DocumentCode :
3308880
Title :
Network structure preserving model reduction with weak a priori structural information
Author :
Yeung, E. ; Gonçalves, J. ; Sandberg, H. ; Warnick, S.
Author_Institution :
Inf. & Decision Algorithms Labs., Brigham Young Univ., Provo, UT, USA
fYear :
2009
fDate :
15-18 Dec. 2009
Firstpage :
3256
Lastpage :
3263
Abstract :
This paper extends a state projection method for structure preserving model reduction to situations where only a weaker notion of system structure is available. This weaker notion of structure, identifying the causal relationship between manifest variables of the system, is especially relevant is settings such as systems biology, where a clear partition of state variables into distinct subsystems may be unknown, or not even exist. The resulting technique, like similar approaches, does not provide theoretical performance guarantees, so an extensive computational study is conducted, and it is observed to work fairly well in practice. Moreover, conditions characterizing structurally minimal realizations and sufficient conditions characterizing edge loss resulting from the reduction process, are presented.
Keywords :
modelling; causal relationship; edge loss characterization; network structure preserving model reduction; state projection method; system structure; Automatic control; Biological systems; Chemical industry; Control systems; Laboratories; Power system dynamics; Power system interconnection; Power system modeling; Reduced order systems; Transfer functions;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on
Conference_Location :
Shanghai
ISSN :
0191-2216
Print_ISBN :
978-1-4244-3871-6
Electronic_ISBN :
0191-2216
Type :
conf
DOI :
10.1109/CDC.2009.5400375
Filename :
5400375
Link To Document :
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