Identification method of neuro-fuzzy-based Hammerstein model with coloured noise

In this study, neuro-fuzzy-based identification procedure for Hammerstein model with coloured noise is presented. Separable signal is used to realise the decoupling of the identification of dynamic linear part from that of static non-linear part, and then correlation analysis method is adopted to id...

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Bibliographic Details
Published in:	IET control theory & applications Vol. 11; no. 17; pp. 3026 - 3037
Main Authors:	Li, Feng, Li, Jia, Peng, Daogang
Format:	Journal Article
Language:	English
Published:	The Institution of Engineering and Technology 24.11.2017
Subjects:	coloured noise convergence analysis correlation analysis method dynamic linear part fuzzy control fuzzy neural nets gradient methods gradient search theory identification identification method linear systems martingale theory multiinnovation‐based extended stochastic gradient approach neurocontrollers neuro‐fuzzy‐based Hammerstein model neuro‐fuzzy‐based identification procedure nonlinear control systems parameter estimation parameter estimation error persistent excitation condition Research Article search problems static nonlinear part stochastic processes fuzzy neural nets martingale theory correlation analysis method linear systems neuro-fuzzy-based Hammerstein model static nonlinear part fuzzy control identification method identification dynamic linear part neuro-fuzzy-based identification procedure convergence analysis neurocontrollers nonlinear control systems gradient search theory coloured noise parameter estimation stochastic processes persistent excitation condition gradient methods multiinnovation-based extended stochastic gradient approach search problems parameter estimation error
ISSN:	1751-8644, 1751-8652
Online Access:	Get full text
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