SICE Journal of Control, Measurement, and System Integration
Online ISSN : 1884-9970
Print ISSN : 1882-4889
Special Issue on SICE Annual Conference 2015
A Self-Organizing Quasi-Linear ARX RBFN Model for Nonlinear Dynamical Systems Identification
Imam SUTRISNOMohammad ABU JAMI’INJinglu HUMohammad HAMIRUCE MARHABAN
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2016 Volume 9 Issue 2 Pages 70-77

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Abstract

The quasi-linear ARX radial basis function network (RBFN) model has shown good approximation ability and usefulness in nonlinear system identification and control. It has an easy-to-use structure, good generalization and strong tolerance to input noise. In this paper, we propose a self-organizing quasi-linear ARX RBFN (QARX-RBFN) model by introducing a self-organizing scheme to the quasi-linear ARX RBFN model. Based on the active firing rate and the mutual information of RBF nodes, the RBF nodes in the quasi-linear ARX RBFN model can be added or removed, so as to automatically optimize the structure of the quasi-linear ARX RBFN model for a given system. This significantly improves the performance of the model. Numerical simulations on both identification and control of nonlinear dynamical system confirm the effectiveness of the proposed self-organizing QARX-RBFN model.

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© 2016 The Society of Instrument and Control Engineers
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