Artificial Neural Network (ANN) based Proportional Integral Derivative (PID) for Arm Rehabilitation Device
The current work was developed under the title of Artificial Neural Network (ANN) Proportional Integral Derivative (PID) for the arm rehabilitation device and included building and designing the simulation model and simulation results for the arm rehabilitation device. A set of tests were proposed t...
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| Format: | Article |
| Language: | English |
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Faculty of Engineering, University of Kufa
2025-02-01
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| Series: | Mağallaẗ Al-kūfaẗ Al-handasiyyaẗ |
| Subjects: | |
| Online Access: | https://journal.uokufa.edu.iq/index.php/kje/article/view/15952 |
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| author | salam waley shneen Rajaa khalaf Gaber Rasha Saad Salih Suaad Makki Jiaad |
| author_facet | salam waley shneen Rajaa khalaf Gaber Rasha Saad Salih Suaad Makki Jiaad |
| author_sort | salam waley shneen |
| collection | DOAJ |
| description | The current work was developed under the title of Artificial Neural Network (ANN) Proportional Integral Derivative (PID) for the arm rehabilitation device and included building and designing the simulation model and simulation results for the arm rehabilitation device. A set of tests were proposed to include firstly testing a system that represents the state of the open arm rehabilitation device and secondly It represents the closed arm rehabilitation device, third represents the closed-loop arm rehabilitation device with PID control device, fourth represents the arm rehabilitation device using ANN, and finally the closed-loop arm rehabilitation device can be used with a comparison between PIDC and ANN. To conduct all the proposed test cases, a program can be used MATLAB, which can help simulate a device that represents an attempt to regain movement in the arm, which is called rehabilitation. It can be noted that the target group is some people who suffer from stroke. By representing the system in the proposed simulation model, its effectiveness can be verified. It is possible to conduct tests aimed at improving performance by working on developing the model by adopting the appropriate design for the characteristics that match the required operational behavior of the system with all conditions that suit different situations. The test cases demonstrated through the simulation results the possibility of identifying the system behavior for the proposed cases. The difference between the system behavior for all these cases was also identified. In addition to the possibility of improving the performance of the movement recovery device to rehabilitate the injured arm through the system’s performance in the presence of an expert neural network controller, it is better than the traditional controller.
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| format | Article |
| id | doaj-art-d1bfe724c106420bbc1804462ea40395 |
| institution | Kabale University |
| issn | 2071-5528 2523-0018 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Faculty of Engineering, University of Kufa |
| record_format | Article |
| series | Mağallaẗ Al-kūfaẗ Al-handasiyyaẗ |
| spelling | doaj-art-d1bfe724c106420bbc1804462ea403952025-02-06T06:30:42ZengFaculty of Engineering, University of KufaMağallaẗ Al-kūfaẗ Al-handasiyyaẗ2071-55282523-00182025-02-0116018010310.30572/2018/KJE/160106Artificial Neural Network (ANN) based Proportional Integral Derivative (PID) for Arm Rehabilitation Devicesalam waley shneen0https://orcid.org/0000-0003-3718-6104Rajaa khalaf Gaber1Rasha Saad Salih2Suaad Makki Jiaad3Energy and Renewable Energies Technology Center, University of Technology – IraqElectro-mechanical Engineering Department, University of Technology – IraqElectro-mechanical Engineering Department, University of Technology – IraqElectro-mechanical Engineering Department, University of Technology – IraqThe current work was developed under the title of Artificial Neural Network (ANN) Proportional Integral Derivative (PID) for the arm rehabilitation device and included building and designing the simulation model and simulation results for the arm rehabilitation device. A set of tests were proposed to include firstly testing a system that represents the state of the open arm rehabilitation device and secondly It represents the closed arm rehabilitation device, third represents the closed-loop arm rehabilitation device with PID control device, fourth represents the arm rehabilitation device using ANN, and finally the closed-loop arm rehabilitation device can be used with a comparison between PIDC and ANN. To conduct all the proposed test cases, a program can be used MATLAB, which can help simulate a device that represents an attempt to regain movement in the arm, which is called rehabilitation. It can be noted that the target group is some people who suffer from stroke. By representing the system in the proposed simulation model, its effectiveness can be verified. It is possible to conduct tests aimed at improving performance by working on developing the model by adopting the appropriate design for the characteristics that match the required operational behavior of the system with all conditions that suit different situations. The test cases demonstrated through the simulation results the possibility of identifying the system behavior for the proposed cases. The difference between the system behavior for all these cases was also identified. In addition to the possibility of improving the performance of the movement recovery device to rehabilitate the injured arm through the system’s performance in the presence of an expert neural network controller, it is better than the traditional controller. https://journal.uokufa.edu.iq/index.php/kje/article/view/15952arm rehabilitation deviceopen loopclose loopannpidc |
| spellingShingle | salam waley shneen Rajaa khalaf Gaber Rasha Saad Salih Suaad Makki Jiaad Artificial Neural Network (ANN) based Proportional Integral Derivative (PID) for Arm Rehabilitation Device Mağallaẗ Al-kūfaẗ Al-handasiyyaẗ arm rehabilitation device open loop close loop ann pidc |
| title | Artificial Neural Network (ANN) based Proportional Integral Derivative (PID) for Arm Rehabilitation Device |
| title_full | Artificial Neural Network (ANN) based Proportional Integral Derivative (PID) for Arm Rehabilitation Device |
| title_fullStr | Artificial Neural Network (ANN) based Proportional Integral Derivative (PID) for Arm Rehabilitation Device |
| title_full_unstemmed | Artificial Neural Network (ANN) based Proportional Integral Derivative (PID) for Arm Rehabilitation Device |
| title_short | Artificial Neural Network (ANN) based Proportional Integral Derivative (PID) for Arm Rehabilitation Device |
| title_sort | artificial neural network ann based proportional integral derivative pid for arm rehabilitation device |
| topic | arm rehabilitation device open loop close loop ann pidc |
| url | https://journal.uokufa.edu.iq/index.php/kje/article/view/15952 |
| work_keys_str_mv | AT salamwaleyshneen artificialneuralnetworkannbasedproportionalintegralderivativepidforarmrehabilitationdevice AT rajaakhalafgaber artificialneuralnetworkannbasedproportionalintegralderivativepidforarmrehabilitationdevice AT rashasaadsalih artificialneuralnetworkannbasedproportionalintegralderivativepidforarmrehabilitationdevice AT suaadmakkijiaad artificialneuralnetworkannbasedproportionalintegralderivativepidforarmrehabilitationdevice |