MLP and Elman recurrent neural network modelling for the TRMS
This paper presents a scrutinized investigation on system identification using artificial neural network (ANNs). The main goal for this work is to emphasis the potential benefits of this architecture for real system identification. Among the most prevalent networks are multi-layered perceptron NNs...
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| Format: | Conference or Workshop Item |
| Language: | English |
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2008
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| Online Access: | http://irep.iium.edu.my/7128/ http://irep.iium.edu.my/7128/ http://irep.iium.edu.my/7128/ http://irep.iium.edu.my/7128/1/Siti_CIS_NN_2008.pdf |
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iium-7128 |
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eprints |
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iium-71282012-10-02T00:07:48Z http://irep.iium.edu.my/7128/ MLP and Elman recurrent neural network modelling for the TRMS Toha, Siti Fauziah Tokhi, M. Osman T173.2 Technological change This paper presents a scrutinized investigation on system identification using artificial neural network (ANNs). The main goal for this work is to emphasis the potential benefits of this architecture for real system identification. Among the most prevalent networks are multi-layered perceptron NNs using Levenberg-Marquardt (LM) training algorithm and Elman recurrent NNs. These methods are used for the identification of a twin rotor multi-input multi-output system (TRMS). The TRMS can be perceived as a static test rig for an air vehicle with formidable control challenges. Therefore, an analysis in modeling of nonlinear aerodynamic function is needed and carried out in both time and frequency domains based on observed input and output data. Experimental results are obtained using a laboratory set-up system, confirming the viability and effectiveness of the proposed methodology. 2008 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/7128/1/Siti_CIS_NN_2008.pdf Toha, Siti Fauziah and Tokhi, M. Osman (2008) MLP and Elman recurrent neural network modelling for the TRMS. In: 7th IEEE International Conference on Cybernetic Intelligent Systems (CIS08), 9-10 September 2008, London, U.K.. http://dx.doi.org/10.1109/UKRICIS.2008.4798969 doi:10.1109/UKRICIS.2008.4798969 |
| repository_type |
Digital Repository |
| institution_category |
Local University |
| institution |
International Islamic University Malaysia |
| building |
IIUM Repository |
| collection |
Online Access |
| language |
English |
| topic |
T173.2 Technological change |
| spellingShingle |
T173.2 Technological change Toha, Siti Fauziah Tokhi, M. Osman MLP and Elman recurrent neural network modelling for the TRMS |
| description |
This paper presents a scrutinized investigation on system identification using artificial neural network (ANNs). The main goal for this work is to emphasis the potential benefits of this architecture for real system identification. Among the most prevalent networks are multi-layered perceptron NNs using Levenberg-Marquardt (LM) training algorithm and Elman recurrent NNs. These methods are used for the identification of a twin rotor multi-input multi-output system (TRMS). The TRMS can be perceived as a static test rig for an air vehicle with formidable control challenges. Therefore, an analysis in modeling of nonlinear aerodynamic function is needed and carried out in both time and frequency domains based on observed input and output data. Experimental results are obtained using a laboratory set-up system, confirming the viability and effectiveness of the proposed methodology. |
| format |
Conference or Workshop Item |
| author |
Toha, Siti Fauziah Tokhi, M. Osman |
| author_facet |
Toha, Siti Fauziah Tokhi, M. Osman |
| author_sort |
Toha, Siti Fauziah |
| title |
MLP and Elman recurrent neural network modelling for the TRMS |
| title_short |
MLP and Elman recurrent neural network modelling for the TRMS |
| title_full |
MLP and Elman recurrent neural network modelling for the TRMS |
| title_fullStr |
MLP and Elman recurrent neural network modelling for the TRMS |
| title_full_unstemmed |
MLP and Elman recurrent neural network modelling for the TRMS |
| title_sort |
mlp and elman recurrent neural network modelling for the trms |
| publishDate |
2008 |
| url |
http://irep.iium.edu.my/7128/ http://irep.iium.edu.my/7128/ http://irep.iium.edu.my/7128/ http://irep.iium.edu.my/7128/1/Siti_CIS_NN_2008.pdf |
| first_indexed |
2023-09-18T20:16:25Z |
| last_indexed |
2023-09-18T20:16:25Z |
| _version_ |
1777407817249980416 |