非线性刚性微分-代数系统的波形松弛离散法

研究基于Runge-Kutta方法的波形松弛离散过程,得到新的刚性微分-代数系统的收敛理论,及该类系统解的存在性和惟一性,并用具体算例测试该理论的有效实用性.     

计算微分代数系统稳定域的迭代Lyapunov函数方法

用迭代Lyapunov函数方法对微分代数系统稳定域进行了研究,根据所研究的微分代数系统形式,构造一个Lyapunov函数,然后对这个Lyapunov函数进行逐次迭代,给出了微分代数系统稳定域逐次扩大的迭代算法,数值实验表明迭代Lyapunov函数方法应用于微分代数系统稳定域的估计比单个Lyapunov函数具有良好的优越性。     

Bnach空间积-微分方程两点边值问题

本文利用一些新的微分和积分不等式研究了Bnach空间中积-微分方程的两点边值问题解的存在唯一性,给出了解的隐式迭代序列和误差估计式.     

Banach空间积-微分方程两点边值问题

本文利用一些新的微分和积分不等式研究了Ｂａｎａｃｈ空间中积－微分方程的 两点边值问题解的存在唯一性,给出了解的隐式迭代序列和误差估计式．     

Banach空间积-微分方程两点边值问题

本文利用一些新的微分和积分不等式研究了Ｂａｎａｃｈ空间中积－微分方程的 两点边值问题解的存在唯一性,给出了解的隐式迭代序列和误差估计式．     

在动载荷作用下框架结构大变形分析的微分代数方法

采用弧坐标首先建立了在动载荷作用下,具有不连续性条件和初始位移的框架结构大变形分析的非线性数学模型．其次, 在空间区域内, 采用微分求积单元法（DQEM）来离散非线性数学模型, 并提出了在使用DQEM来求解结构大变形分析中,多个变量具有间断性条件的有效方法,得到了一组非线性DQEM的离散化方程,它是时间域内的一组具有奇异性的非线性微分-代数方程．同时也给出了求解非线性微分-代数方程组的一个解法A·D2作为应用,求解了受集中力和分布力作用的框架和组合框架的大变形静动力学问题,并与现有结果进行了比较．数值算例表明,处理多个变量具有间断性条件的方法和求解代数-微分系统的方法是一个有效的和一般的方法,它具有较少的节点、 较小的计算工作量、 较高的精度、良好的收敛性、 操作简单以及应用广泛等优点．     

微分代数系统的标准型和分支

我们首先把微分代数系统归结为受限微分方程,且讨论了受限微分系统的参数化问题,即系统的状态空间形式。然后,借助于受限系统的状态空间形式,我们得到了受限微分系统平行于常微分方程的线性化问题和Ｈｏｐｆ分支理论问题的有关结果。     

多体系统动力学微分／代数方程组的一类新的数值分析方法

本文讨论了多体系统动力学微分／代数混合方程组的数值离散问题．首先把参数t并入广义坐标讨论，简化了方程组及其隐含条件的结构，并将其化为指标1的方程组．然后利用方程组的特殊结构，引入一种局部离散技巧并构造了相应的算法．算法结构紧凑，易于编程，具有较高的计算效率和良好的数值性态，且其形式适合于各种数值积分方法的的实施．文末给出了具体算例．     

微分多项式系统的约化算法理论

本文中，作者推广了纯代数形式的特征列集理论（吴方法）为微分形式的相应理论，即建立了在机器证明了诸多微分问题中非常重要的微分多项式组的约化算法理论。引入了一些新的概念和观点使函数微分（导数）具有直观的代数几何表示。给出了Coherent条件下的特征列集的算法。给出的算法易于在计算机上实现并适合应用于广泛的微分问题，如微分方程对称计算，各种微分关系的自动推理等问题。     

Banach空间中混合单调脉冲微分-积分方程解的存在性

本文给出了Banach空间中混合单调脉冲微分-积分方程解、耦合最小最大解的存在性定理及单调迭代方法,改进和推广了[1]-[4]的相应结果．     

An iterative back substitution algorithm for the solution of tridiagonal matrix systems with fringes

For tridiagonal matrix systems, a simple direct algorithm giving the solution exists, but in the most general case of tridiagonal matrix with fringes, the direct solving algorithms are more complicated. For big systems, direct methods are not well fitted and iterative algorithms are preferable. In this paper a relaxation type iterative algorithm is presented. It is an extension of the backward substitution method used for simple tridiagonal matrix systems. The performances show that this algorithm is a good compromise between a direct method and other iterative methods as block SOR. Its nature suggests its use as inner solver in the solution of problems derived by application of a decomposition domain method. A special emphasis is done on the programming aspect. The solving Fortran subroutines implementing the algorithm have been generated automatically from their specification by using a computer algebra system technique.     

