Robust Control of Uncertain Markov Jump Singularly Perturbed Systems

In this paper,we study the robust control for uncertain Markov jump linear singularly perturbed systems(MJLSPS),whose transition probability matrix is unknown.An improved heuris- tic algorithm is proposed to solve the nonlinear matrix inequalities.The results of this paper can apply not only to standard,but also to nonstandard MJLSPS.Moreover,the proposed approach is independent of the perturbation parameter and therefore avoids the ill-conditioned numerical prob- lems.     

Stability analysis for continuous-time systems with actuator saturation

The aim of this paper is to study the determination of the stability regions for continuous-time systems subject to actuator saturation. Using an affine saturation-dependent Lyapunov function, a new method is proposed to obtain the estimation of the domain of attraction of the closed-loop system. A family of linear matrix inequalities （LMIs） that provides sufficient conditions for the existence of this type of Lyapunov function are presented. The results obtained in this paper can reduce the conservativeness compared with the existing ones. Numerical examples are given to illustrate the effectiveness of the proposed results.     

Orthogonal projection based subspace identification against colored noise

In this paper, a bias-eliminated subspace identification method is proposed for industrial applications subject to colored noise. Based on double orthogonal projections, an identification algorithm is developed to eliminate the influence of colored noise for consistent estimation of the extended observability matrix of the plant state-space model. A shift-invariant approach is then given to retrieve the system matrices from the estimated extended observability matrix. The persistent excitation condition for consistent estimation of the extended observability matrix is analyzed. Moreover, a numerical algorithm is given to compute the estimation error of the estimated extended observability matrix. Two illustrative examples are given to demonstrate the effectiveness and merit of the proposed method.     

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.     

Fast inverse covariance matrix computation based on element-order recursive method for space-time adaptive processing

Because of large computational complexity in the inverse space-time covariance matrix computation,the conventional space-time adaptive processing(STAP) is unsuitable for practical implementation. According to the block Hermitian matrix property of covariance matrix, a new element-order recursive method is proposed in this paper to calculate the inverse space-time covariance matrix for STAP weight vector. In the proposed method, the inverse space-time covariance matrix of first element-order is initially calculated recursively based on block Hermitian matrix property, and then the inverse space-time covariance matrix of high element-order is correspondingly deduced recursively based on obtained inverse covariance matrix of previous element-order.Finally, STAP weight vector is calculated based on the final inverse covariance matrix. Afterwards, a modified reduced-dimension STAP method is derived by combining the proposed method with the m-Doppler Transformation(m DT-SAP) STAP approach. Based on the simulated and the actual airborne phased array radar data, the proposed method verified that the computational complexity is much smaller than conventional STAP methods. The proposed element-order recursive method for STAP is applicable for practical airborne phased radar system.     

正则Petri网的研究

State equation method based on incidence matrix ,which shows the structural property of Petri Nets ,has been used widely in the reachability analysis ot Petri Nets. However,due to the state explosion, the complexity of this method increased exponentially when the rank of this incidence matrix is not full. So in this paper ,a new Petri Net model——full rank Petri Net has been proposed to solve this problem.     

Soft sensing modelling based on optimal selection of secondary variables and its application

The composition of the distillation column is a very important quality value in refineries, unfortunately, few hardware sensors are available on-line to measure the distillation compositions. In this paper, a novel method using sensitivity matrix analysis and kernel ridge regression （KRR） to implement on-line soft sensing of distillation compositions is proposed. In this approach, the sensitivity matrix analysis is presented to select the most suitable secondary variables to be used as the soft sensor＇s input. The KRR is used to build the composition soft sensor. Application to a simulated distillation column demonstrates the effectiveness of the method.     

Theory and algorithms for two-dimensional warped discrete Fourier transform

In this paper, the two-dimensional Warped Discrete Fourier Transform （2-D WDFT） is developed based on the concept of the 1-D WDFT. An exact computation algorithm is developed for 2-D WDFT based on matrix factorizing with special structure. A fast algorithm is then proposed to reduce greatly the computational complexity of the inverse 2-D WDFT. Finally, numerical examples are given to show the efficiency of the proposed approach.     

Sparse representation and blind source separation of ill-posed mixtures

Bofill et al. discussed blind source separation (BSS) of sparse signals in the case of two sensors. However, as Bofill et al. pointed out, this method has some limitation. The potential function they introduced is lack of theoretical basis. Also the method could not be extended to solve the problem in the case of more than three sensors. In this paper, instead of the potential function method, a K-PCA method (combining K-clustering with PCA) is proposed. The new method is easy to be used in the case of more than three sensors. It is easy to be implemented and can provide accurate estimation of mixing matrix. Some criterion is given to check the effect of the mixing matrix A . Some simulations illustrate the availability and accuracy of the method we proposed.     

