1) fuzzy Lyapunov-Krasovskii function
模糊Lyapunov-Krasovskii函数
1.
The H∞ control problem of discrete T-S fuzzy systems with time-delay are studied via fuzzy Lyapunov-Krasovskii function.
研究了离散时滞T-S模糊系统基于模糊Lyapunov-Krasovskii函数的H∞控制问题。
2.
The stability analysis and controller design problem of discrete T-S fuzzy model with delay are studied via fuzzy Lyapunov-Krasovskii function.
研究了离散时滞T-S模糊模型基于模糊Lyapunov-Krasovskii函数的稳定性分析及控制器设计问题。
3.
Based on the fuzzy Lyapunov-Krasovskii function(LFK),a fuzzy controller is designed to acquire globally asymptotical stability for the discrete uncertain fuzzy time-delay system with the method of parallel distributed compensation(PDC).
基于模糊Lyapunov-Krasovskii函数,应用并行分布补偿算法,设计了使模糊系统全局渐近稳定的控制器,提出并证明了一个新的判别闭环不确定离散时滞模糊系统鲁棒H∞渐近稳定的充分条件。
2) fuzzy Lyapunov-Krasovskii functional
模糊Lyapunov-Krasovskii泛函
1.
Based on a fuzzy Lyapunov-Krasovskii functional(LKF) and fuzzy free-weighting matrices with time-delay,a new delay-dependent robust stability criterion is proposed and proved for the close-loop fuzzy system.
基于模糊Lyapunov-Krasovskii泛函(LKF),引入多个模糊时滞自由权值矩阵,提出并证明了闭环系统新的时滞相关鲁棒H∞渐近稳定的充分条件。
3) 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。
4) fuzzy Lyapunov function
模糊Lyapunov函数
1.
Based on a more general continuous model of actuator failure,the sufficient condition for the existence of state-feedback guaranteed reliable controller is derived from using fuzzy Lyapunov function and linear matrix inequality(LMI) technique.
在更一般性的连续型执行器故障模型基础上,运用模糊Lyapunov函数和线性矩阵不等式(LMI)技术,推导出状态反馈保性能可靠控制器存在的充分条件,并给出了最优化可靠控制器设计的拟凸优化方法。
2.
The quadratic stability of fuzzy descriptor system is investigated based on the fuzzy Lyapunov function.
针对T-S模糊广义系统,基于模糊Lyapunov函数研究了其渐近稳定性问题。
3.
The original systems can be generalized to augmented systems,then some admissible conditions for fuzzy descriptor systems are obtained based on a new fuzzy Lyapunov function and new fuzzy controller.
首先将原系统表示成增广系统,进而基于新的模糊Lyapunov函数和模糊控制器得到容许性条件。
5) 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。
6) Piecewise Fuzzy Lyapunov Function
分段模糊Lyapunov函数
1.
Analysis and Design of Fuzzy Systems Based on Piecewise Fuzzy Lyapunov Function;
基于分段模糊Lyapunov函数的模糊系统分析与设计
2.
Firstly, a new sufficient condition to check the stability of open-loop discrete T-S fuzzy systems is proposed after the definition of a discrete piecewise fuzzy Lyapunov function.
研究了基于分段模糊Lyapunov函数的离散T-S模糊控制系统稳定性分析及控制器设计问题。
补充资料：高斯函数模拟斯莱特函数
尽管斯莱特函数作为基函数在原子和分子的自洽场（SCF）计算中表现良好，但在较大分子的SCF计算中，多中心双电子积分计算极为复杂和耗时。使用高斯函数(GTO)则可使计算大大简化,但高斯函数远不如斯莱特函数(STO)更接近原子轨道的真实图象。为了兼具两者之优点，避两者之短,考虑到高斯函数是完备函数集合,可将STO向GTO展开：
式中X(ζS,A,nS,l,m)定义为在核A上，轨道指数为ζS，量子数为nS、l、m 的STO；g是GTO：
其变量与STO有相似的定义；Ngi是归一化常数：
rA是空间点相对于核A的距离;ci是组合系数；K是用以模拟STO的GTO个数（理论上，K→∞，但实践证明K只要取几个，便有很好的精确度）。
ci和ζ在固定K值下, 通过对原子或分子的 SCF能量计算加以优化。先优化出 ζS＝1 时固定K值的ci和(i＝1,2,...,K)，然后利用标度关系式便可得出ζS的STO展开式中每一个GTO的轨道指数，而且，ci不依赖于ζS,因而ζS＝1时的展开系数就是具有任意ζS的STO的展开系数。对不同展开长度下的展开系数和 GTO轨道指数已有表可查。
式中X(ζS,A,nS,l,m)定义为在核A上，轨道指数为ζS，量子数为nS、l、m 的STO；g是GTO：
其变量与STO有相似的定义；Ngi是归一化常数：
rA是空间点相对于核A的距离;ci是组合系数；K是用以模拟STO的GTO个数（理论上，K→∞，但实践证明K只要取几个，便有很好的精确度）。
ci和ζ在固定K值下, 通过对原子或分子的 SCF能量计算加以优化。先优化出 ζS＝1 时固定K值的ci和(i＝1,2,...,K)，然后利用标度关系式便可得出ζS的STO展开式中每一个GTO的轨道指数，而且，ci不依赖于ζS,因而ζS＝1时的展开系数就是具有任意ζS的STO的展开系数。对不同展开长度下的展开系数和 GTO轨道指数已有表可查。
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