Skip to content

Latest commit

 

History

History
162 lines (127 loc) · 12.7 KB

README.md

File metadata and controls

162 lines (127 loc) · 12.7 KB
Raw

MatrixPencils.jl

DOI DocBuild codecov.io Latest The MIT License Aqua QA

Matrix pencil manipulation using Julia

Compatibility

Julia 1.8 and higher.

How to Install

pkg> add MatrixPencils
pkg> test MatrixPencils

About

The Kronecker-canonical form of a linear matrix pencil M − λN basically characterizes the right and left singular structure and the eigenvalue structure of the pencil. The computation of the Kronecker-canonical form may involve the use of ill-conditioned similarity transformations and, therefore, is potentially numerically unstable. Fortunately, alternative staircase forms, called Kronecker-like forms (KLFs), can be determined by employing exclusively orthogonal or unitary similarity transformations and allow to obtain basically the same (or only a part of) structural information on the pencil M − λN. Various KLFs can serve to address, in a numerically reliable way, the main applications of the Kronecker form, such as the computation of minimal left or right nullspace bases, the computation of eigenvalues and zeros, the determination of the normal rank of polynomial and rational matrices, the computation of various factorizations of rational matrices, as well as the solution of linear equations with polynomial or rational matrices. The KLFs are also instrumental for solving computational problems in the analysis of generalized systems described by linear differential- or difference-algebraic equations (also known as descriptor systems).

This collection of Julia functions is an attemp to implement high performance numerical software to compute a range of KLFs which reveal the full or partial Kronecker structure of a linear pencil. The KLFs are computed by performing several pencil reduction operations on a reduced basic form of the initial pencil. These operations efficiently compress the rows or columns of certain submatrices to full rank matrices and simultaneously maintain the reduced basic form. The rank decisions involve the use of rank revealing QR-decompositions with column pivoting or, the more reliable, SVD-decompositions. The overall computational complexity of all reduction algorithms is O(n^3), where n is the largest dimension of the pencil.

Many of the implemented pencil manipulation algorithms are extensions of computational procedures proposed by Professor Paul Van Dooren (Université catholique de Louvain, Belgium) in several seminal contributions in the field of linear algebra and its applications in control systems theory. The author expresses his gratitude to Paul Van Dooren for his friendly support during the implementation of functions for manipulation of polynomial matrices. Therefore, the release v1.0 of the MatrixPencils package is dedicated in his honor on the occasion of his 70th birthday in 2020.

The current version of the package includes the following functions:

Manipulation of general linear matrix pencils

  • pbalance! Balancing linear matrix pencils.
  • pbalqual Evaluation of the balancing quality of a matrix pencils.
  • preduceBF Reduction to the basic condensed form [B A-λE; D C] with E upper triangular and nonsingular.
  • klf Computation of the Kronecker-like form exhibiting the full Kronecker structure.
  • klf_left Computation of the Kronecker-like form exhibiting the left and finite Kronecker structures.
  • klf_leftinf Computation of the Kronecker-like form exhibiting the left and infinite Kronecker structures.
  • klf_right Computation of the Kronecker-like form exhibiting the right Kronecker structure.
  • klf_rlsplit Computation of the Kronecker-like form exhibiting the separation of right and left Kronecker structures.

Manipulation of structured linear matrix pencils of the form [A-λE B; C D]

  • sreduceBF Reduction to the basic condensed form [B A-λE; D C] with E upper triangular and nonsingular.
  • sklf Computation of the Kronecker-like form exhibiting the full Kronecker structure.
  • sklf_left Computation of the Kronecker-like form exhibiting the left Kronecker structure.
  • sklf_right Computation of the Kronecker-like form exhibiting the right Kronecker structure.
  • gsklf Computation of several row partition preserving special Kronecker-like forms.

Manipulation of regular linear matrix pencils

  • regbalance! Balancing regular matrix pencils.
  • isregular Checking the regularity of a pencil.
  • isunimodular Checking the unimodularity of a pencil.
  • fisplit Finite-infinite eigenvalue splitting.
  • sfisplit Special finite-infinite eigenvalue splitting.
  • fihess Finite-infinite eigenvalue splitting in a generalized Hessenberg form.
  • fischur Finite-infinite eigenvalue splitting in a generalized Schur form.
  • fischursep Finite-infinite eigenvalue splitting in an ordered generalized Schur form.
  • sfischursep Special finite-infinite eigenvalue splitting in an ordered generalized Schur form.
  • fiblkdiag Finite-infinite eigenvalue splitting based block diagonalization.
  • gsblkdiag Finite-infinite and stable-unstable eigenvalue splitting based block diagonalization.
  • saloc Spectrum alocation for the pairs (A,B) and (A-λE,B).
  • salocd Spectrum alocation for the dual pairs (A,C) and (A-λE,C).
  • ordeigvals Order-preserving computation of eigenvalues of a Schur matrix or a generalized Schur pair.

Some applications of matrix pencil computations

  • pkstruct Determination of the Kronecker structure information.
  • peigvals Computation of the finite and infinite eigenvalues.
  • pzeros Computation of the finite and infinite zeros.
  • prank Determination of the normal rank.

