Comparison of Global Nonlinear Models and "Model-on-Demand" Estimation Applied to Identification of a RTP Wafer Reactor
1999 (English)Report (Other academic)
"Model on Demand" (MoD) simulation of the temperature dynamics in a simulated Rapid Thermal Process-ing (RTP) reactor is compared against various types of global models (ARX, semiphysical, combined semiphysical with neural net). The identication data is generated from a m-level pseudo-random sequence input whose parameters are specied systematically using a priori information readily available to the engineer. The MoD estimator outperforms the ARX model and two semi-physical models, while matching the performance of a combined semi-physical with neural net model. This makes MoD estimation an appealing alternative to global methods because of its reduced engineering eort and simplified a priori knowledge regarding model structure.
Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 1999. , 7 p.
LiTH-ISY-R, ISSN 1400-3902 ; 2184
Identification, Non-parametric estimation
IdentifiersURN: urn:nbn:se:liu:diva-55353ISRN: LiTH-ISY-R-2184OAI: oai:DiVA.org:liu-55353DiVA: diva2:316031