矩阵方程AX-EXF=BY的通解及其应用

给出矩阵方程AX—EXY=BY的一个完全解析的、具有显式表达式和完全自由度的参数解(X,Y)．这里假设矩阵束(E,A B)为R-能控的,F为任意的方阵．相比于现有结论,求解算法不要求矩阵A和F具有特殊的形式,且对它们的特征值没有任何的限制,此外,本文给出的通解还具有结构简洁的特点,作为一个应用,给出了广义系统正常Luenberger函数观测器的一种参数化的设计方法,算例证明了方法的有效性．     

An explicit solution to polynomial matrix right coprime factorization with application in eigenstructure assignment

In this paper, an explicit solution to polynomial matrix right coprime factorization of input-state transfer function is obtained in terms of the Krylov matrix and the Pseudo-controllability indices of the pair of coefficient matrices. The proposed approach only needs to solve a series of linear equations. Applications of this solution to a type of generalized Sylvester matrix equations and the problem of parametric eigenstructure assignment by state feedback are investigated. These new solutions are simple, they possess better structural properties and are very convenient to use. An example shows the effect of the proposed results.     

An explicit solution to polynomial matrix right coprime factorization with application in eigenstructure assignment

In this paper, an explicit solution to polynomial matrix right coprime factorization of input-state transfer function is obtained in terms of the Krylov matrix and the Pseudo-controllability indices of the pair of coefficient matrices. The proposed approach only needs to solve a series of linear equations. Applications of this solution to a type of generalized Sylvester matrix equations and the problem of parametric eigenstructure assignment by state feedback are investigated. These new solutions are simple, they possess better structural properties and are very convenient to use. An example shows the effect of the proposed results.     

Solving the generalized Sylvester matrix equation AV +BW = VF via Kronecker map

This note considers the solution to the generalized Sylvester matrix equation AV ＋ BW = VF with F being an arbitrary matrix, where V and W are the matrices to be determined. With the help of the Kronecker map, an explicit parametric solution to this matrix equation is established. The proposed solution possesses a very simple and neat form, and allows the matrix F to be undetermined.     

矩阵方程AX-EXF=BY的通解及其应用

给出矩阵方程 AX-EXY=BY的一个完全解析的、具有显式表达式和完全自由度的参数解 (X,Y) .这里假设矩阵束 (E,A,B) 为R-能控的, F为任意的方阵.相比于现有结论,求解算法不要求矩阵A和F具有特殊的形式,且对它们的特征值没有任何的限制.此外,本文给出的通解还具有结构简洁的特点.作为一个应用,给出了广义系统正常Luenberger函数观测器的一种参数化的设计方法.算例证明了方法的有效性.     

PARAMETRIC SOLUTIONS TO THE GENERALIZED SYLVESTER MATRIX EQUATION AX ‐ XF = BY AND THE REGULATOR EQUATION AX ‐ XF = BY + R

In this paper, explicit parametric solutions to the generalized Sylvester matrix equation AX ‐ XF = BY and the regulator matrix equation AX ‐ XF = BY + R are proposed without any transformation and factorization. The proposed solutions are presented in terms of the Krylov matrix of matrix pair (A, B), a symmetric operator and the generalized observability matrix of matrix pair (Z, F) where Z is an arbitrary matrix and is used to denote the degree of freedom in the solution. Due to its elegant form and convenient computation, these proposed solutions will play an important role in solving and analyzing these types of equations in control systems theory.     

离散线性系统高阶积分观测器设计

针对离散线性系统提出一类高阶积分观测器。并且显示这类观测器满足极点配置分离原理，同时给出了这类观测器的存在条件．基于Sylvester矩阵方程的显式参数化通解提出了这类观测器的参数化设计方法．该方法不仅给出了观测器增益矩阵的参数表达式，而且还提供了观测器系统矩阵左特征向量的参数表达式．该设计方法给出了所有的设计自由度，为实现系统的其他性能提供了方便且强有力的工具．数值例子说明了设计过程，并表明了该方法的有效性．     

基于Fisher判别分析的增量式非负矩阵分解算法

增量式非负矩阵分解算法是基于子空间降维技术的无监督增量学习方法.文中将Fisher判别分析思想引入增量式非负矩阵分解中,提出基于Fisher判别分析的增量式非负矩阵分解算法.首先,利用初始样本训练的先验信息,通过索引矩阵对新增系数矩阵进行初始化赋值.然后,将增量式非负矩阵分解算法的目标函数改进为批量式的增量学习算法,在此基础上施加类间散度最大和类内散度最小的约束.最后,采用乘性迭代的方法计算分解后的因子矩阵.在ORL、Yale B和PIE等3个不同规模人脸数据库上的实验验证文中算法的有效性.     

An explicit solution to right factorization with application in eigenstructure assignment

Based on the well-known Leverrier algorithm, a simple explicit solution to right factorization of a linear system is established.This solution is expressed by the controllability matrix of the given system and a symmetric operator matrix.Applications of this solution to a type of generalized Sylvester matrix equations and the problem of parametric eigenstructure assignment by state feedback are investigated,and general complete parametric solutions to these two problems are deduced. These new solutions are simple,and possess desirable structural properties which render the solutions readily implementable.An example demonstrates the effect of the proposed results.     

Unified parametric approaches for high-order integral observer design for matrix second-order linear systems

A type of high-order integral observers for matrix second-order linear systems is proposed on the basis of generalized eigenstructure assignment via unified parametric approaches. Through establishing two general parametric solutions to this type of generalized matrix second-order Sylvester matrix equations, two unified complete parametric methods for the proposed observer design problem are presented. Both methods give simple complete parametric expressions for the observer gain matrices. The first one mainly depends on a series of singular value decompositions, and is thus numerically simple and reliable; the second one utilizes the right factorization of the system, and allows eigenvalues of the error system to be set undetermined and sought via certain optimization procedures. A spring-mass-dashpot system is utilized to illustrate the design procedure and show the effect of the proposed approach.     

Unified parametric approaches for high-order integral observer design for matrix second-order linear systems

A type of high-order integral observers for matrix second-order linear systems is proposed on the basis of generalized eigenstructure assignment via unified parametric approaches. Through establishing two general parametric solutions to this type of generalized matrix second-order Sylvester matrix equations, two unified complete parametric methods for the proposed observer design problem are presented. Both methods give simple complete parametric expressions for the observer gain matrices. The first one mainly depends on a series of singular value decompositions, and is thus numerically simple and reliable; the second one utilizes the right factorization of the system, and allows eigenvalues of the error system to be set undetermined and sought via certain optimization procedures. A spring-mass-dashpot system is utilized to illustrate the design procedure and show the effect of the proposed approach.     

An explicit solution to right factorization with application in eigenstructure assignment

1Proble mfor mulationRight factorization oflinear systems is a basic problemincontrol systems theory,and has important applications inmany analysis and design problems ,such as , robuststabilization [1] ,minimal state space realization [2,3] ,speed servo system design [4] ,synthesis of H_infinitycontrollers [5] ,etc .Furthermore ,it has been shown byDuan and his co_authors that a factorization can be usedtoparameterize all the solutions to a generalized_type ofSylvester matrix equations [6 ~8…     

Polynomial J-spectral factorization

Several algorithms are presented for the J-spectral factorization of a para-Hermitian polynomial matrix. The four algorithms that are discussed are based on diagonalization, successive factor extraction, interpolation, and the solution of an algebraic Riccati equation, respectively. The paper includes a special algorithm for the factorization of unimodular para-Hermitian polynomial matrices and deals with canonical, noncanonical, and nearly noncanonical factorizations