A self-organizing quasi-linear ARX RBFN model for nonlinear dynamical systems identification

• Main Authors: Sutrisno, Imam, Jami'in, Mohammad Abu, Hu, Jinglu, Marhaban, Mohammad Hamiruce
• Format: Article
• Language: English
• Published: The Society of Instrument and Control Engineers 2016
• Online Access: http://psasir.upm.edu.my/id/eprint/34850/1/A%20self-organizing%20quasi-linear%20ARX%20RBFN%20model%20for%20nonlinear%20dynamical%20systems%20identification.pdf; http://psasir.upm.edu.my/id/eprint/34850/; https://www.jstage.jst.go.jp/article/jcmsi/9/2/9_70/_article

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.