Some applications to structured linear matrix pencils of the form [A-λE B; C D]

  • spkstruct Determination of the Kronecker structure information.
  • speigvals Computation of the finite and infinite eigenvalues.
  • spzeros Computation of the finite and infinite zeros.
  • sprank Determination of the normal rank.

Manipulation of linearizations of polynomial or rational matrices

  • lsbalance! Scaling of a descriptor system based linearization.
  • lsbalqual Evaluation of the scaling quality of descriptor system based linearizations.
  • lsminreal Computation of minimal order linearizations of the form [A-λE B; C D].
  • lsminreal2 Computation of minimal order linearizations of the form [A-λE B; C D] (potentially more efficient).
  • lpsminreal Computation of strong minimal pencil based linearizations of the form [A-λE B-λF; C-λG D-λH].
  • lsequal Check the equivalence of two linearizations.
  • lpsequal Check the equivalence of two pencil based linearizations.
  • lseval Evaluation of the value of the rational matrix corresponding to a descriptor system based linearization.
  • lpseval Evaluation of the value of the rational matrix corresponding to a pencil based linearization.
  • lps2ls Conversion of a pencil based linearization into a descriptor system based linearization.

Manipulation of polynomial matrices

  • poly2pm Conversion of a polynomial matrix from the Polynomials package format to a 3D matrix.
  • pm2poly Conversion of a polynomial matrix from a 3D matrix to the Polynomials package format.
  • pmdeg Determination of the degree of a polynomial matrix.
  • pmeval Evaluation of a polynomial matrix for a given value of its argument.
  • pmreverse Building the reversal of a polynomial matrix.
  • pmdivrem Quotients and remainders of elementwise divisions of two polynomial matrices.
  • pm2lpCF1 Building a linearization in the first companion Frobenius form.
  • pm2lpCF2 Building a linearization in the second companion Frobenius form.
  • pm2ls Building a structured linearization of a polynomial matrix.
  • ls2pm Computation of the polynomial matrix from its structured linearization.
  • pm2lps Building a linear pencil based structured linearization of a polynomial matrix.
  • lps2pm Computation of the polynomial matrix from its linear pencil based structured linearization.
  • spm2ls Building a structured linearization [A-λE B; C D] of a structured polynomial matrix [T(λ) U(λ); V(λ) W(λ)].
  • spm2lps Building a linear pencil based structured linearization [A-λE B-λF; C-λG D-λH] of a structured polynomial matrix [T(λ) U(λ); V(λ) W(λ)].

Some applications to polynomial matrices

  • pmkstruct Determination of the Kronecker structure and infinite pole-zero structure.
  • pmeigvals Computation of the finite and infinite eigenvalues.
  • pmzeros Computation of the finite and infinite zeros.
  • pmzeros1 Computation of the finite and infinite zeros using linear pencil based structured linearization.
  • pmzeros2 Computation of the finite and infinite zeros using structured pencil based linearization.
  • pmroots Computation of the roots of the determinant of a regular polynomial matrix.
  • pmpoles Computation of the infinite poles.
  • pmpoles1 Computation of the infinite poles using linear pencil based structured linearization.
  • pmpoles2 Computation of the infinite poles using structured pencil based linearization.
  • pmrank Determination of the normal rank.
  • ispmregular Checking the regularity of a polynomial matrix.
  • ispmunimodular Checking the unimodularity of a polynomial matrix.

Manipulation of rational matrices

  • rm2lspm Representation of a rational matrix as a linearization of its strictly proper part plus its polynomial part.
  • rmeval Evaluation of a rational matrix for a given value of its argument.
  • rm2ls Building a descriptor system based structured linearization of a rational matrix.
  • ls2rm Computation of the rational matrix from its descriptor system based structured linearization.
  • rm2lps Building a pencil based structured linearization of a rational matrix.
  • lps2rm Computation of the rational matrix from its pencil based structured linearization.
  • lpmfd2ls Building a descriptor system based structured linearization of a left polynomial matrix fractional description.
  • rpmfd2ls Building a descriptor system based structured linearization of a right polynomial matrix fractional description.
  • lpmfd2lps Building a pencil based structured linearization of a left polynomial matrix fractional description.
  • rpmfd2lps Building a pencil based structured linearization of a right polynomial matrix fractional description.
  • pminv2ls Building a descriptor system based structured linearization of the inverse of a polynomial matrix.
  • pminv2lps Building a pencil based structured linearization of the inverse of a polynomial matrix.

Some applications to rational matrices

  • rmkstruct Determination of the Kronecker structure and infinite pole-zero structure.
  • rmzeros Computation of the finite and infinite zeros using structured pencil based linearization.
  • rmzeros1 Computation of the finite and infinite zeros using linear pencil based structured linearization.
  • rmpoles Computation of the finite and infinite poles using structured pencil based linearization.
  • rmpoles1 Computation of the finite and infinite poles using linear pencil based structured linearization.
  • rmrank Determination of the normal rank.

A complete list of implemented functions is available here.

Future plans

Functional extensions and performance enhancements of some functions will be performed as needs arise.

Supplementary information

The mathematical background and the computational aspects which underly the implementation of functions for polynomial and rational matrices are presented in the eprint arXiv:2006.06825.