1) Lyapunov-functional
Lyapunov-泛函
2) Lyapunov-Krasovskii functional
Lyapunov-Krasovskii泛函
1.
By adopting Lyapunov-Krasovskii functional and dissi-pative theory,sufficient conditions are given to ensure the existence of a memoryless state feedback control law,which guarantees the stability of the closed-loop system.
采用Lyapunov-Krasovskii泛函和耗散性理论,给出了保证闭环系统渐近稳定的无记忆状态反馈控制律存在的充分条件,该条件同时保证闭环系统满足γ-次优H∞性能,为控制器的设计提供了理论依据。
2.
Applying a stabilizing state feedback control to systemsm,aking use of the Lyapunov-Krasovskii functional and combining the method of the linear matrix inequalities(LMI)t,he sufficient conditions of robust BIBO stabilization for T-S fuzzy control systems are obtained.
研究了一类具有不确定系数的T-S模糊控制系统的鲁棒BIBO镇定问题,应用稳定的状态反馈控制,通过构造Lyapunov-Krasovskii泛函,采用线性矩阵不等式(LMI)方法,给出了T-S模糊连续控制系统Robust有界输入有界输出镇定的充分条件;当参考的输入信号r(t)≡0时,给出了T-S模糊连续控制系统的零解鲁棒镇定的充分条件。
3.
Constructing a suitable Lyapunov-Krasovskii functional and based on the scheme of decentralized control,the design of a control law is proposed to ensure the global asymptotic synchronization of state trajectories of two chaotic neural networks of which the structure are the same and the initial conditions are different.
基于分散控制策略,通过构造适当的Lyapunov-Krasovskii泛函,给出了保证两个具有相同结构但初始条件不相同的时滞混沌神经网络全局渐近同步的控制律设计方法。
3) Lyapunov function
Lyapunov泛函
1.
In this paper,by making use of the Lyapunov functional method and combining with the technique of inequality analysis,we discuss the global asympototic stability of a class of cellular neural networks.
利用Lyapunov泛函方法和不等式技巧,研究了一类细胞神经网络的全局渐近稳定性,通过引入一系列参数,给出了保证时滞细胞神经网络全局渐近稳定的模型设计方法。
2.
By making use of the Lyapunov functional method,the measuring of Hopfield neural networks with delay is discussed.
利用Lyapunov泛函方法,研究了具有时滞的Hopfield神经网络稳定性的测试问题,得到了网络全局渐近稳定性与滞量无关的测试方法,这对于时滞神经网络的设计与检验具有普遍应用的意义。
3.
By Lyapunov functional method,the asymptotic property of the solutions for the Cauchy problem is obtained.
研究了在高维空间下多孔介质方程初值问题解的渐近行为,利用Lyapunov泛函方法得到了该问题解在L1(RN)里的渐近性质。
4) Lyapunov-Krasovskii
Lyapunov-kresovskii泛函
1.
By constructing appropriate Lyapunov-Krasovskii functions (LKF) and solving linear matrix inequality(LMI), the state observer making the observer error asymptotically convergence to zero was constructed.
通过构造适当的Lyapunov-kresovskii泛函(LKF)和求解线性矩阵不等式(LMI),给出了使得误差动态系统渐近趋于零的非线性时滞系统的状态观测器。
5) Lyapunov functional
Lyapunov泛函
1.
Based on Lyapunov functional method,a sufficient criterion for stability and quadratic performance of the systems,which is dependent on the size of the time-delay and the size of its derivative,is derived and it is shown that this condition is equivalent to the solvability of a set certain linear matrix inequalities(LMIs).
基于Lyapunov泛函方法,导出该系统的稳定性和性能指标与时滞及其导数有关的充分条件,该条件等价于线性矩阵不等式(LMI)系统的可解性问题,进而用这组线性矩阵不等式系统的可行解,给出了使此类系统鲁棒渐近稳定且满足性能指标的状态反馈控制器设计方法。
2.
Some stability criteria in terms of matrix inequalities(LMIs) are obtained based on Lyapunov functional method,which is only to solve LIMIs for verifying the stability conditions.
利用Lyapunov泛函方法建立了基于线性矩阵不等式的绝对稳定性条件,因而将稳定性条件的检验转化为数学软件Matlab线性矩阵不等式的求解问题。
3.
By using differential formula and Lyapunov functional,a new delay-independent sufficient condition for exponential stability is derived.
研究了均方意义下的具有时变时滞与分布时滞的随机Cohen-Grossberg神经网络的指数稳定性,利用It微分公式和Lyapunov泛函,得到了一个关于其指数稳定时滞无关的充分条件。
6) Lyapunov-Krasoviskii functionals
Lyapunov-Krasoviskii泛函
补充资料：[3-(aminosulfonyl)-4-chloro-N-(2.3-dihydro-2-methyl-1H-indol-1-yl)benzamide]
分子式：C16H16ClN3O3S
分子量：365.5
CAS号：26807-65-8
性质：暂无
制备方法：暂无
用途：用于轻、中度原发性高血压。
分子量：365.5
CAS号：26807-65-8
性质：暂无
制备方法：暂无
用途：用于轻、中度原发性高血压。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条