ANN-Based DTC for Three level VSI Powered Induction Motor

This paper presents an artificial neural network (ANN) based direct torque control (DTC) drive for three-level VSI. Traditional look-up table (LUT)-based DTC algorithms have high output torque ripple and flux ripple. Additionally, CDTC is difficult to practically implement in multi-phase or multi-level systems due to exponential increases in memory requirements. The proposed ANN-based approach offers better generalization, reduced memory usage, and lower computational complexity. The presented ANN-based DTC eliminates hysteresis controllers, leading to improved control of torque and flux and better transient and steady-state response. The proposed ANN-based DTC is verified through simulations and experimental tests. Comparative results are presented.