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Integrated OBF-NN models with enhanced extrapolation capability for nonlinear systems

H., Zabiri and M., Ramasamy and T. D. , Lemma and Maulud, Abdulhalim (2013) Integrated OBF-NN models with enhanced extrapolation capability for nonlinear systems. [Citation Index Journal]

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Official URL: http://www.sciencedirect.com/science?_ob=ArticleUR...

Abstract

This paper proposes a nonlinear system identification using parallel linear-plus-neural network models that provide more accurate predictions on the process behavior even on extrapolated regions. For this purpose, a residuals-based identification algorithm using parallel integration of linear orthonormal basis filters (OBF) and neural networks model is developed and analyzed under range extrapolations. Results on the van de Vusse reactor case study show enhanced extrapolation capability when compared to the conventional neural network (NN) and the series Wiener-NN models.

Item Type:Citation Index Journal
Impact Factor:1.8
Uncontrolled Keywords:Nonlinear systems Residuals Parallel integration Orthonormal basis filters Neural networks Range extrapolation
Subjects:Q Science > Q Science (General)
T Technology > TP Chemical technology
Academic Subject One:Academic Department - Chemical Engineering - Advance Process Control
Departments / MOR / COE:Departments > Chemical Engineering
ID Code:10745
Deposited By: Haslinda Zabiri
Deposited On:16 Dec 2013 23:47
Last Modified:16 Dec 2013 23:47

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