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 :
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