Recent developments in large-scale and parallel matrix computations and their applications to linear control problems

Author

Datta, Biswa Nath

Author_Institution

Northern Illinois Univ., DeKalb, IL, USA

Volume

1

fYear

1994

Firstpage

438

Abstract

An overview of some of the existing important Krylov subspace methods that have been developed in the last few years for large-scale solutions of control problems, is given. These algorithms are suitable for large and sparse problems. Also included is a statement of a parallel-block algorithm for the Sylvester-observer matrix equation, suitable for high-performance computing. This is an emerging area of research. A need for an urgent and expanded research in the area of large-scale and parallel computations in control has been outlined in the NSF panel report (1988)

Keywords

large-scale systems; linear systems; matrix algebra; observers; parallel algorithms; Krylov subspace methods; Sylvester-observer matrix equation; high-performance computing; large-scale matrix computations; large-scale solutions; linear control problems; parallel matrix computations; parallel-block algorithm; Books; Computer applications; Concurrent computing; Eigenvalues and eigenfunctions; High performance computing; Large-scale systems; Linear systems; Parallel algorithms; Sparse matrices; Symmetric matrices;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1994., Proceedings of the 33rd IEEE Conference on

Conference_Location

Lake Buena Vista, FL

Print_ISBN

0-7803-1968-0

Type

conf

DOI

10.1109/CDC.1994.410887

Filename

410887