An algorithm to assign canonical forms by state feedback

B. Datta, K. Datta
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引用次数: 2

Abstract

A procedure for assigning an arbitrary normalized Hessenberg matrix is presented. Specifically, given a controller-Hessenberg pair (A,b) and a normalized upper Hessenberg matrix B, the algorithm computes an upper triangular matrix L=(l/sub ij/) and a row vector f/sup T/ such that L(A-b/sup T/f/sup T/)L/sup -1/=B/sup T/. It is formulated in such a way that the columns of L can be scaled to have unit lengths. Since the class of normalized Hessenberg matrices contains important canonical forms, such as companion, Schwarz, Rough, a Jordan matrix associated with a single eigenvalue, or any bidiagonal matrix having its eigenvalues on the diagonal, the method can be used to assign all these important canonical forms and also an arbitrary set of eigenvalues. After the initial reduction to the Hessenberg form, the method requires only the evaluation of a simple recursion, which becomes extremely simplified in all of these cases. It is also easy to program on a computer. A theoretical operations count suggests that the method is more efficient as an eigenvalue-assignment procedure than the best-known previous procedures.<>
一种基于状态反馈的规范化形式分配算法
给出了一种赋值任意归一化海森伯格矩阵的方法。具体来说,给定一个控制器-Hessenberg对(a,b)和一个归一化的上Hessenberg矩阵b,该算法计算一个上三角矩阵L=(L/下标ij/)和一个行向量f/sup T/,使得L(a -b/sup T/f/sup T/)L/sup -1/= b/sup T/。它是这样表述的:L的列可以缩放成单位长度。由于归一化的Hessenberg矩阵类包含重要的规范形式,如companion, Schwarz, Rough,与单个特征值相关的Jordan矩阵,或任何具有其特征值在对角线上的双对角线矩阵,该方法可以用于分配所有这些重要的规范形式以及任意的特征值集。在初始化简为Hessenberg形式之后,该方法只需要计算一个简单的递归,在所有这些情况下都变得非常简化。在电脑上编程也很容易。理论操作计数表明,该方法作为特征值分配过程比以前最著名的过程更有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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