Nonlinear Aeroelastic System Identification Based on Neural Network
This paper focuses on the nonlinear aeroelastic system identification method based on an artificial neural network (ANN) that uses time-delay and feedback elements. A typical two-dimensional wing section with control surface is modelled to illustrate the proposed identification algorithm. The respon...
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-10-01
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| Series: | Applied Sciences |
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| Online Access: | http://www.mdpi.com/2076-3417/8/10/1916 |
| _version_ | 1819013768996192256 |
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| author | Bo Zhang Jinglong Han Haiwei Yun Xiaomao Chen |
| author_facet | Bo Zhang Jinglong Han Haiwei Yun Xiaomao Chen |
| author_sort | Bo Zhang |
| collection | DOAJ |
| description | This paper focuses on the nonlinear aeroelastic system identification method based on an artificial neural network (ANN) that uses time-delay and feedback elements. A typical two-dimensional wing section with control surface is modelled to illustrate the proposed identification algorithm. The response of the system, which applies a sine-chirp input signal on the control surface, is computed by time-marching-integration. A time-delay recurrent neural network (TDRNN) is employed and trained to predict the pitch angle of the system. The chirp and sine excitation signals are used to verify the identified system. Estimation results of the trained neural network are compared with numerical simulation values. Two types of structural nonlinearity are studied, cubic-spring and friction. The results indicate that the TDRNN can approach the nonlinear aeroelastic system exactly. |
| first_indexed | 2024-12-21T02:05:12Z |
| format | Article |
| id | doaj.art-c031dece50734fde902d9552034a1eb4 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-12-21T02:05:12Z |
| publishDate | 2018-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-c031dece50734fde902d9552034a1eb42022-12-21T19:19:31ZengMDPI AGApplied Sciences2076-34172018-10-01810191610.3390/app8101916app8101916Nonlinear Aeroelastic System Identification Based on Neural NetworkBo Zhang0Jinglong Han1Haiwei Yun2Xiaomao Chen3State Key Laboratory of Mechanics and Control of Mechanical Structures, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaState Key Laboratory of Mechanics and Control of Mechanical Structures, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaState Key Laboratory of Mechanics and Control of Mechanical Structures, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaState Key Laboratory of Mechanics and Control of Mechanical Structures, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaThis paper focuses on the nonlinear aeroelastic system identification method based on an artificial neural network (ANN) that uses time-delay and feedback elements. A typical two-dimensional wing section with control surface is modelled to illustrate the proposed identification algorithm. The response of the system, which applies a sine-chirp input signal on the control surface, is computed by time-marching-integration. A time-delay recurrent neural network (TDRNN) is employed and trained to predict the pitch angle of the system. The chirp and sine excitation signals are used to verify the identified system. Estimation results of the trained neural network are compared with numerical simulation values. Two types of structural nonlinearity are studied, cubic-spring and friction. The results indicate that the TDRNN can approach the nonlinear aeroelastic system exactly.http://www.mdpi.com/2076-3417/8/10/1916neural networksystem identificationnonlinear aeroelastic |
| spellingShingle | Bo Zhang Jinglong Han Haiwei Yun Xiaomao Chen Nonlinear Aeroelastic System Identification Based on Neural Network Applied Sciences neural network system identification nonlinear aeroelastic |
| title | Nonlinear Aeroelastic System Identification Based on Neural Network |
| title_full | Nonlinear Aeroelastic System Identification Based on Neural Network |
| title_fullStr | Nonlinear Aeroelastic System Identification Based on Neural Network |
| title_full_unstemmed | Nonlinear Aeroelastic System Identification Based on Neural Network |
| title_short | Nonlinear Aeroelastic System Identification Based on Neural Network |
| title_sort | nonlinear aeroelastic system identification based on neural network |
| topic | neural network system identification nonlinear aeroelastic |
| url | http://www.mdpi.com/2076-3417/8/10/1916 |
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