By Topic

Solving linear matrix equations in control problems on distributed memory multiprocessors

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
V. Hernandez ; Dept. de Sistemas Inf. y Comput., Univ. Politecnica de Valencia, Spain ; E. S. Quintana ; M. Marques

Linear matrix equations such as Sylvester, Lyapunov and commutant matrix equations play an important role in many control problems, like the design of Luenberger's observers, pole assignment problems, system balancing and model reduction, inertia and stability problems, generic matrix function computation, etc. Two of the most efficient methods for solving linear matrix equations are the Schur algorithm and the Hessenberg-Schur algorithm. In this paper, we present parallel cyclic algorithms based on the Schur and Hessenberg-Schur methods for solving the Sylvester matrix equation. We also present parallel cyclic algorithms based on the Schur method for solving Lyapunov and commutant matrix equations. In the case of Lyapunov equations we also consider the problem of computing the Cholesky factor of the unknown matrix

Published in:

Decision and Control, 1994., Proceedings of the 33rd IEEE Conference on  (Volume:1 )

Date of Conference:

14-16 Dec 1994