Passivity analysis for uncertain stochastic neural networks with discrete interval and distributed time-varying delays

The problem of passivity analysis is investigated for uncertain stochastic neural networks with discrete interval and distributed time-varying delays. The parameter uncertainties are assumed to be norm bounded and the delay is assumed to be time-varying and belongs to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. By constructing proper Lyapunov-Krasovskii functional and employing a combination of the free-weighting matrix method and stochastic analysis technique, new delay dependent passivity conditions are derived in terms of linear matrix inequalities (LMIs). Finally, numerical examples are given to show the less conservatism of the proposed conditions.     

一类Markov跳变神经网络的时滞相关鲁棒稳定性

针对一类Markov跳变神经网络,研究了其在系统参数不确定情况下的全局鲁棒稳定性。利用Leibniz Newton公式对原系统进行等价变换,基于Lyapunov 稳定性理论,并结合Moon不等式得到了此类Markov跳变神经网络时滞相关均方鲁棒稳定性的判别条件。所得结果以线性矩阵不等式(linear matrix inequality, LMI)的形式给出,容易被Matlab中的LMI工具箱验证。最后,通过一个算例验证了所得结论的有效性。     

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。     

Robust fuzzy control of Takagi-Sugeno fuzzy neural networks with discontinuous activation functions and time delays

The problem of global robust asymptotical stability for a class of Takagi-Sugeno fuzzy neural networks(TSFNN) with discontinuous activation functions and time delays is investigated by using Lyapunov stability theory.Based on linear matrix inequalities(LMIs),we originally propose robust fuzzy control to guarantee the global robust asymptotical stability of TSFNNs.Compared with the existing literature,this paper removes the assumptions on the neuron activations such as Lipschitz conditions,bounded,monotonic increasing property or the right-limit value is bigger than the left one at the discontinuous point.Thus,the results are more general and wider.Finally,two numerical examples are given to show the effectiveness of the proposed stability results.     

On delay-dependent robust stability for uncertain neutral systems

1.INTRODUCTION Time delaysarefrequentlyencounteredinvariousengi neeringsystems,includingaircraftstabilization,nuclear reactors,populationdynamicsmodels[1].Theirexistence isoftenthesourceofinstabilityinmanycontrolsystems.Stabilitycriteriafortime delaysystemscanbeclassified intotwocategories.Thestabilitycriteriathatincludein formationonthesizeofdelaysarereferredtoasdelay de pendentcriteria[2～18]andthecriteriaapplicabletoanar bitrarysizeofdelaysarereferredtoasdelay independent criteria[19～…     

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.     

Delay-dependent robust passivity control for uncertain time-delay systems

The robust passivity control problem is addressed for a class of uncertain delayed systems with time-varying delay. The parameter uncertainties are norm-bounded. First, the delay-dependent stability sufficient condition is obtained for the nominal system, and then, based-on the former, the delay-dependent robust passivity criteria is provided and the corresponding controller is designed in terms of linear matrix inequalities. Finally, a numerical example is given to demonstrate the validity of the proposed approach.     

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。     

区间时滞相关不确定奇异系统的鲁棒稳定性和镇定性

研究区间时滞相关的不确定时变时滞奇异系统的鲁棒稳定性和镇定性问题,不确定参数假设是范数有界的。充分利用时滞的下界信息构造Lyapunov函数,用严格的矩阵不等式给出系统对所有的容许不确定满足正则、无脉冲、稳定的新判据。基于这个判据,设计状态反馈控制器使得系统鲁棒稳定。数值例子说明所得结果具有更小的保守性。     

时滞竞争神经网络的全局指数稳定性

对于不同时标的时变时滞竞争神经网络的网络模型,通过构造适当的Lyapunov函数,结合微分不等式分析,研究了时变时滞竞争神经网络的全局指数稳定性,获得了新的全局指数稳定性判据,所得判据推广和改进了前人的相关结论。最后的数值仿真例子证明了该算法的有效性。     

两类不确定奇异时滞系统鲁棒稳定的相关型判据

研究了不确定奇异时滞系统的鲁棒稳定性问题。首先以线性矩阵不等式的形式给出了奇异时滞系统正则,无脉冲模且零解渐近稳定的一种新的时滞相关型判据。通过引入新的参数避免了利用不等式处理交叉项,从而使该判据具有较小的保守性。最后,利用研究结果,给出了两类不确定奇异时滞系统新的时滞相关型鲁棒稳定性判据。     

New type of adaptive control for a class of distributed time-delay systems with adaptation regard to delay parameter

The problem on stabilization for the system with distributed delays is researched. The distributed time-delay under consideration is assumed to be a constant time-delay, but not known exactly. A design method is proposed for a memory proportional and integral (PI) feedback controller with adaptation to distributed time-delay. The feedback controller with memory simultaneously contains the current state and the past distributedinformation of the addressed systems. The design for adaptation law to distributed delay is very concise. The controller can be derived by solving a set of linear matrix inequalities (LMIs). Two numerical examples are given to illustrate the effectiveness of the design method.     

