DocumentCode
2185410
Title
Implicitly restarted Lanczos algorithm for model reduction
Author
Papakos, Vasilios ; Jaimoukha, Lmad M.
Author_Institution
Dept. of Electr. & Electron. Eng., Imperial Coll. of Sci., Technol. & Med., London, UK
Volume
4
fYear
2001
fDate
2001
Firstpage
3671
Abstract
The Lanczos algorithm is increasingly used for model reduction of large scale stable systems. Two features of the algorithm, however, limit its applicability: the tendency of the reduced model to poorly approximate low frequency dynamics, and the fact that the approximation is not guaranteed to be stable. This paper tackles these issues via a computationally efficient implicit restart scheme based on balanced truncation which preserves the attractive features of the Lanczos algorithm
Keywords
Lyapunov methods; approximation theory; large-scale systems; linear systems; reduced order systems; stability; Lanczos algorithm; Lyapunov equation; SISO systems; approximation; balanced truncation; large scale systems; linear systems; low frequency dynamics; model reduction; stable systems; Approximation algorithms; Educational institutions; Equations; Erbium; Frequency; Large-scale systems; Reduced order systems; Transfer functions; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 2001. Proceedings of the 40th IEEE Conference on
Conference_Location
Orlando, FL
Print_ISBN
0-7803-7061-9
Type
conf
DOI
10.1109/.2001.980432
Filename
980432
Link To Document