A comparison study between integrated OBFARX-NN and OBF-NN for modeling of nonlinear systems in extended regions of operation

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Zabiri, H. and Ariff, M. and Tufa, L.D. and Ramasamy, M. (2014) A comparison study between integrated OBFARX-NN and OBF-NN for modeling of nonlinear systems in extended regions of operation. Applied Mechanics and Materials, 625. pp. 382-385. ISSN 16609336

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Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

In this paper the combination 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-Auto regressive with exogenous input (OBFARX) and a nonlinear neural network (NN) models is developed. The model performance is then compared against previously developed parallel OBF-NN model in a nonlinear CSTR case study in extended regions of operation (i.e. extrapolation capability). Â© 2014 Trans Tech Publications, Switzerland.

Item Type:	Article
Additional Information:	cited By 0; Conference of 3rd International Conference on Process Engineering and Advanced Materials, ICPEAM 2014 ; Conference Date: 3 June 2014 Through 5 June 2014; Conference Code:114811
Uncontrolled Keywords:	Algorithms; Models, Comparison study; Identification algorithms; Linear and nonlinear models; Model performance; NN; Nonlinear neural networks; OBFARX; Parallel integration, Nonlinear systems
Depositing User:	Mr Ahmad Suhairi UTP
Date Deposited:	09 Nov 2023 16:16
Last Modified:	09 Nov 2023 16:16
URI:	https://khub.utp.edu.my/scholars/id/eprint/4777

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