Linear model reduction and solution of the algebraic Riccati equation by use of the sign function†
Jeffrey Roberts
Abstract
Jeffrey Roberts
Abstract
The sign function of a square matrix can be defined in terms of a contour integral or as the result of an iterated map $. Application of this function enables a matrix to be decomposed into two components whose spectra lie on opposite sides of the imaginary axis. This has application in reduction of linear systems to lower order models and in the solution of the matrix Lyapunov and algebraic Riccati equations.
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The sign function of a square matrix can be defined in terms of a contour integral or as the result of an iterated map $. Application of this function enables a matrix to be decomposed into two components whose spectra lie on opposite sides of the imaginary axis. This has application in reduction of linear systems to lower order models and in the solution of the matrix Lyapunov and algebraic Riccati equations.
Key concepts: Riccati equation, Sign (mathematics), Mathematics, Algebraic Riccati equation, Reduction (mathematics), Applied mathematics, Algebraic number, Function (biology)