Stability analysis and design of time-delay uncertain systems using robust reliability method

A robust reliability method for stability analysis and reliability-based stabilization of time-delay dynamic systems with uncertain but bounded parameters is presented by treating the uncertain parameters as interval variables.The performance function used for robust reliability analysis is defined by a delayindependent stability criterion.The design of robust controllers is carried out by solving a reliability-based optimization problem in which the control cost satisfying design requirements is minimized.This kind of treatment makes it possible to achieve a balance between the reliability and control cost in the design of controller when uncertainties must be taken into account.By the method,a robust reliability measure of the degree of stability of a time-delay uncertain system can be provided,and the maximum robustness bounds of uncertain parameters such that the time-delay system to be stable can be obtained.All the procedures are based on the linear matrix inequality approach and therefore can be carried out conveniently.The effectiveness and feasibility of the proposed method are demonstrated with two practical examples.It is shown by numerical simulations and comparison that it is meaningful to take the robust reliability into account in the control design of uncertain systems.     

Stability of stochastic neural networks with Markovian jumping parameters

The global asymptotical stability for a class of stochastic delayed neural networks (SDNNs) with new delay-dependent stability conditions are derived. All results are expressed in terms of linear matrix inequality (LMI), and a numerical example is presented to illustrate the correctness and less conservativeness of the proposed method.     

时滞大系统的模型参考鲁棒自适应分散控制

基于Lyapunov-Krasovskii (L-K) 泛函方法,结合线性矩阵不等式（linear matrix inequality, LMI）技术以及自适应控制方法,研究了一类不确定时变时滞大系统的模型参考跟踪控制问题,提出了一种鲁棒自适应分散控制器设计方法。时滞无关的控制器设计无需模型参考跟踪控制中苛刻的模型匹配条件且局部状态反馈增益以LMI 形式给出,便于计算机求解和参数优化。为避免控制过程中的自适应参数持续增长问题,提出了死区自适应算法。最后以仿真实例表明了所提方法的正确性与有效性。     

Stability analysis of cellular neural networks with time-varying delay

The global asymptotic stability of cellular neural networks with delays is investigated. Three kinds of time delays have been considered. New delay-dependent stability criteria are proposed and are formulated as the feasibility of some linear matrix inequalities, which can be checked easily by resorting to the recently developed interior-point algorithms. Based on the Finsler Lemma, it is theoretically proved that the proposed stability criteria are less conservative than some existing results.     

On the exponential stability of neural networks systems with time-varying delay

In this paper, exponential stability of Hopfield-type neural networks with time-varying delays are analyzed. By using the Lyapunov functional method, sufficient conditions are obtained for general exponential stabilities. At the same time, the output functions do not satisfy the Lipschitz conditions and do not require them to be differential or strictly monotonously increasing. Moreover, all results are established without assuming any symmetry of the connection matrix.A numeric example is pressented to show the effective of these criteria.     

Global exponential stability for delayed cellular neural networks and estimate of exponential convergence rate

Some sufficient conditions for the global exponential stability and lower bounds on the rate of exponential convergence of the cellular neural networks with delay (DCNNs) are obtained by means of a method based on delay differential inequality. The method, which does not make use of any Lyapunov functional, is simple and valid for the stability analysis of neural networks with delay. Some previously established results in this paper are shown to be special casses of the presented result.     

Delay-dependent exponential stability of impulsive stochastic systems with time-varying delay

The problem of delay-dependent exponential stability is investigated for impulsive stochastic systems with time-varying delay.Although the exponential stability of impulsive stochastic delay systems has been discussed by several authors,few works have been done on delay-dependent exponential stability of impulsive stochastic delay systems.Firstly,the Lyapunov-Krasovskii functional method combing the free-weighting matrix approach is applied to investigate this problem.Some delay-dependent mean square exponential stability criteria are derived in terms of linear matrix inequalities.In particular,the estimate of the exponential convergence rate is also provided,which depends on system parameters and impulsive effects.The obtained results show that the system will stable if the impulses’ frequency and amplitude are suitably related to the increase or decrease of the continuous flows,and impulses may be used as controllers to stabilize the underlying stochastic system.Numerical examples are given to show the effectiveness of the results.     

参数不确定系统鲁棒镇定控制器设计的鲁棒可靠性方法

用区间变量描述系统参数的不确定性,从可靠性角度研究不确定系统的稳定鲁棒性设计问题。基于二次稳定性准则,提出了参数不确定系统鲁棒镇定控制器设计的鲁棒可靠性新方法。依据该法设计的控制系统可满足稳定性意义上的鲁棒可靠性要求,并给出保证系统稳定性所要求的基本参数的最大鲁棒界限。所给公式完全基于线性矩阵不等式(LMI)方法,求解方便。适用于不确定参数的摄动范围准确已知和未知等情况。对实际算例的设计和模拟结果与现有结果的比较研究表明了在传统的控制器设计中,保守性的增加并不意味着可靠性的增加。从而也说明了所提方法是实用、有效和可行的。