区间时变时滞系统的时滞相关稳定性分析

研究了具有区间时变时滞线性不确定系统的稳定性问题。通过引入新型的Lyapunov泛函,结合改进型的Jensen积分不等式,推导出区间时变时滞线性系统的时滞相关鲁棒稳定新判据。该方法在推导过程中没有用到模型变换及自由权矩阵方法,简化了计算上的复杂性。由于判据中充分利用了时变时滞的中值及时滞变化范围两个参数,减少了结果的保守性。数值算例表明了提出方法的有效性及优越性。     

Bessel-Legendre不等式在时滞系统稳定性分析中的新结果

本文主要研究了时变时滞线性系统的时滞相关稳定性问题。首先,本文基于Bessel-Legendre积分不等式推导出三阶Bessel-Legendre积分不等式的一般形式,它与Wirtinger-based积分不等式和Jensen不等式相比,能够让系统产生更少的保守性;其次,本文在构建Lyapunov-Krasovskii泛函时,充分结合了二阶与三阶Bessel-Legendre不等式一般形式的所有特征,量体裁衣地构造出一个含增广项的Lyapunov-Krasovskii泛函;再次,为了让泛函具有更精确的下界,本文对Lyapunov-Krasovskii泛函中的部分项进行整体正定处理,以至于放松了正定条件;最后,一个新的稳定判据以线性矩阵不等式的形式被推导出来,并通过数值实例仿真来表明本文方法的有效性与优越性。     

区间变时滞不确定系统鲁棒稳定性分析

本文针对一类线性区间变时滞不确定系统的鲁棒稳定性分析问题进行了研究.基于时滞中点法和凸组合技术,借助于构造一个包含四重积分项的新Lyapunov-Krasovskii（L-K）泛函,并利用积分不等式方法给出了LMI（Linear Matrix Inequality）形式的时滞相关稳定性新判据.与已有文献相比,该判据能大大降低理论推导和计算上的复杂性.最后通过三个具有代表性的数值例子对比验证了本文所提出方法在降低结论保守性方面的优越性.     

控制增益符号已知的MIMO非线性时滞系统自适应控制

针对一类具有死区模型并且控制增益符号已知的不确定多输入多输出非线性时滞系统,基于滑模控制原理提出了一种稳定的自适应神经网络控制方案。该方案通过使用Lyapunov-Krasovskii泛函抵消了因未知时变时滞带来的系统不确定性。通过利用积分型李亚普诺夫函数,并且构造逼近连续函数,闭环系统证明是半全局一致终结有界。仿真结果表明了该方法的有效性。     

具有时延和丢包的不确定性NCS的稳定性

研究了同时具有网络时延和数据丢包的不确定网络化控制系统的稳定性.将数据丢失看成一种特殊的时延,利用动态反馈控制器设计提高系统的动态性能,得到了总时滞(包括传感器与控制器之间的时滞,控制器与执行器之间的时滞)的表达式,建立了不确定网络化控制系统模型.通过构造李亚普诺夫函数,采用线性矩阵不等式技巧,给出了系统稳定的判定定理.仿真结果表明了该方法的有效性.     

一种新型Hopfield神经网络平衡解的全局指数稳定性

 结合生物学最近的研究成果,提出一种具有动态突触和不同时间尺度的新型Hopfield神经网络模型.运用不动点定理、不等式技巧及Lyapunov泛函等方法,讨论了该人工神经网络在具有常时滞和变时滞两种情况下,其平衡解的存在性唯一性和全局指数稳定性.     

多时滞Lurie网络控制系统动态输出反馈控制器设计

针对一类具有非理想网络状况,如时变网络时滞、分组丢失和乱序等问题的基于动态输出反馈控制器的网络控制系统,建立了多时滞Lurie网络控制系统模型,应用Lyapunov-Krasovskii泛函方法,保留Lyapunov-Krasovskii泛函导数中经常被忽略的有用项,提出了一种具有更低保守性的多时滞Lurie网络控制系统时滞相关稳定条件。并通过增加一等式约束将非线性矩阵不等式转化为线性矩阵不等式表示的可解性问题,给出了一种动态输出反馈控制器的设计方法。数值实例表明该设计方法具有更低的保守性。     

参数不确定的单时滞系统基于简化的L-K泛函的稳定性分析

参数不确定和时滞广泛存在于各种实际的控制系统中,而且它们往往是导致系统不稳定或性能下降的原因。本文基于Lyapunov稳定性理论,通过构造简化的Lyapunov-Krasovskii泛函,同时应用线性矩阵不等式(LMI:linearmatrix inequality)方法,研究了参数不确定和单时变时滞系统的鲁棒稳定性问题,并导出了由LMI表示的该类系统的鲁棒稳定性判据,而且,通过这类简化的L-K泛函,在充分利用时滞信息的基础上减少了判据的保守性。最后借助含不确定性扰动的具有单时变时滞的单机-无穷大系统模型,分析了保持鲁棒稳定时系统可承受的最大时滞的界限,数值仿真验证了方法的有效性。     

一类时变时滞模糊细胞神经网络的 时滞依赖指数稳定性判据

 针对一类带有时变时滞的模糊细胞神经网络,通过适当的构造Lyapunov-Krasovskii泛函,以线性矩阵不等式的形式提出了一种新颖的依赖于时滞的全局指数稳定性判据.与之前结果相比,所提出的判据针对模糊时滞项进行了变换,从而首次考虑了模糊细胞神经网络中非模糊项的连接权矩阵中元素的符号问题,降低了判据的保守性.并且时滞变化率的限制将被放松.仿真结果进一步证明了判据的有效性.     

