AI-BASED FIELD-ORIENTED CONTROL FOR INDUCTION MOTORS

Elmehdi Benmalek

elmehdi.benmalek@um5s.net.ma
Mohammed V University of Rabat (Morocco)
https://orcid.org/0000-0003-1078-1421

Marouane Rayyam


Mohammed V University of Rabat (Morocco)

Ayoub Gege


Mohammed V University in Rabat (Morocco)

Omar Ennasiri


Mohammed V University in Rabat (Morocco)

Adil Ezzaidi


Mohammed V University in Rabat (Morocco)

Abstract

The current article deals with the implementation of Reinforcement Learning based Field Oriented Control (FOC) for the induction motors (IM). It is pertinent to mention that although conventional controllers like PID are widely used in FOC induction, they are model-based and face problems such as parameter adjustment. PID controllers need to be tuned because of the approximations of the model, variations of the parameters during operation, and the external disturbances that are uncertain and unpredictable. RL is a machine learning approach that is model-free which can adapt to the variations and disturbances. Therefore, these controllers can be an excellent alternative to the conventional controllers. In this study, an RL-based controller was used to control the speed of the induction motor using the FOC and space vector modulation (SVM). Computational simulations were done using the MATLAB/SIMULINK to test the controllers’ performance under different operating conditions. This study highlights the effectiveness of RL in optimizing IM control, offering potential benefits in various industrial and automation applications.


Keywords:

induction motor, field-oriented control, NPC inverter, reinforcement learning, TD3 agent

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Published
2024-12-21

Cited by

Benmalek, E., Rayyam, M., Gege, A., Ennasiri, O., & Ezzaidi, A. (2024). AI-BASED FIELD-ORIENTED CONTROL FOR INDUCTION MOTORS. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 14(4), 75–81. https://doi.org/10.35784/iapgos.6253

Authors

Elmehdi Benmalek 
elmehdi.benmalek@um5s.net.ma
Mohammed V University of Rabat Morocco
https://orcid.org/0000-0003-1078-1421

Authors

Marouane Rayyam 

Mohammed V University of Rabat Morocco

Authors

Ayoub Gege 

Mohammed V University in Rabat Morocco

Authors

Omar Ennasiri 

Mohammed V University in Rabat Morocco

Authors

Adil Ezzaidi 

Mohammed V University in Rabat Morocco

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