to the problem of multi-vehicle coordinated motion to design distributed controllers for individual vehicles moving in a specified formation. The main idea of our approach is that a moving formation of vehicles can be characterized by a time-varying set in the state space, and hence, the problem of distributed control design for multi-vehicle coordinated motion is equivalent to the design of stabilizing controllers for time-varying sets of nonlinear dynamical systems. The control framework is shown to ensure global exponential stabilization of multi-vehicle formations. Finally, we implement the feedback stabilizing controllers for time-invariant sets to achieve global exponential stabilization of static formations of multiple vehicles.     

传感器失效不确定时滞系统指数稳定可靠控制

针对一类含有时变时滞的不确定参数线性系统,研究了在传感器发生故障情况下系统指数稳定鲁棒可靠控制器设计问题。系统中的参数不确定性满足广义匹配条件,时变时滞及其变化率有界,并假设故障传感器元件的输出为零。经过适当的状态变换,将原系统的指数稳定鲁棒可靠控制问题转化为另一个等价系统的鲁棒可靠控制问题。根据Lyapunov稳定性理论,得到了系统存在指数稳定鲁棒可靠控制器应满足的一个矩阵不等式。为了便于数值求解,将该矩阵不等式转化为线性矩阵不等式（LMI）,并给出了可靠控制器的设计方法和步骤。利用该文方法设计的指数稳定鲁棒可靠控制器能够使得时滞系统对于任意允许的不确定性以及传感器失效都具有指定衰减度的渐近稳定性。数值算例说明了所提出设计方法的有效性。     

Robust exponential stability of time-varying linear systems

This paper investigates the robustness of time-varying linear systems under a large class of complex time-varying perturbations. Previous results⁸ which were restricted to bounded linear perturbations of output feedback type are generalized to unbounded and nonlinear perturbations of multi-output feedback type. We establish a lower bound for the stability radius of these systems and show how it may be possible to improve the bound using time-varying scalar transformations of the state, input and output variables. The results are applied to derive Gershgorin type stability criteria for time-varying linear systems.     

Stability analysis of large-scale systems with stable and unstable subsystems

Sufficient conditions are given for both exponential and asymptotic stability of time-varying non-linear large-scale systems composed of stable and unstable subsystems. Sign-negative coupling among the subsystems, which can be of arbitrary order and interconnected in arbitrary fashion, is allowable. Under the conditions the required stability property of the overall system is implied by the stability properties of all its subsystems and global features of their interactions. The interactions can be expressed in terms of time-varying, sign-indefinite functions rather than only in terms of time-invariant positive definite functions. Three examples are worked out to illustrate application of- the results.     

Exponential stability of semi-Markovian jump generalized neural networks with interval time-varying delays

This draft addresses the exponential stability problem for semi-Markovian jump generalized neural networks (S-MJGNNs) with interval time-varying delays. The exponential stability conditions are derived by establishing a suitable Lyapunov–Krasovskii functional and applying new analysis method. Improved results are obtained to guarantee the exponential stability of S-MJGNNs through improved reciprocally convex combination and new weighted integral inequality techniques. The method in this paper shows the advantages over some existing ones. To verify the advantages and benefits of employing proposed method is explained through numerical examples.

     

Extension of Popov absolute stability criterion to non-autonomous systems with delays

This paper extends in a simple way the classical absolute stability Popov criterion to multivariable systems with delays and with time-varying memoryless non-linearities subject to sector conditions. The proposed sufficient conditions are expressed in the frequency domain, a form well-suited for robustness issues, and lead to simple graphical interpretations for scalar systems. Apart from the usual conditions, the results assume basically a generalized sector condition on the derivative of the non-linearities with respect to time. Results for local and global stability are given, the latter concerning in particular the linear time-varying ones. For rational transfers, the frequency conditions are equivalent to some easy-tocheck linear matrix inequalities:this leads to a tractable method of numerical resolution by rational approximation of the transfer. As an illustration, a numerical example is provided.     

时滞非线性随机大系统的指数稳定性

建立了一般随机泛函微分方程p阶均值指数稳定与几乎必然指数稳定的新型判据, 然后应用所得判据到具有可变多时滞的非线性随机大系统, 得到了这种随机大系统时滞无关的均方指数稳定与几乎必然指数稳定的代数判据.     

New sufficient conditions for the stability of slowly varyinglinear systems

The frozen-time approach is used to state some new sufficient conditions for the stability of linear time-varying systems. An upper bound on the norm of the time derivative of system matrix which, under different assumptions on frozen-time system eigenvalues, guarantees asymptotic stability or exponential stability of the system is established