一类离散时间代数Riccati矩阵方程异类约束解的双迭代算法

本文研究在最优控制系统中遇到的离散时间代数Riccati矩阵方程(DTARME)异类约束解的数值计算问题.首先对多变量DTARME中的逆矩阵采用矩阵级数方法进行等价转化,然后采用牛顿算法求多变量DTARME的异类约束解,并采用修正共轭梯度法求由牛顿算法每一步迭代计算导出的线性矩阵方程的异类约束解或者异类约束最小二乘解,建立求多变量DTARME的异类约束解的双迭代算法.双迭代算法仅要求多变量DTARME有异类约束解,不要求它的异类约束解唯一,也不对它的系数矩阵做附加限定.数值算例表明,双迭代算法是有效的.     

求线性矩阵方程双对称最小二乘解的变形共轭梯度法

本文基于求线性代数方程组的共轭梯度法的思想,通过特殊的变形与近似处理,建立了求一般线性矩阵方程的双对称最小二乘解的迭代算法,并证明了迭代算法的收敛性。不考虑舍入误差时,迭代算法能够在有限步计算之后得到矩阵方程的双对称最小二乘解;选取特殊的初始矩阵时,还能够求得矩阵方程的极小范数双对称最小二乘解。同时,也能够给出指定矩阵的最佳逼近双对称矩阵。算例表明,迭代算法是有效的。     

一类双变量Riccati矩阵方程组对称解的迭代算法

基于求线性矩阵方程组约束解的修正共轭梯度法,讨论了由Nash均衡对策导出的一类双矩阵变量Riccati矩阵方程组(R-MEs)对称解的数值计算问题.提出用牛顿算法将R-MEs的对称解问题转化为双矩阵变量线性矩阵方程组的对称解或者对称最小二乘解问题,并采用修正共轭梯度法解决后一计算问题,建立了求R-MEs对称解的新型迭代算法.新型迭代算法仅要求R-MEs有对称解,不要求它的对称解唯一,也不对它的系数矩阵做附加限定.数值算例表明,新型迭代算法是有效的.     

一类矩阵方程组带有子矩阵约束的最小二乘中心对称解

约束矩阵方程问题在控制理论、振动理论、工程和科学计算等领域具有重要应用.基于共轭梯度法的思想,本文构造了一种算法,以寻求一类矩阵方程组的带有子矩阵约束的最小二乘中心对称解.在没有舍入误差的情况下,该算法经过有限步迭代得到了矩阵方程组带子矩阵约束的最小二乘中心对称解,而且,通过选择一种特殊的初始矩阵,得到了矩阵方程组的带子矩阵约束的最小范数最小二乘中心对称解.数值实验显示该算法具有较快的收敛速度.     

非线性方程组自反解的非精确Newton-MCG算法

针对源于科学计算和工程应用领域的非线性代数方程组,本文应用Newton算法求其自反解,并采用修正共轭梯度法(MCG算法)求由Newton算法每一步迭代计算导出的线性代数方程组的近似自反解或其近似自反最小二乘解,建立了求其自反解的非精确Newton-MCG算法.基于MCG算法适用面宽和有限步收敛的特点,建立的非精确Newton-MCG算法仅要求非线性代数方程组有自反解,而不要求它的自反解唯一.数值算例表明,非精确Newton-MCG算法是有效的.     

分数阶电报方程的Chebyshev多项式数值解法研究

分数阶电报方程作为通信工程中的一类重要方程,在实际应用中往往很难求得解析解,因而对其进行数值求解就显得至关重要．为了求得分数阶电报方程的数值解,本文借助Chebyshev多项式函数构造相应的微分算子矩阵,并结合Tau方法将待求方程转化为非线性代数方程组,然后对该方程组进行数值离散求解,最后给出的数值算例也验证了该方法的可行性及有效性．     

一类矩阵方程组的对称解及其最佳逼近

本文建立了求矩阵方程组AiXBi+GiXDi=Fi(i=1,2)对称解的迭代算法.使用该算法可以判断矩阵方程组是否有对称解.在有对称解时,能在有限步迭代后得到矩阵方程组的对称解;当选取特殊初始矩阵时,可得极小范数对称解.另外,在上述解集合中可得到给定矩阵的最佳逼近矩阵表达式.     

