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Integrated OBF-NN models for extrapolation enhancement in conventional neural networks for nonlinear systems

H., Zabiri and M., Ramasamy and Lemma D, Tufa and Maulud, Abdulhalim (2011) Integrated OBF-NN models for extrapolation enhancement in conventional neural networks for nonlinear systems. In: Australian Control Conference (AUCC), 2011 , 10-11 Nov. 2011 , Melbourne, Australia.

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Official URL: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumb...

Abstract

Abstract In this paper the integration of linear and nonlinear models in parallel for nonlinear system identification is investigated. A residuals-based sequential identification algorithm using parallel integration of linear Orthornormal basis filters (OBF) and a nonlinear feedforward (MLP) NN model is used and applied to the nonlinear Van de Vusse reactor. Results show improved extrapolation capability of the proposed method in comparison to conventional MLP NN, and opens up a promising area for further research and analysis.

Item Type:Conference or Workshop Item (Paper)
Subjects:T Technology > TP Chemical technology
Academic Subject One:Academic Department - Chemical Engineering - Advance Process Control
Departments / MOR / COE:Departments > Chemical Engineering
ID Code:10748
Deposited By: Haslinda Zabiri
Deposited On:16 Dec 2013 23:48
Last Modified:16 Dec 2013 23:48

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