High-Performance Inverse Artificial Neural Network Controller for Asynchronous Motor Control
Induction motor (IM) is considered one of the most important machines in industrial applications, which requires precise and effective control of its behavior in order to improve its performance. In this paper, three control strategies based on the development of inverse artificial neural networks...
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| Format: | Article |
| Language: | English |
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Universidade Federal de Viçosa (UFV)
2024-12-01
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| Series: | The Journal of Engineering and Exact Sciences |
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| Online Access: | https://periodicos.ufv.br/jcec/article/view/20857 |
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| author | Benyekhlef Kada Mourad Hebali Ibrahim Farouk Bouguenna Benaoumeur Ibari Menouer Bennaoum |
| author_facet | Benyekhlef Kada Mourad Hebali Ibrahim Farouk Bouguenna Benaoumeur Ibari Menouer Bennaoum |
| author_sort | Benyekhlef Kada |
| collection | DOAJ |
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Induction motor (IM) is considered one of the most important machines in industrial applications, which requires precise and effective control of its behavior in order to improve its performance. In this paper, three control strategies based on the development of inverse artificial neural networks (IANNs) were proposed in order to control the current (Ias), electromagnetic torque (Ce), and speed (Wr) of an asynchronous machine IM. These inverse artificial neural networks have been learned from conventional control system (PI controller and vector control) data using MATLAB software. Comparison between the responses of both the classical controller and the IANNs showed the ability and effectiveness of the latter in precisely controlling the three properties of the asynchronous motor, and it also achieved better dynamic motor behavior, speed without overtaking, and good load disturbance rejection, which proves the high performance of these developed IANNs.
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| format | Article |
| id | doaj-art-81216f75185142dc8a987ae3d74687bb |
| institution | Kabale University |
| issn | 2527-1075 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Universidade Federal de Viçosa (UFV) |
| record_format | Article |
| series | The Journal of Engineering and Exact Sciences |
| spelling | doaj-art-81216f75185142dc8a987ae3d74687bb2025-02-02T19:53:06ZengUniversidade Federal de Viçosa (UFV)The Journal of Engineering and Exact Sciences2527-10752024-12-0110910.18540/jcecvl10iss9pp20857High-Performance Inverse Artificial Neural Network Controller for Asynchronous Motor ControlBenyekhlef Kada0Mourad Hebali1Ibrahim Farouk Bouguenna 2Benaoumeur Ibari3Menouer Bennaoum4Department of Electrotechnical, University Mustapha Stambouli of Mascara. Mascara, Algeria. LIS2T Laboratory, University Mustapha Stambouli of Mascara. AlgeriaDepartment of Electrotechnical, University Mustapha Stambouli of Mascara. Mascara, Algeria. LIS2T Laboratory, University Mustapha Stambouli of Mascara. AlgeriaDepartment of Electrotechnical, University Mustapha Stambouli of Mascara. Mascara, Algeria. LIS2T Laboratory, University Mustapha Stambouli of Mascara. AlgeriaDepartment of Electrotechnical, University Mustapha Stambouli of Mascara. Mascara, Algeria. LIS2T Laboratory, University Mustapha Stambouli of Mascara. AlgeriaDepartment of Electrotechnical, University Mustapha Stambouli of Mascara. Mascara, Algeria. LIS2T Laboratory, University Mustapha Stambouli of Mascara. Algeria Induction motor (IM) is considered one of the most important machines in industrial applications, which requires precise and effective control of its behavior in order to improve its performance. In this paper, three control strategies based on the development of inverse artificial neural networks (IANNs) were proposed in order to control the current (Ias), electromagnetic torque (Ce), and speed (Wr) of an asynchronous machine IM. These inverse artificial neural networks have been learned from conventional control system (PI controller and vector control) data using MATLAB software. Comparison between the responses of both the classical controller and the IANNs showed the ability and effectiveness of the latter in precisely controlling the three properties of the asynchronous motor, and it also achieved better dynamic motor behavior, speed without overtaking, and good load disturbance rejection, which proves the high performance of these developed IANNs. https://periodicos.ufv.br/jcec/article/view/20857Induction Motor,PI-ControllerVector Control,Inverse ANNs |
| spellingShingle | Benyekhlef Kada Mourad Hebali Ibrahim Farouk Bouguenna Benaoumeur Ibari Menouer Bennaoum High-Performance Inverse Artificial Neural Network Controller for Asynchronous Motor Control The Journal of Engineering and Exact Sciences Induction Motor, PI-Controller Vector Control, Inverse ANNs |
| title | High-Performance Inverse Artificial Neural Network Controller for Asynchronous Motor Control |
| title_full | High-Performance Inverse Artificial Neural Network Controller for Asynchronous Motor Control |
| title_fullStr | High-Performance Inverse Artificial Neural Network Controller for Asynchronous Motor Control |
| title_full_unstemmed | High-Performance Inverse Artificial Neural Network Controller for Asynchronous Motor Control |
| title_short | High-Performance Inverse Artificial Neural Network Controller for Asynchronous Motor Control |
| title_sort | high performance inverse artificial neural network controller for asynchronous motor control |
| topic | Induction Motor, PI-Controller Vector Control, Inverse ANNs |
| url | https://periodicos.ufv.br/jcec/article/view/20857 |
| work_keys_str_mv | AT benyekhlefkada highperformanceinverseartificialneuralnetworkcontrollerforasynchronousmotorcontrol AT mouradhebali highperformanceinverseartificialneuralnetworkcontrollerforasynchronousmotorcontrol AT ibrahimfaroukbouguenna highperformanceinverseartificialneuralnetworkcontrollerforasynchronousmotorcontrol AT benaoumeuribari highperformanceinverseartificialneuralnetworkcontrollerforasynchronousmotorcontrol AT menouerbennaoum highperformanceinverseartificialneuralnetworkcontrollerforasynchronousmotorcontrol |