求解大型稀疏线性方程组的不完全SAOR预条件共轭梯度法

预条件共轭梯度法是求解大型稀疏线性方程组的有效方法之一,SSOR预条件方法是基于矩阵分裂的较有效的预条件共轭梯度法。通过矩阵分裂,本文讨论不完全SAOR预条件方法,研究此方法的预条件因子及系数矩阵的预条件数,并证明了此方法的预条件数小于SSOR预条件方法的预条件数。最后通过求解离散化波松(Poisson)方程组表明了该方法的有效性。     

鳞状因子循环矩阵方程解的条件与求解的快速算法

利用多项式快速算法,给出了鳞状因子循环矩阵方程AX=b可解的条件与求解的快速算法.当鳞状因子循环矩阵非奇异时,该快速算法求出线性方程组的唯一解;当鳞状因子循环矩阵奇异时,该快速算法求出线性方程组的特解与通解.该快速算法仅用到鳞状因子循环矩阵的第一行元素及对角矩阵中的对角上的常数进行计算.在计算机上实现时只有舍入误差.特别地,在有理数域上用计算机求得的结果是精确的.     

一类周期结构的部分组集有限元法及静动力分析

本文分析了周期结构经有限元离散所形成系数矩阵的元素分布，提出部分组集的有限元法；随后将块ＳＯＲ、块共轭梯度等方法用于求解相应的线性代数方程组，并以此改造求解大型特征值问题的Ｌａｎｃｚｏｓ算法。这些工作使得在一类周期结构静动力分析中能够避免对大规模代数方程组的直接计算。算例表明这些工作大大降低了所需内外存空间     

Iterative techniques for 3-D boundary element method systems of equations

A key issue in the boundary element method (BEM) is the solution of the associated system of algebraic equations whose matrices are dense, nonsymmetric and sometimes ill conditioned. For large scale tridimensional problems, direct methods like Gauss elimination become too expensive and iterative methods may be preferable. This paper presents a comparison of the performances of some iterative techniques based on conjugate gradient solvers as conjugate gradient squared (CGS) and bi-conjugate gradient (Bi-CG) that seem to have the potential to be efficient and competitive for BEM algebraic systems of equations, specially when used with an appropriate preconditioner. A comparison with the direct application of the conjugate gradient method to the normalized systems of equations (CGNE and CGNR) is also presented.     

Non-linear vibration of frames by the incremental dynamic stiffness method

The dynamic stiffness method is extended to large amplitude free and forced vibrations of frames. When the steady state vibration is concerned, the time variable is replaced by the frequency parameter in the Fourier series sense and the governing partial differential equations are replaced by a set of ordinary differential equations in the spatial variables alone. The frequency-dependent shape functons are generated approximately for the spatial discretization. These shape functions are the exact solutions of a beam element subjected to mono-frequency excitation and constant axial force to minimize the spatial discretization errors. The system of ordinary differential equations is replaced by a system of non-linear algebraic equations with the Fourier coefficients of the nodal displacements as unknowns. The Fourier nodal coefficients are solved by the Newtonian algorithm in an incremental manner. When an approximate solution is available, an improved solution is obtained by solving a system of linear equations with the Fourier nodal increments as unknowns. The method is very suitable for parametric studies. When the excitation frequency is taken as a parameter, the free vibration response of various resonances can be obtained without actually computing the linear natural modes. For regular points along the response curves, the accuracy of the gradient matrix (Jacobian or tangential stiffness matrix) is secondary (cf. the modified Newtonian method). However, at the critical positions such as the turning points at resonances and the branching points at bifurcations, the gradient matrix becomes important. The minimum number of harmonic terms required is governed by the conditions of completeness and balanceability for predicting physically realistic response curves. The evaluations of the newly introduced mixed geometric matrices and their derivatives are given explicitly for the computation of the gradient matrix.     

基于二阶矩阵微分方程的机械振动系统线性二次型调节器设计

本文讨论机械振动系统线性二次型状态调节器（LQR）问题，直接针对系统二阶运动微分方程，性能指标为一个依赖于二阶导数的泛函。由欧拉-拉格朗日方程得出一个系统矩阵增广的二阶线性微分方程，指出该方程稳定的特征对就是最优控制振动系统闭环特征对，并给出求解最优控制状态反馈矩阵的方法，另外，由本文方法还可得出基于速度和加速度反馈的最优控制反馈矩阵。这里不涉及求解代数矩阵Riccati方程。     

Iterative solution techniques in boundary element analysis

Iterative techniques for the solution of the algebraic equations associated with the direct boundary element analysis (BEA) method are discussed. Continuum structural response analysis problems are considered, employing single- and multi-zone boundary element models with and without zone condensation. The impact on convergence rate and computer resource requirements associated with the sparse and blocked matrices, resulting in multi-zone BEA, is studied. Both conjugate gradient and generalized minimum residual preconditioned iterative solvers are applied for these problems and the performance of these algorithms is reported. Included is a quantification of the impact of the preconditioning utilized to render the boundary element matrices solvable by the respective iterative methods in a time competitive with direct methods. To characterize the potential of these iterative techniques, we discuss accuracy, storage and timing statistics in comparison with analogous information from direct, sparse blocked matrix factorization procedures. Matrix populations that experience block fill-in during the direct decomposition process are included. With different degrees of preconditioning, iterative equation solving is shown to be competitive with direct methods for the problems considered.     

