Self-organizing quasi-linear ARX RBFN modeling for identification and control of nonlinear systems

Imam Sutrisno, Mohammad Abu Jami'In, Takayuki Furuzuki, Mohammad Hamiruce Marhaban

研究成果: Conference contribution

4 被引用数 (Scopus)

抄録

The quasi-linear ARX radial basis function network (QARX-RBFN) model has shown good approximation ability and usefulness in nonlinear system identification and control. It owns an ARX-like structure, easy design, good generalization and strong tolerance to input noise. However, the QARX-RBFN model still needs to improve the prediction accuracy by optimizing its structure. In this paper, a novel self-organizing QARX-RBFN (SOQARX-RBFN) model is proposed to solve this problem. The proposed SOQARX-RBFN model consists of simultaneously network construction and parameter optimization. It offers two important advantages. Firstly, the hidden neurons in the SOQARX-RBFN model can be added or removed, based on the neuron activity and mutual information (MI), to achieve the appropriate network complexity and maintain overall computational efficiency for identification. Secondly, the model performance can be significantly improved through the structure optimization. Additionally, the convergence of the SOQARX-RBFN model is analyzed, and the proposed approach is applied to identify and control the nonlinear dynamical systems. Mathematical system simulations are carried out to demonstrate the effectiveness of the proposed method.

本文言語English
ホスト出版物のタイトル2015 54th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2015
出版社Institute of Electrical and Electronics Engineers Inc.
ページ642-647
ページ数6
ISBN(印刷版)9784907764487
DOI
出版ステータスPublished - 2015 9 30
イベント54th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2015 - Hangzhou, China
継続期間: 2015 7 282015 7 30

Other

Other54th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2015
国/地域China
CityHangzhou
Period15/7/2815/7/30

ASJC Scopus subject areas

  • 制御およびシステム工学

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