Performance Analysis of DTC-IM Drive Using Various Control Algorithms

Direct Torque Control (DTC) is the dominant strategy used in three-phase induction motor control, thanks to its excellent and vibrant characteristics, consistent operation, fewer mathematical calculations, and rigidity in adjustable velocity drives. However, torque ripple is the main drawback of DTC, and it is challenging to reduce it. While DTC based conventional PID controller is utilized, it gets pretentious by lengthy settling time, maximum peak overshoot, and torque and speed curve oscillations. The current research aims to diminish the torque ripple and augment the DTC-enabled induction motor drive performance. Various control methods, such as Fuzzy Logic Control (FLC), Artificial Neural Network (ANN), and Adaptive Neuro-Fuzzy Inference System (ANFIS), were used in the chapter to enhance the DTC-enabled induction motor drive performance. These control methods were carefully verified and simulated under MATLAB/Simulink 2017. The effectiveness of the projected work was confirmed through simulation, which achieved promising results, thus establishing the supremacy of the proposed model.