基于C8051F的深海投放装置导航电机控制系统研制

针对深海观测设备的定点投放问题,研制了一种基于高速混合单片机C8051F020的导航电机控制系统.着重介绍了以C8051F020单片机为核心的导航电机控制系统.该控制系统由D/A输出模块,功率放大电路以及检测电路组成.控制算法采用变速积分PID算法,并通过仿真结果证明了该算法解决了普通PID控制中的积分饱和现象,系统响应速度快,提高了电机的可控性.整个电机控制系统稳定可靠,保证了水下投放装置运行的可靠性.     

New Synchronization Stability of Complex Networks With an Interval Time-Varying Coupling Delay

In this brief, the problem of synchronization stability analysis for complex dynamical networks with a time-varying coupling delay is studied. The delay considered in this brief is assumed to vary over an interval where the lower and upper bounds are known. By dividing the interval time-varying delay into a constant and a time-varying part and using a delay-partitioning approach, a new Lyapunov-Krasovskii functional is constructed. Based on this, a new delay-range-dependent criterion is obtained in terms of linear matrix inequalities. A numerical example is provided to show the effectiveness of the proposed results.     

On Designing Time-Varying Delay Feedback Controllers for Master–Slave Synchronization of Lur'e Systems

This paper is concerned with the problem of designing time-varying delay feedback controllers for master-slave synchronization of Lur'e systems. Two cases of time-varying delays are fully considered; one is the time-varying delay being continuous uniformly bounded while the other is the time-varying delay being differentiable uniformly bounded with the derivative of the delay bounded by a constant. Based on Lyapunov-Krasovskii functional approach, some delay-dependent synchronization criteria are first obtained and formulated in the form of linear matrix inequalities (LMIs). The relationship between synchronization criteria for the two cases of time-varying delays is built. Then, sufficient conditions on the existence of a time-varying delay feedback controller are derived by employing these newly-obtained synchronization criteria. The controller gains can be achieved by solving a set of LMIs. Finally, Chua's circuit is used to illustrate the effectiveness of the design method.     

Existence and Global Asymptotic Stability of Fuzzy Cellular Neural Networks with Time Delay in the Leakage Term and Unbounded Distributed Delays

Fuzzy cellular neural network (FCNN) structures are based on the uncertainties in human cognitive processes and in modeling neural systems, and they provide an interface between a human expert and classical cellular neural networks (CNNs). In this paper, an existence and global asymptotic stability analysis of the equilibrium point of FCNNs with time delay in the leakage term and unbounded distributed delays is investigated. Based on the Lyapunov-Krasovskii functional with free-weighting matrix, and using the homeomorphism mapping principle and linear matrix inequalities (LMIs), a new set of stability criteria for FCNNs is obtained with time delay in the leakage term, time-varying delays and unbounded distributed delays. The proposed results can be easily checked via the LMI Control Toolbox in MATLAB. Moreover, it is well known that the stability behavior of FCNNs is very sensitive to the time delay in the leakage term. In the absence of the leakage term, a new stability criterion is also derived by employing a Lyapunov-Krasovskii functional using an LMI approach. Numerical examples are provided to illustrate the effectiveness and reduced conservativeness of the developed techniques.     

线性时滞系统的时滞相关稳定性

本文讨论了线性时滞系统x(t)=Ax( ) Bx(t-τ)渐近稳定的时滞界限，利用Lyapunov—Krasovskii泛函及H∞范数理论，获得了线性时滞系统时滞相关稳定的充分条件，同时得到了一个新的时滞界限的代数估计式。将本文结果应用于实际系统，计算简单，并且扩大了时滞的稳定区域，降低了对时滞的保守性。分析结果还表明，线性时滞系统的稳定性可以转化为一定常无时滞的线性系统的H∞控制问题。     

Robust Delay-Dependent Stability Criteria for Dynamic Systems with Nonlinear Perturbations and Leakage Delay

This paper studies the global asymptotic stability for uncertain systems with mixed delays. The mixed delays include constant delay in the leakage term (i.e., leakage delay) and time-varying delays. The uncertainties under consideration are nonlinear time-varying parameter perturbations and norm-bounded uncertainties. Based on a appropriate Lyapunov–Krasovskii functional with triple integral terms, some integral inequalities and convex combination technique, a novel delay-dependent stability criterion is derived in terms of linear matrix inequalities (LMIs). Finally, three numerical examples are included to show the superiority of the proposed method.     

Global stability of a class of neural networks with time-varying delay

This paper presents a new sufficient condition for the uniqueness and global asymptotic stability of the equilibrium point for a class of neural networks with time-varying delays. The result is obtained by the use of a more general type of Lyapunov-Krasovskii functional, establishing a relation between the network parameters of the neural system and time-varying delay parameter. The result is also shown to be a generalization of a previously published result.