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Network structure preserving model reduction with weak a priori structural information
Yeung, E.; Goncalves, Jorge; Sandberg, H. et al.
2009In The proceedings of the Joint 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference
Peer reviewed
 

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Abstract :
[en] 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.
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Yeung, E.
Goncalves, Jorge ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
Sandberg, H.
Warnick, S.
Language :
English
Title :
Network structure preserving model reduction with weak a priori structural information
Publication date :
2009
Event name :
Joint 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference
Event place :
Shangai, China
Event date :
December 16-18, 2009
Main work title :
The proceedings of the Joint 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference
Publisher :
IEEE
ISBN/EAN :
978-1-4244-3872-3
Pages :
3256-3263
Peer reviewed :
Peer reviewed
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