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On numerical solutions of the Sylvester-observer equation, and the multi-input eigenvalue assignment problem.

机译:关于Sylvester-observer方程的数值解以及多输入特征值分配问题。

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摘要

This dissertation is devoted to the study of numerical solutions of two important linear algebra problems arising in control theory: the Sylvester-observer matrix equation and multi-input eigenvalue assignment problem. Two new algorithms are proposed: one for each problem.;The timing and accuracy of the proposed algorithm for the multi-input eigenvalue assignment problem are comparable to those of the existing algorithms for small problems; but for large problems, the new algorithm is much faster.;The basis of these algorithms is a novel generalization of the classical Arnoldi method for constructing an orthonormal basis of the Krylov subspace. This generalization, besides its roles in the solutions of the two above mentioned problems, may be of independent interest and may find applications elsewhere.;The results of the dissertation should be of interest and useful to applied and computational mathematics as well as control theorists and practising control engineers. They are expected to contribute to the development of numerically effective control design software.;The algorithm for the Sylvester-observer equation constructs an orthogonal solution to the equation. From numerical and design points of view, it is highly desirable to have such a solution. None of the existing algorithms, however, constructs such a solution.
机译:本文致力于研究控制理论中两个重要的线性代数问题的数值解:Sylvester-observer矩阵方程和多输入特征值分配问题。提出了两种新算法:一种是针对每个问题。所提出的用于多输入特征值分配问题的算法的时间和准确性与现有的解决小问题的算法相当。这些算法的基础是经典Arnoldi方法的新颖概括,用于构造Krylov子空间的正交基。这种概括,除了在解决上述两个问题中的作用外,可能是独立利益的,并可能在其他地方找到应用。论文的结果应引起人们的兴趣,对应用数学和计算数学以及控制理论家和研究者有用。执业的控制工程师。预期它们将有助于数字有效控制设计软件的开发。Sylvester-observer方程的算法构造了该方程的正交解。从数值和设计的角度来看,非常需要一种这样的解决方案。但是,现有的算法都没有构造这样的解决方案。

著录项

  • 作者单位

    Northern Illinois University.;

  • 授予单位 Northern Illinois University.;
  • 学科 Mathematics.
  • 学位 Ph.D.
  • 年度 1996
  • 页码 117 p.
  • 总页数 117
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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