Design of DTC Controller for Three-phase Induction Motor

Abstract

Induction motors (IM) are among the most prevalently electric motors that are extensively utilized in industry. The control of these types of motors must be accurate and responsive to changes in torque and magnetic flux. Many induction motor control strategies have been introduced in recent years, direct torque control (DTC) is one of the most advanced types of induction motor control. This paper aims to design and improve the conventional torque control of induction motor using artificial neural networks. The main drawbacks of conventional torque control are high torque and flux ripples, variable switching behavior and control problems at low speeds. Artificial Neural Network (ANN) techniques are used to control the speed of induction motor and compared with the speed controller using proportional-integral-differential governor. The proposed models are implemented in MATLAB/SIMULINK platform which consists of subsystem models including induction motor, three-phase rectifier, three-phase inverter, along with the main controllers. The simulation results show a significant reduction in torque and flux ripples and improvements in the dynamic speed response.