离散广义系统稳定性分析与控制的Lyapunov方法

利用Lyapunov方法,研究离散广义系统稳定性分析与控制问题.得到了离散广义 系统正则、具有因果关系且渐近稳定的等价条件;还给出了相关的鲁棒稳定性分析与镇定方 法.     

离散广义大系统的Lyapunov稳定性分析

广义大系统的稳定性是广义大系统理论的基本问题之一,对其稳定性的研究要比状态空间大系统复杂得多,因为广义大系统不仅需要考虑稳定性,而且还要考虑正则性和因果性(离散广义系统)及脉冲自由(连续广义系统).本文在所有孤立子系统都是正则的且具有因果关系的条件下,利用Lyapunov方程,应用Lyapunov函数方法,研究了广义离散线性大系统和广义离散非线性大系统的稳定性和不稳定性问题,给出了离散广义大系统稳定性和不稳定性判定定理,得到了离散广义大系统的关联稳定参数域和不稳定域.     

广义非线性系统解的一致最终有界性研究*

首先利用隐函数定理及常规的非线性系统解地存在唯一性定理,给出了广义非线性系统解的存在唯一性条件,然后利用标量和Ｌｙａｐｕｎｏｖ函数方法,从系统本身出发,研究了广义非线性系统解的一致最终有界性。     

离散随机Markov 跳跃系统的广义Lyapunov 方程解的性质

针对离散随机Markov 跳跃系统, 基于?表示方法研究了其对应的广义Lyapunov 方程解的性质. 首先, 证明了广义Lyapunov 方程存在唯一实对称矩阵序列解的充分必要条件是系统的谱不包含零特征值; 然后, 在系统的谱包含零特征值的情况下, 分析了广义Lyapunov 方程解的结构; 最后, 通过数值仿真表明了所得结论的正确性.

     

求解规范型Lyapunov矩阵方程的新方法

本文揭示了规范型Lyapunov矩阵方程及其对偶方程的一些特殊性质,充分压缩解矩阵的未知元素,并利用对偶解矩阵与解矩阵的合同关系,提出了一种高精度、高效率求解规范型Lyapunov方程的新算法,文中举例验证了新算法的正确性。 Lyapunov矩阵方程 能控制和能观测规范型 单输入单输出系统     

离散广义双线性系统的稳定控制

针对离散广义双线性系统,研究了稳定控制存在的条件,给出了相应的控制方案。所采用的方法是利用广义系统分解,选择适当的控制,运用Lyapunov方法证明线性状态控制可以使闹环系统在原点附近渐近稳定。对于这一类离散广义双线性系统有关理论的证明,可以看作是正常离散广义双线性系统的拓广。给出了一个可行性的应用算例,同时仿真结果也说明了该方法的有效性所得稳定性的判据对于选择合适的控制方案具有实际指导意义。     

具有脉冲作用的切换线性广义系统的稳定性

本文引入一类新的系统模型—具有脉冲作用的切换线性广义系统. 应用驻留时间(Dwell time)方法和平均驻留时间(Average dwell time)方法研究其稳定性问题, 并给出系统指数稳定性的充分条件. 证明了当平均驻留时间足够大且重设律是允许的, 那么系统是指数稳定的. 利用广义系统的受限等价性质, 具体给出允许的重设律的设计方法. 数值例子说明本文方法的有效性.     

Fokker Planck方程的非古典广义势对称及精确解

分析了Fokker-Planck方程的非古典势对称,通过广义势系统而不是一般势系统求得了这些非古典势对称.文中得到了这些方程的新的对称,同时也得到了伴随系统的新的对称,并用其求出了一些精确解.这些解对进一步研究Fokker-Planck方程所描述的物理现象具有广泛的应用价值.     

一类滞后型时变广义系统解的稳定性

滞后广义系统解的稳定性的研究与非奇异系统或不带滞后的广义系统解的稳定性研究均有不同。为了解决所遇到的新困难,一种稳定性的新概念被提出,同时,通过Lyapunov函数方法,两个稳定性判定定理得以建立。这些结果被应用于线性系统,得到了一个关于线性系统稳定性判定的很有价值的结果。     

一般广义时变系统的容许性和二次容许性

针对一般广义时变系统, 采用广义Lyapunov 不等式和受限等价变换的分析方法, 提出了一般广义时变系统容许性和二次容许性的概念, 建立了一般广义时变系统的Lyapunov 不等式. 将一般广义时变系统容许性问题转化为求解Lyapunov 不等式问题, 获得了该类系统容许和二次容许的充要条件, 所得结论是广义系统容许性研究成果向一般广义时变系统的自然推广. 最后, 通过数值算例验证了所得结论的有效性.     

Construction of square root factor for solution of the Lyapunov matrix equation

The Lyapunov matrix equation is considered in this paper, where the solution is a nonnegative definite matrix, i.e. a matrix admitting decomposition in square root factors. An algorithm for findings the square root factor without preliminary finding the solution itself is given.     

Bounds for the solution of the Lyapunov matrix equation — A unified approach

In recent years, several bounds have been reported for the solution of the continuous and the discrete Lyapunov equations. Using the unified Lyapunov equation, we give in this paper bounds for the solution of this equation. In the limiting cases, the bounds reduce to existing bounds for both the continuous and discrete Lyapunov equations.     

Bounds on the trace of a solution to the Lyapunov equation with a general stable matrix

Some new estimates for the eigenvalue decay rate of the Lyapunov equation AX+XA^T=B with a low rank right-hand side B are derived. The new bounds show that the right-hand side B can greatly influence the eigenvalue decay rate of the solution. This suggests a new choice of the ADI-parameters for the iterative solution. The advantage of these new parameters is illustrated on second order damped systems with a low rank damping matrix.     

Improved gradient-based neural networks for online solution of Lyapunov matrix equation

By adding different activation functions, a type of gradient-based neural networks is developed and presented for the online solution of Lyapunov matrix equation. Theoretical analysis shows that any monotonically-increasing odd activation function could be used for the construction of neural networks, and the improved neural models have the global convergence performance. For the convenience of hardware realization, the schematic circuit is given for the improved neural solvers. Computer simulation results further substantiate that the improved neural networks could solve the Lyapunov matrix equation with accuracy and effectiveness. Moreover, when using the power-sigmoid activation functions, the improved neural networks have superior convergence when compared to linear models.     

A parametric Lyapunov equation approach to low gain feedback design for discrete-time systems

Low gain feedback, a parameterized family of stabilizing state feedback gains whose magnitudes approach zero as the parameter decreases to zero, has found several applications in constrained control systems, robust control and nonlinear control. In the continuous-time setting, there are currently three ways of constructing low gain feedback laws: the eigenstructure assignment approach, the parametric ARE based approach and the parametric Lyapunov equation based approach. The eigenstructure assignment approach leads to feedback gains explicitly parameterized in the low gain parameter. The parametric ARE based approach results in a Lyapunov function along with the feedback gain, but requires the solution of an ARE for each value of the parameter. The parametric Lyapunov equation based approach possesses the advantages of the first two approaches and results in both an explicitly parameterized feedback gains and a Lyapunov function. The first two approaches have been extended to discrete-time setting. This paper develops the parametric Lyapunov equation based approach to low gain feedback design for discrete-time systems.