1) Lyapunov-Krasovskii theorem
Lyapunov-Krasovskii理论
2) Krasovskii theory
Krasovskii理论
1.
Based on Lyapunov theory of stability and Krasovskii theory,an optimal controller was designed by means of the coordinate transformation for controlling the new type chaotic system.
基于Lyapunov稳定性理论和Krasovskii理论,结合坐标平移变换,对该混沌系统设计了一优化控制器,将混沌吸引子渐近稳定到它的不稳定的平衡点。
3) Lyapunov Krasovskii stability theory
Lyapunov-Krasovskii稳定性理论中图法分类号TP18
4) 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。
5) Lyapunov-Krasovskii functional
Lyapunov-Krasovskii函数
1.
When the activation function satisfies the condition of Lipschitz continuity,two sufficient conditions are established for the globally robust stability of the equilibrium point by suitably choosing Lyapunov-Krasovskii functional.
通过选取合适的Lyapunov-Krasovskii函数,建立了两个全局鲁棒稳定判据。
2.
Based on a RBF neural network online approximation model, a state feedback adaptive controller is obtained by constructing a novel Lyapunov-Krasovskii functional.
在RBF神经网络在线估计模型的基础上,本文通过设计新的Lyapunov-Krasovskii函数推导出了新的状态自适应控制器。
6) Lyapunov-Krasovskii approach
Lyapunov-Krasovskii方法
1.
Applying Lyapunov-Krasovskii approach,the property of norm and Riccati equation,corresponding nonlinear state feedback controllers are presented.
系统中含有不确定性非线性多时滞扰动,利用Lyapunov-Krasovskii方法、范数的性质及Riccati方程等工具提出了相应的非线性状态反馈控制器,它们可保证所讨论的系统是均方指数稳定性的。
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