DocumentCode :
2081178
Title :
Prediction uncertainty from models and data
Author :
Renklach, Michael F. ; Packard, Andrew ; Seiler, Pete
Author_Institution :
Dept. of Mech. Eng., California Univ., Berkeley, CA, USA
Volume :
5
fYear :
2002
fDate :
2002
Firstpage :
4135
Abstract :
We present an approach to uncertainty propagation in dynamic systems, exploiting information provided by related experimental results along with their models. Our computational procedure draws from ideas and tools that are now common in robust control theory. A case study on a well-known database of methane combustion experiments and models demonstrates the viability of our proposed method.
Keywords :
optimisation; robust control; computational procedure; dynamic systems; methane combustion experiments; prediction uncertainty; robust control theory; uncertainty propagation; Chemicals; Combustion; Data processing; Databases; Equations; Mechanical engineering; Numerical simulation; Predictive models; Robust control; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference, 2002. Proceedings of the 2002
ISSN :
0743-1619
Print_ISBN :
0-7803-7298-0
Type :
conf
DOI :
10.1109/ACC.2002.1024578
Filename :
1024578
Link To Document :
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