Please use this identifier to cite or link to this item: https://doi.org/10.3724/SP.J.1004.2013.00690
Title: Research on multi-signal based neuro-fuzzy Hammerstein-Wiener model
Authors: Jia, L.
Yang, A.-H.
Chiu, M.-S. 
Keywords: Hammerstein-Wiener model
Neuro-fuzzy systems
Nonlinear systems
Signal separation
Issue Date: May-2013
Source: Jia, L.,Yang, A.-H.,Chiu, M.-S. (2013-05). Research on multi-signal based neuro-fuzzy Hammerstein-Wiener model. Zidonghua Xuebao/Acta Automatica Sinica 39 (5) : 690-696. ScholarBank@NUS Repository. https://doi.org/10.3724/SP.J.1004.2013.00690
Abstract: In order to solve the control problem of complex systems, it is important to design a special structure model with data information to simplify the question of designing control system. Thus, a multi-signal based neuro-fuzzy Hammerstein-Wiener model is proposed, which breaks through the traditional iterative separation method. The separation of the neuro-fuzzy nonlinear and linear parts of the Hammerstein-Wiener model is realized by one kind of multi-signals. And a noniterative neuro-fuzzy optimization algorithm is designed to expand the research results to piecewise nonlinear system, which can be applied to much more nonlinear systems. This algorithm guarantees the precision of the model. Moreover, it has the ability of approximating strong nonlinearity. Furthermore, a neuro-fuzzy Hammerstein-Wiener model based control system is designed to simplify the control problem of the nonlinear system into the problem of linear system by using the special structure of the model. As a result, the traditional PID controller can get a better control result. Simulated results show the effectiveness of the method. Copyright © 2013 Acta Automatica Sinica. All rights reserved.
Source Title: Zidonghua Xuebao/Acta Automatica Sinica
URI: http://scholarbank.nus.edu.sg/handle/10635/64516
ISSN: 02544156
DOI: 10.3724/SP.J.1004.2013.00690
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