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  • 标题:Globally Optimal H2-Norm Model Reduction: A Numerical Linear Algebra Approach ⁎ ⁎
  • 本地全文:下载
  • 作者:Oscar Mauricio Agudelo ; Christof Vermeersch ; Bart De Moor
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2021
  • 卷号:54
  • 期号:9
  • 页码:564-571
  • DOI:10.1016/j.ifacol.2021.06.117
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractWe show that the H2-norm model reduction problem for single-input/single-output (SISO) linear time-invariant (LTI) systems is essentially an eigenvalue problem (EP), from which the globally optimal solution(s) can be retrieved. The first-order optimality conditions of this model reduction problem constitute a system of multivariate polynomial equations that can be converted to an affine (or inhomogeneous) multiparameter eigenvalue problem (AMEP). We solve this AMEP by using the so-called augmented block Macaulay matrix, which is introduced in this paper and has a special (block) multi-shift invariant null space. The set of all stationary points of the optimization problem, i.e., the (2r)-tuples (r is the order of the reduced model) of affine eigenvalues and eigenvectors of the AMEP, follows from a standard EP related to the structure of that null space. At least one of these (2r)-tuples corresponds to the globally optimal solution of the H2-norm model reduction problem. We present a simple numerical example to illustrate our approach.
  • 关键词:KeywordsModel reductionmultivariate polynomialsaugmented block Macaulay matrixmultiparameter eigenvalue problemsnumerical algorithms
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