Decentralized iterative learning control for a class of large scale interconnected dynamical systems

The problem of decentralized iterative learning control for a class of large scale interconnected dynamical systems is considered. In this paper, it is assumed that the considered large scale dynamical systems are linear time-varying, and the interconnections between each subsystem are unknown. For such a class of uncertain large scale interconnected dynamical systems, a method is presented whereby a class of decentralized local iterative learning control schemes is constructed. It is also shown that under some given conditions, the constructed decentralized local iterative learning controllers can guarantee the asymptotic convergence of the local output error between the given desired local output and the actual local output of each subsystem through the iterative learning process. Finally, as a numerical example, the system coupled by two inverted pendulums is given to illustrate the application of the proposed decentralized iterative learning control schemes.     

Numerical simulations of glacial rebound using preconditioned iterative solution methods

This paper discusses finite element discretization and preconditioning strategies for the iterative solution of nonsymmetric indefinite linear algebraic systems of equations arising in modelling of glacial rebound processes. Some numerical experiments for the purely elastic model setting are provided. Comparisons of the performance of the iterative solution method with a direct solution method are included as well.     

Lower bound for the convergence rate of nonstationary Jacobi-like iteration

Stationary and nonstationary Jacobi-like iterative processes for solving systems of linear algebraic equations are examined. For a system whose coefficient matrix A is an H-matrix, it is shown that the convergence rate of any Jacobi-like process is at least as high as that of the point Jacobi method as applied to a system with 〈A〉 as the coefficient matrix, where 〈A〉 is a comparison matrix of A.     

H-非线性方程组的一种高效迭代解法

１．引言满足参见（［５］）（１．１）的任一非线性刚性函数ｆ（ｙ）：所产生的非线性方程组称之为由 ｆ（ｙ）产生的 Ｈ－非线性方程组,其中 Ａ,Ａ１为与 ｆ（ｙ）的刚性无关的常数,最多为中等大小;的第ｉ个特征值;常数,或者ｖ＞０且最多为中等大小;所谓“中等大小”是指与。相比较而言的;显然,已知;ａ,ｂ,ｃ,ｄ满足且均为常数,（１．２）是由混合（Ｈｙｂｒｉｄ）法解初值问题导出的,其中 ｈ是积分步长．对ｋ１＝ １,即所谓一阶刚性初值问题,混合法已有诸多研究（见［６,９－１１,１４－１６］）;对 ｋ１＝ ２,即所…     

Numerical method for solving a nonlinear time-optimal control problem with additive control

Nonlinear systems whose right-hand sides are divided by the state and control and are linear in control are considered. An iterative method is proposed for solving time-optimal control problems for such systems. The method is based on constructing finite sequences of adjacent simplexes with their vertices lying on the boundaries of reachability sets. For a controllable system, it is proved that the minimizing sequence converges to an ?-optimal solution in a finite number of iterations.     

Generalizations and modifications of the GMRES iterative method

For solving nonsymmetric linear systems, the well-known GMRES method is considered to be a stable method; however, the work per iteration increases as the number of iterations increases. We consider two new iterative methods GGMRES and MGMRES, which are a generalization and a modification of the GMRES method, respectively. Instead of using a minimization condition as in the derivation of GGMRES, we use a Galerkin condition to derive the MGMRES method. We also introduce another new iterative method, LAN/MGMRES, which is designed to combine the reliability of GMRES with the reduced work of a Lanczos-type method. A computer program has been written based on the use of the LAN/MGMRES algorithm for solving nonsymmetric linear systems arising from certain elliptic problems. Numerical tests are presented comparing this algorithm with some other commonly used iterative algorithms. These preliminary tests of the LAN/MGMRES algorithm show that it is comparable in terms of both the approximate number of iterations and the overall convergence behavior. This revised version was published online in June 2006 with corrections to the Cover Date.     

Operator-splitting methods in respect of eigenvalue problems for nonlinear equations and applications for Burgers equations

In this article we consider iterative operator-splitting methods for nonlinear differential equations with respect to their eigenvalues. The main focus of the proposed idea is the fixed-point iterative scheme that linearizes our underlying equations. On the basis of the approximated eigenvalues of such linearized systems we choose the order of the operators for our iterative splitting scheme. The convergence properties of such a mixed method are studied and demonstrated. We confirm with numerical applications the effectiveness of the proposed scheme in comparison with the standard operator-splitting methods by providing improved results and convergence rates. We apply our results to deposition processes.     

Superfast Iterative Solvers for Linear Matrix Equations

Superfast algorithms for solving large systems of linear equations are developed on the basis of an original method for multistep decomposition of a linear multidimensional dynamical system. Examples of analytical synthesis of iterative solvers for matrices of the general form and for large numerical systems of linear algebraic equations are given. For the analytical case, it is shown that convergence occurs at the second iteration.     

A rational Arnoldi approach for ill-conditioned linear systems

For the solution of full-rank ill-posed linear systems a new approach based on the Arnoldi algorithm is presented. Working with regularized systems, the method theoretically reconstructs the true solution by means of the computation of a suitable function of matrix. In this sense, the method can be referred to as an iterative refinement process. Numerical experiments arising from integral equations and interpolation theory are presented. Finally, the method is extended to work in connection with the standard Tikhonov regularization with the right-hand side contaminated by noise.