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含区间时变时滞的线性不确定系统鲁棒稳定性新判据 总被引:2,自引:0,他引:2
研究一类区间时变时滞线性不确定系统的鲁棒稳定性问题.通过引入增广Lyapunov泛函,结合积分不等式方法,导出了区间时变时滞线性系统的时滞相关鲁棒稳定性新判据.与现有方法不同,该方法不涉及自由权矩阵技术和任何模型变换,减少了理论和计算上的复杂性,而且在估计Lyapunov泛函导数的上界时没有忽略某些有用项.数值算例表明,所提出的判据是有效的,具有更低的保守性. 相似文献
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研究一类含混合变时滞不确定中立系统时滞相关鲁棒稳定性问题。基于时滞中点值,把时滞区间均分成两部分,通过构造包含时滞中点信息的增广泛函和三重积分项的Lyapunov-Krasovskii (L-K)泛函,利用L-K稳定性定理、积分不等式方法和自由权矩阵技术,建立了一种基于线性矩阵不等式(LMI)的、与离散时滞和中立时滞均相关的鲁棒稳定性判据。数值算例表明,该判据改善了已有文献的结论,具有更低的保守性。 相似文献
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本文利用Lyapunov—Krasovskii稳定性定理和线性矩阵不等式技术,得到了多时滞区间神经网路全局鲁棒稳定性的一个新的稳定性规则。该规则推广了最近文献中的一些结果,并通过数值仿真证实了结果的正确性。 相似文献
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针对一类不确定中立型时变时滞Hopfield神经网络的鲁棒稳定性问题, 构造了一个新Lyapunov-Krasovskii泛函, 并结合自由矩阵方法和牛顿—莱布尼茨公式, 得到了新的时滞相关稳定性判据. 该判据考虑了中立型时变时滞Hopfield神经网络中的参数不确定性, 所得结果以线性矩阵不等式(Linear matrix inequality, LMI)的形式给出, 容易验证. 最后, 通过两个数值算例验证了该结果的有效性及可行性. 该判据对丰富与完善中立型神经网络的稳定性理论体系, 具有积极的意义. 相似文献
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针对一类存在泛数有界不确性的区间变时滞线性系统, 利用Lyapunov-Krasovskii (L-K) 泛函方法并结合线性矩阵不等式(LMI) 技术建立一种新的保守性更低的鲁棒稳定性判据. 首先基于时滞分割方法将时滞区间均分成N 等分, 针对不同的子区间构造合适的L-K 泛函; 然后在各自的分割区间采用保守性较小的积分不等式处理泛函沿时间的导数, 基于凸组合技术建立了LMI 形式的时滞相关稳定性新判据; 最后通过数值实例验证了结论的有效性.
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具有时滞的线性区间系统的鲁棒稳定性 总被引:3,自引:1,他引:3
本文给出了线性区间时滞系统鲁棒稳定性的一些结果,这些结果推广和是了前人关于线性时滞系统鲁棒稳定性的相关结论,同时还讨论了线性区间时滞系统的稳定度,最后讨论了线性区间时滞大系统的鲁棒稳定性。 相似文献
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《国际计算机数学杂志》2012,89(10):2188-2201
The article addresses the problem of global robust exponential stability of interval neural networks with time-varying delays. On the basis of linear matrix inequality technique and M-matrix theory, some novel sufficient conditions for the existence, uniqueness, and global robust exponential stability of the equilibrium point for delayed interval neural networks are presented. It is shown that our results improve and generalize some previously published ones. Some numerical examples and simulations are given to show the effectiveness of the obtained results. 相似文献
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This paper deals with the stability of static recurrent neural networks (RNNs) with a time-varying delay. An augmented Lyapunov-Krasovskii functional is employed, in which some useful terms are included. Furthermore, the relationship among the timevarying delay, its upper bound and their difierence, is taken into account, and novel bounding techniques for 1- τ(t) are employed. As a result, without ignoring any useful term in the derivative of the Lyapunov-Krasovskii functional, the resulting delay-dependent criteria show less conservative than the existing ones. Finally, a numerical example is given to demonstrate the effectiveness of the proposed methods. 相似文献
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分析了区间变时滞的随机神经网络的全局渐进稳定性。区间变时滞不仅考虑了时变因素,而且考虑了时滞时变的上界和下界。通过Itô’s 微分公式和构造适当的李雅普罗夫泛函,并且引入自由权值矩阵,以线性矩阵不等式形式给出了该系统在均方意义下的全局渐进稳定的充分性判据。数值算例进一步证明了结论的有效性。 相似文献
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多时滞Lurie控制系统的时滞相关鲁棒稳定性 总被引:5,自引:1,他引:4
时滞Lurie控制系统的稳定性条件与Lyapunov函数的选取有关.本文对多时滞Lurie控制系统进行了变换,然后选择一个适当的Lyapunov函数,利用Lyapunov稳定性方法并结合Moon引理,得到了多时滞Lurie控制系统的时滞相关鲁棒稳定性判别条件,该条件是以线性矩阵不等式(LMI)给出的,可用Matlab求解.最后用一个算例验证了所得方法的有效性. 相似文献
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Tao Li Lei Guo Lingyao Wu Changyin Sun 《International Journal of Control, Automation and Systems》2009,7(2):281-287
This article investigates the problem of robust stability for neural networks with time-varying delays and parameter uncertainties
of linear fractional form. By introducing a new Lyapunov-Krasovskii functional and a tighter inequality, delay-dependent stability
criteria are established in term of linear matrix inequalities (LMIs). It is shown that the obtained criteria can provide
less conservative results than some existing ones. Numerical examples are given to demonstrate the applicability of the proposed
approach.
