Nonlinear System Identification via Basis Functions Based Time Domain Volterra Model
This paper proposes basis functions based time domain Volterra model for nonlinear system identification. The Volterra kernels are expanded by using complex exponential basis functions and estimated via genetic algorithm (GA). The accuracy and practicability of the proposed method are then assessed...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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EDP Sciences
2014-07-01
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| Series: | MATEC Web of Conferences |
| Online Access: | http://dx.doi.org/10.1051/matecconf/20141302031 |
| _version_ | 1798027106948481024 |
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| author | Yazid Edwar Liew M.S. Parman Setyamartana Kurian V.J. Ng C.Y. |
| author_facet | Yazid Edwar Liew M.S. Parman Setyamartana Kurian V.J. Ng C.Y. |
| author_sort | Yazid Edwar |
| collection | DOAJ |
| description | This paper proposes basis functions based time domain Volterra model for nonlinear system identification. The Volterra kernels are expanded by using complex exponential basis functions and estimated via genetic algorithm (GA). The accuracy and practicability of the proposed method are then assessed experimentally from a scaled 1:100 model of a prototype truss spar platform. Identification results in time and frequency domain are presented and coherent functions are performed to check the quality of the identification results. It is shown that results between experimental data and proposed method are in good agreement. |
| first_indexed | 2024-04-11T18:46:06Z |
| format | Article |
| id | doaj.art-3d5e641e27564b669848878103bf550b |
| institution | Directory Open Access Journal |
| issn | 2261-236X |
| language | English |
| last_indexed | 2024-04-11T18:46:06Z |
| publishDate | 2014-07-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | MATEC Web of Conferences |
| spelling | doaj.art-3d5e641e27564b669848878103bf550b2022-12-22T04:08:43ZengEDP SciencesMATEC Web of Conferences2261-236X2014-07-01130203110.1051/matecconf/20141302031matecconf_icper2014_02031Nonlinear System Identification via Basis Functions Based Time Domain Volterra ModelYazid Edwar0Liew M.S.1Parman Setyamartana2Kurian V.J.3Ng C.Y.4Mechanical Engineering Department, Universiti Teknologi PetronasCivil Engineering Department, Universiti Teknologi PetronasMechanical Engineering Department, Universiti Teknologi PetronasCivil Engineering Department, Universiti Teknologi PetronasCivil Engineering Department, Universiti Teknologi PetronasThis paper proposes basis functions based time domain Volterra model for nonlinear system identification. The Volterra kernels are expanded by using complex exponential basis functions and estimated via genetic algorithm (GA). The accuracy and practicability of the proposed method are then assessed experimentally from a scaled 1:100 model of a prototype truss spar platform. Identification results in time and frequency domain are presented and coherent functions are performed to check the quality of the identification results. It is shown that results between experimental data and proposed method are in good agreement.http://dx.doi.org/10.1051/matecconf/20141302031 |
| spellingShingle | Yazid Edwar Liew M.S. Parman Setyamartana Kurian V.J. Ng C.Y. Nonlinear System Identification via Basis Functions Based Time Domain Volterra Model MATEC Web of Conferences |
| title | Nonlinear System Identification via Basis Functions Based Time Domain Volterra Model |
| title_full | Nonlinear System Identification via Basis Functions Based Time Domain Volterra Model |
| title_fullStr | Nonlinear System Identification via Basis Functions Based Time Domain Volterra Model |
| title_full_unstemmed | Nonlinear System Identification via Basis Functions Based Time Domain Volterra Model |
| title_short | Nonlinear System Identification via Basis Functions Based Time Domain Volterra Model |
| title_sort | nonlinear system identification via basis functions based time domain volterra model |
| url | http://dx.doi.org/10.1051/matecconf/20141302031 |
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