We consider the numerical solution of the continuous algebraic Riccati equation A*X + XA − XFX + G = 0, with F = F*,G = G* of low rank and A large and sparse. We develop an algorithm for the low-rank approximation of X by means of an invariant subspace iteration on a function of the associated Hamiltonian matrix. We show that the sought-after approximation can be obtained by a low-rank update, in the style of the well known Alternating Direction Implicit (ADI) iteration for the linear equation, from which the new method inherits many algebraic properties. Moreover, we establish new insightful matrix relations with emerging projection-type methods, which will help increase our understanding of this latter class of solution strategies.
Lin, Y., Simoncini, V. (2015). A new subspace iteration method for the algebraic Riccati equation. NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS, 22(1), 26-47 [10.1002/nla.1936].
A new subspace iteration method for the algebraic Riccati equation
SIMONCINI, VALERIA
2015
Abstract
We consider the numerical solution of the continuous algebraic Riccati equation A*X + XA − XFX + G = 0, with F = F*,G = G* of low rank and A large and sparse. We develop an algorithm for the low-rank approximation of X by means of an invariant subspace iteration on a function of the associated Hamiltonian matrix. We show that the sought-after approximation can be obtained by a low-rank update, in the style of the well known Alternating Direction Implicit (ADI) iteration for the linear equation, from which the new method inherits many algebraic properties. Moreover, we establish new insightful matrix relations with emerging projection-type methods, which will help increase our understanding of this latter class of solution strategies.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.