Recommended by Editorial Board member Naira Hovakimyan under the direction of Editor Young-Hoon Joo. This work was supported
by the National Science foundation of China under Grant no. 60774013 and Key Laboratory of Education Ministry for Image Processing
and Intelligent Control under grant no. 200805.
Tao Li received the Ph.D. degree in The Research Institute of Automation Southeast University, China. Now He is an Assistant Professor
in Department of Information and Communication, Nanjing University of Information Science and Technology. His current research
interests include time-delay systems, neural networks, robust control, fault detection and diagnosis.
Lei Guo received the Ph.D. degree in the Research Institute of Automation Southeast University, China. From 1999 to 2004, he has
worked at Hong Kong University, IRCCyN (France), Glasgow University, Loughborough University and UMIST, UK. Now He is a Professor
in School of Instrument Science and Opto-Electronics Engineering, Beihang University. His current research interests include
robust control, fault detection and diagnosis.
Lingyao Wu received the Ph.D. degree in The Research Institute of Automation Southeast University, China. Now He is an Assistant Professor
in the Research Institute of Automation Southeast University. His current research interests include time-delay systems, neural
networks, robust control, fault detection and diagnosis.
Changyin Sun received the Ph.D. degree in the Research Institute of Automation Southeast University, China. Now He is a Professor in the
Research Institute of Automation Southeast University. His current research interests include timedelay systems, neural networks. 相似文献
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New delay-dependent criterion for the stability of recurrent neural networks with time-varying delay
This paper is concerned with the global asymptotic stability of a class of recurrent neural networks with interval time-varying
delay. By constructing a suitable Lyapunov functional, a new criterion is established to ensure the global asymptotic stability
of the concerned neural networks, which can be expressed in the form of linear matrix inequality and independent of the size
of derivative of time varying delay. Two numerical examples show the effectiveness of the obtained results.
Supported by the National Natural Science Foundation of China (Grant Nos. 60534010, 60728307, 60774048, 60774093), the Program
for Cheung Kong Scholars and Innovative Research Groups of China (Grant No. 60521003) and the National High-Tech Research
& Development Program of China (Grant No. 2006AA04Z183), China Postdoctoral Sciencer Foundation (Grant No. 20080431150), and
the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 200801451096) 相似文献
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Feiqi DengAuthor Vitae Mingang HuaAuthor Vitae Xinzhi LiuAuthor Vitae Yunjian PengAuthor VitaeJuntao FeiAuthor Vitae 《Neurocomputing》2011,74(10):1503-1509
This paper is concerned with the robust delay-dependent exponential stability of uncertain stochastic neural networks (SNNs) with mixed delays. Based on a novel Lyapunov-Krasovskii functional method, some new delay-dependent stability conditions are presented in terms of linear matrix inequalities, which guarantee the uncertain stochastic neural networks with mixed delays to be robustly exponentially stable. Numerical examples are given to illustrate the effectiveness of our results. 相似文献
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《国际计算机数学杂志》2012,89(15):1938-1951
This paper considers the asymptotic stability problem for a class of neural networks with discrete and distributed delays. Based on a new augmented Lyapunov functional and integral inequalities, the new asymptotic stability condition is established in terms of linear matrix inequality. Meanwhile, the importance of some augmented terms in the Lyapunov functional are discussed. Compared with previous methods to deal with the distributed delay, our method is less conservative due to the use of the new Lyapunov functional. Finally, numerical examples illustrate the relaxation of obtained results and our claims. 相似文献
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This paper deals with the global asymptotic stability problem for Hopfield neural networks with time-varying delays. By resorting to the integral inequality and constructing a Lyapunov-Krasovskii functional, a novel delay-dependent condition is established to guarantee the existence and global asymptotic stability of the unique equilibrium point for a given delayed Hopfield neural network. This criterion is expressed in terms of linear matrix inequalities (LMIs), which can be easily checked by utilizing the recently developed algorithms for solving LMIs. Examples are provided to demonstrate the effectiveness and reduced conservatism of the proposed condition. 相似文献