Abstract
This paper introduces the stator flux vector-oriented control method for the three-phase asynchronous motor using internal model. In which, the three-layers feed-forward neural network with on-line learning algorithm is applied to design the reverse model for the independent torque and flux controllers, while the forward model is trained to identify the current in the d-q coordinate system of the motor. Finally, a 3-level cascaded inverter system with common-mode voltage reduction algorithm is applied to increase the stability of the controller. The simulation and experiment process are carried out based on the Matlab/Simulink software for 1-hp, 150-rad/s squirrel cage rotor motor. The simulation and experimental results show that the tracking performance of rotor speed is guaranteed at the angular frequency varying from the lowest 3-rad/s up to highest 150-rad/s. In addition, the motor control system remains stable when the stator and rotor resistance values are increased by 2 times in the presence of unknown disturbances.
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Quan, N.V., Long, M.T. (2024). Flux-Oriented Control for Asynchronous Three-Phase Motors Using Internal Model. In: Todor, D., Kumar, S., Choi, SB., Nguyen-Xuan, H., Nguyen, Q.H., Trung Bui, T. (eds) Proceedings of the International Conference on Sustainable Energy Technologies. ICSET 2023. Green Energy and Technology. Springer, Singapore. https://doi.org/10.1007/978-981-97-1868-9_76
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DOI: https://doi.org/10.1007/978-981-97-1868-9_76
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