判定矩阵稳定、正定以及为M矩阵的统一简化条件

本文给出了一个判定矩阵稳定,正定以及为Ｍ矩阵的统一简化条件,基于该条件提出的判定方法简化了计算,因而应用十分方便,文中给出三个示例说明了方法的应用。     

A matrix gradient algorithm for identification of parameterized time‐varying parameters

This paper considers the problem of estimating time‐varying parameters which can be parameterized by a series of arbitrary known basis functions. It is shown that this problem is equivalent to the observer design problem for a “matrix” dynamic system. A “matrix” gradient algorithm, which mimics the well‐known “vector” gradient algorithm, is proposed to estimate the unknown matrix. The contribution of this paper is to show that convergence of the proposed matrix algorithm is guaranteed by the persistent excitations of both the regressor and the basis functions. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

实时SAR成像系统矩阵转置方法研究与实现

合成孔径雷达（SAR）是一种高分辨率成像雷达,而矩阵转置是实时SAR成像信号处理中一个很重要的操作,矩阵转置的效率高低将直接决定整个SAR成像信号处理系统的性能。对于矩阵转置,可采用行进列出或列进行出、两页式或三页式转置等方法进行处理,但这些方法处理时间较长,转置效率较低。在现有矩阵转置方法的基础上,提出了一种新的矩阵转置方法。在实际硬件平台上利用提出的矩阵转置方法进行了实时SAR成像处理,所得结果的矩阵转置效率为78%,整个SAR成像处理时间为10秒。测试结果表明,该方法对解决矩阵转置问题是行之有效的。     

概率差别矩阵与不完备信息系统属性约简

差别矩阵的概念是基于粗糙集理论对信息系统进行属性约简的一个重要内容。针对不完备信息系统的属性约简本文提出了一种概率差别矩阵的概念与构造方法，给出了相关的定理。在此基础上提出了一种利用概率差别矩阵对不完备信息系统属性约简的方法，并给出了应用举例。     

一种分明矩阵法的推广

属性约简是知识发现的重要研究内容,也是Rough集理论的核心内容之一。目前,最常用的计算所有属性约简方法是Skowron的分明矩阵法。文中在深入研究Skowron分明矩阵法的基础上,对Skowron的分明矩阵法进行了推广,提出了广义分明矩阵的属性约简方法,并给出了运行实例。     

Weighted steepest descent method for solving matrix equations

This paper describes iterative methods for solving the general linear matrix equation including the well-known Lyapunov matrix equation, Sylvester matrix equation and some related matrix equations encountered in control system theory, as special cases. We develop the methods from the optimization point of view in the sense that the iterative algorithms are constructed to solve some optimization problems whose solutions are closely related to the unique solution to the linear matrix equation. Actually, two optimization problems are considered and, therefore, two iterative algorithms are proposed to solve the linear matrix equation. To solve the two optimization problems, the steepest descent method is adopted. By means of the so-called weighted inner product that is defined and studied in this paper, the convergence properties of the algorithms are analysed. It is shown that the algorithms converge at least linearly for arbitrary initial conditions. The proposed approaches are expected to be numerically reliable as only matrix manipulation is required. Numerical examples show the effectiveness of the proposed algorithms.     

Q-矩阵准规则LDPC码编码器设计方案的研究

本文给出了Q矩阵的定义,找到了一种快速搜索9矩阵的算法,并在此基础上提出一种准规则LDPC码编码器设计方案。该设计方案将奇偶校验矩阵H分解成两个子矩阵,通过对这两个子矩阵结构的设计,构造出H矩阵。本文提出的准规则LDPC码编码器算法具有较低的实现复杂度,为LDPC码编码器的设计提供了最佳选择方案。     

面向定制结构的稀疏矩阵分块方法

稀疏矩阵向量乘是科学计算的核心问题,采用定制结构来加速稀疏矩阵向量乘的执行对提升科学计算性能具有重要意义。针对目前面向定制结构的稀疏矩阵分块方法和表示方法的缺点,提出了稀疏矩阵二维均匀分块方法和相应的表示方法嵌套分块CSR。实验结果表明,提出的稀疏矩阵分块方法和表示方法能够有效减少填零个数。     

基于低秩表示的非负张量分解算法

为了提高图像分类准确率,提出了一种基于低秩表示的非负张量分解算法。作为压缩感知理论的推广和发展,低秩表示将矩阵的秩作为一种稀疏测度,由于矩阵的秩反映了矩阵的固有特性,所以低秩表示能有效的分析和处理矩阵数据,本文把低秩表示引入到张量模型中,即引入到非负张量分解算法中,进一步扩展非负张量分解算法。实验结果表明,本文所提算法与其他相关算法相比,分类结果较好。