DocumentCode
921681
Title
Solving large-scale control problems
Author
Benner, Peter
Author_Institution
Technische Univ. Chemnitz-Zwickau, Chemnitz, Germany
Volume
24
Issue
1
fYear
2004
Firstpage
44
Lastpage
59
Abstract
In this article we discuss sparse matrix algorithms and parallel algorithms, as well as their application to large-scale systems. For illustration, we solve the linear-quadratic regulator (LQR) problem and apply balanced truncation model reduction using either parallel computing or sparse matrix algorithms. We conclude that modern tools from numerical linear algebra, along with careful investigation and exploitation of the problem structure, can be used to derive algorithms capable of solving large control problems. Since these approaches are implemented in production-quality software, control engineers can employ complex models and use computational tools to analyse and design feedback control laws.
Keywords
control system CAD; control system analysis computing; large-scale systems; linear quadratic control; parallel algorithms; reduced order systems; sparse matrices; balanced truncation model reduction; feedback control; large control problems; large-scale systems; linear-quadratic regulator; numerical linear algebra; parallel algorithms; parallel computing; production-quality software; sparse matrix algorithms; Computational modeling; Design engineering; Large-scale systems; Linear algebra; Parallel algorithms; Parallel processing; Reduced order systems; Regulators; Software tools; Sparse matrices;
fLanguage
English
Journal_Title
Control Systems, IEEE
Publisher
ieee
ISSN
1066-033X
Type
jour
DOI
10.1109/MCS.2004.1272745
Filename
1272745
Link To Document