A self-organizing quasi-linear ARX RBFN model for nonlinear dynamical systems identification
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 qu...
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| Format: | Article |
| Language: | English |
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The Society of Instrument and Control Engineers
2016
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| Online Access: | http://psasir.upm.edu.my/id/eprint/34850/ http://psasir.upm.edu.my/id/eprint/34850/1/A%20self-organizing%20quasi-linear%20ARX%20RBFN%20model%20for%20nonlinear%20dynamical%20systems%20identification.pdf |
| _version_ | 1848847889212637184 |
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| author | Sutrisno, Imam Jami'in, Mohammad Abu Hu, Jinglu Marhaban, Mohammad Hamiruce |
| author_facet | Sutrisno, Imam Jami'in, Mohammad Abu Hu, Jinglu Marhaban, Mohammad Hamiruce |
| author_sort | Sutrisno, Imam |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-15T09:25:46Z |
| format | Article |
| id | upm-34850 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T09:25:46Z |
| publishDate | 2016 |
| publisher | The Society of Instrument and Control Engineers |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-348502016-10-10T05:33:06Z http://psasir.upm.edu.my/id/eprint/34850/ A self-organizing quasi-linear ARX RBFN model for nonlinear dynamical systems identification Sutrisno, Imam Jami'in, Mohammad Abu Hu, Jinglu Marhaban, Mohammad Hamiruce 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. The Society of Instrument and Control Engineers 2016 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/34850/1/A%20self-organizing%20quasi-linear%20ARX%20RBFN%20model%20for%20nonlinear%20dynamical%20systems%20identification.pdf Sutrisno, Imam and Jami'in, Mohammad Abu and Hu, Jinglu and Marhaban, Mohammad Hamiruce (2016) A self-organizing quasi-linear ARX RBFN model for nonlinear dynamical systems identification. SICE Journal of Control, Measurement, and System Integration, 9 (2). pp. 70-77. ISSN 1882-4889; ESSN: 1884-9970 https://www.jstage.jst.go.jp/article/jcmsi/9/2/9_70/_article 10.9746/jcmsi.9.70 |
| spellingShingle | Sutrisno, Imam Jami'in, Mohammad Abu Hu, Jinglu Marhaban, Mohammad Hamiruce A self-organizing quasi-linear ARX RBFN model for nonlinear dynamical systems identification |
| title | A self-organizing quasi-linear ARX RBFN model for nonlinear dynamical systems identification |
| title_full | A self-organizing quasi-linear ARX RBFN model for nonlinear dynamical systems identification |
| title_fullStr | A self-organizing quasi-linear ARX RBFN model for nonlinear dynamical systems identification |
| title_full_unstemmed | A self-organizing quasi-linear ARX RBFN model for nonlinear dynamical systems identification |
| title_short | A self-organizing quasi-linear ARX RBFN model for nonlinear dynamical systems identification |
| title_sort | self-organizing quasi-linear arx rbfn model for nonlinear dynamical systems identification |
| url | http://psasir.upm.edu.my/id/eprint/34850/ http://psasir.upm.edu.my/id/eprint/34850/ http://psasir.upm.edu.my/id/eprint/34850/ http://psasir.upm.edu.my/id/eprint/34850/1/A%20self-organizing%20quasi-linear%20ARX%20RBFN%20model%20for%20nonlinear%20dynamical%20systems%20identification.pdf |