Intelligent Model for Endpoint Accelerations of Two link Flexible Manipulator Using a Deep Learning Neural Network
This article investigates a two-link flexible manipulator (TLFM) that can be modelled utilizing a deep learning neural network. The system was classified under a multiple-input multiple-output (MIMO) system. In the modelling stage of this study, the TLFM dynamic models were divided into single-input...
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my.unimas.ir.403002022-11-01T01:17:04Z http://ir.unimas.my/id/eprint/40300/ Intelligent Model for Endpoint Accelerations of Two link Flexible Manipulator Using a Deep Learning Neural Network Zidan, Abdulghani Intan Z., Mat Darus Annisa, Jamali T Technology (General) This article investigates a two-link flexible manipulator (TLFM) that can be modelled utilizing a deep learning neural network. The system was classified under a multiple-input multiple-output (MIMO) system. In the modelling stage of this study, the TLFM dynamic models were divided into single-input single-output (SISO) models. Since coupling impact was assumed to be minimised, the characterizations of TLFM were defined independently in each model. Two discrete SISO models of a flexible two link manipulator were developed using the torque input and the endpoint accelerations of each link. The input-output data pairs were collected from experimental work and utilised to establish the system model. The Long Short-Term Memory (LSTM) algorithm optimised using Particle Swarm Optimization (PSO) was selected as the model structure due to the system's high degree of nonlinearity. The identification of the TLFM system utilizing LSTM optimised by PSO was successful, according to the high-performance result of PSO. Using LSTM-PSO, it is demonstrated that both link 1 and 2 models are accurately identified and that their performance in terms of MSE for links endpoint acceleration 1 and 2 is within a 95% confidence interval. 2022-10-28 Proceeding PeerReviewed text en http://ir.unimas.my/id/eprint/40300/1/Intelligent%20Model.pdf Zidan, Abdulghani and Intan Z., Mat Darus and Annisa, Jamali (2022) Intelligent Model for Endpoint Accelerations of Two link Flexible Manipulator Using a Deep Learning Neural Network. In: 2022 IEEE 8th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA), 27-28 Aug. 2022, Hatten Hotel, Melaka. |
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T Technology (General) |
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T Technology (General) Zidan, Abdulghani Intan Z., Mat Darus Annisa, Jamali Intelligent Model for Endpoint Accelerations of Two link Flexible Manipulator Using a Deep Learning Neural Network |
| description |
This article investigates a two-link flexible manipulator (TLFM) that can be modelled utilizing a deep learning neural network. The system was classified under a multiple-input multiple-output (MIMO) system. In the modelling stage of this study, the TLFM dynamic models were divided into single-input single-output (SISO) models. Since coupling impact was assumed to be minimised, the characterizations of TLFM were defined independently in each model. Two discrete SISO models of a flexible two link manipulator were developed using the torque input and the endpoint accelerations of each link. The input-output data pairs were collected from experimental work and utilised to establish the system model. The Long Short-Term Memory (LSTM) algorithm optimised using Particle Swarm Optimization (PSO) was selected as the model structure due to the system's high degree of nonlinearity. The identification of the TLFM system utilizing LSTM optimised by PSO was successful, according to the high-performance result of PSO. Using LSTM-PSO, it is demonstrated that both link 1 and 2 models are accurately identified and that their performance in terms of MSE for links endpoint acceleration 1 and 2 is within a 95% confidence interval. |
| format |
Proceeding |
| author |
Zidan, Abdulghani Intan Z., Mat Darus Annisa, Jamali |
| author_facet |
Zidan, Abdulghani Intan Z., Mat Darus Annisa, Jamali |
| author_sort |
Zidan, Abdulghani |
| title |
Intelligent Model for Endpoint Accelerations of Two link Flexible Manipulator Using a Deep Learning Neural Network |
| title_short |
Intelligent Model for Endpoint Accelerations of Two link Flexible Manipulator Using a Deep Learning Neural Network |
| title_full |
Intelligent Model for Endpoint Accelerations of Two link Flexible Manipulator Using a Deep Learning Neural Network |
| title_fullStr |
Intelligent Model for Endpoint Accelerations of Two link Flexible Manipulator Using a Deep Learning Neural Network |
| title_full_unstemmed |
Intelligent Model for Endpoint Accelerations of Two link Flexible Manipulator Using a Deep Learning Neural Network |
| title_sort |
intelligent model for endpoint accelerations of two link flexible manipulator using a deep learning neural network |
| publishDate |
2022 |
| url |
http://ir.unimas.my/id/eprint/40300/1/Intelligent%20Model.pdf http://ir.unimas.my/id/eprint/40300/ |
| _version_ |
1748706498628812800 |
| score |
13.251813 |