Real-Time Validation of Enhanced Permanent Magnet Synchronous Motor Drive Using Dense-Neural-Network-Based Control

High-performance current and speed control are required to obtain smooth output torque, current tracking, and speed tracking in permanent-magnet synchronous motor (PMSM) drives. The motor speed and stator current control rely on multiple nonlinear motor parameters, which play a crucial role in shapi...

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Veröffentlicht in:	IEEE access 2024, Vol.12, p.73323-73339
Hauptverfasser:	Fatemimoghadam, Armita, Varaha Iyer, Lakshmi, Kar, Narayan C.
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial intelligence Artificial neural networks Computational efficiency Computational modeling Controllers Dense neural network Directional control hardware-in-the-loop Hardware-in-the-loop simulation Mathematical models motor drive Neural networks Parameter uncertainty permanent magnet synchronous motor Permanent magnets Proportional integral Real time Real-time systems Robust control software-in-the-loop Speed control Synchronous motors Tracking control Training vector control Vehicle dynamics
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