The solution of sparse linear equations by the conjugate gradient method

The convergence properties of the conjugate gradient method are discussed in relation to relaxation methods and Chebyshev accelerated Jacobi iteration when applied to the solution of large sets of linear equations which have a sparse, symmetric and positive definite coefficient matrix. The conclusion is reached that its convergence rate is unlikely to be much worse than these methods, and may be considerably better. The conjugate gradient method may either be applied to the basic unscaled or scaled equations or alternatively to various transformed equations. Preconditioning, block elimination and partial elimination methods of transforming equations are considered, and some comparative tests given for six problems.     

A comparison of direct and preconditioned iterative techniques for sparse,unsymmetric systems of linear equations

In this paper we compare direct and preconditioned iterative methods for the solution of nonsymmetric, sparse systems of linear algebraic equations. These problems occur in finite difference and finite element simulations of semiconductor devices, and fluid flow problems. We consider five iterative methods that appear to be the most promising for this class of problems: the biconjugate gradient method, the conjugate gradient squared method, the generalized minimal residual method, the generalized conjugate residual method and the method of orthogonal minimization. Each of these methods was tested using similar preconditioning (incomplete LU factorization) on a set of large, sparse matrices arising from finite element simulation of semiconductor devices. Results are shown where we compare the computation time and memory requirements for each of these methods against one another, as well as against a direct method that uses LU factorization to solve these problems. The results of our numerical experiments show that preconditioned iterative methods are a practical alternative to direct methods in the solution of large, sparse systems of equations, and can offer significant savings in storage and CPU time.     

Conjugate gradient methods for three-dimensional BEM systems of equations

A fundamental advantage of the boundary element method (BEM) is that the dimensionality of the problems is reduced by one. However, this advantage has to be weighted against the difficulty in solving the resulting systems of algebraic linear equations whose matrices are dense, non-symmetric and sometimes ill conditioned. For large three-dimensional problems the application of the classical direct methods becomes too expensive.This paper studies the comparative performance of iterative techniques based on conjugate gradient solvers as bi-conjugate gradient (Bi-CG), generalized minimal residual (GMRES), conjugate gradient squared (CGS), quasi-minimal residuals (QMR) and bi-conjugate gradient stabilized (Bi-CGStab) for potential and exterior problems. Preconditioning is also considered and assessed.Two examples, one from electrostatics and other from fluid mechanics, were employed to test these methods, which proved to be effective and competitive as solvers for BEM linear algebraic systems of equations.     

A class of preconditioned conjugate gradient methods for the solution of a mixed finite element discretization of the biharmonic operator

The homogeneous Dirichlet problem for the biharmonic operator is solved as the variational formulation of two coupled second-order equations. The discretization by a mixed finite element model results in a set of linear equations whose coefficient matrix is sparse, symmetric but indefinite. We describe a class of preconditioned conjugate gradient methods for the numerical solution of this linear system. The precondition matrices correspond to incomplete factorizations of the coefficient matrix. The numerical results show a low computational complexity in both number of computer operations and demand of storage.     

Application of a Modified Algorithm of the Method of Conjugate Gradients in Finite-Element Analyses

For the solution of systems of linear algebraic equations by the finite-element method, we consider a generalized method of conjugate gradients with preconditioning matrix constructed by using the transition matrix for the method of symmetric upper relaxation. It is shown that the rate of the iterative process can be doubled. We present the results of the numerical analysis of the rate of convergence of the iterative process in the solution of two-dimensional model problems of the theory of elasticity and linear fracture mechanics with the help of the classical and modified algorithms of the method of conjugate gradients with preconditioning matrix of the method of symmetric upper relaxation. __________ Translated from Problemy Prochnosti, No. 6, pp. 89 – 102, November – December, 2005.     

Circulant preconditioners for ill-conditioned boundary integral equations from potential equations

In this paper, we consider solving potential equations by the boundary integral equation approach. The equations so derived are Fredholm integral equations of the first kind and are known to be ill-conditioned. Their discretized matrices are dense and have condition numbers growing like O(n) where n is the matrix size. We propose to solve the equations by the preconditioned conjugate gradient method with circulant integral operators as preconditioners. These are convolution operators with periodic kernels and hence can be inverted efficiently by using fast Fourier transforms. We prove that the preconditioned systems are well conditioned, and hence the convergence rate of the method is linear. Numerical results for two types of regions are given to illustrate the fast convergence. © 1998 John Wiley & Sons, Ltd.