A High-Performance Sensorless DTC Strategy Based on MRAS for Induction Motors: Experimental Validation

Direct Torque Control (DTC) is one of the most widely adopted techniques in industrial applications due to its numerous advantages. While it effectively reduces torque ripple, its performance is further enhanced through the use of hysteresis-based models, PID speed controllers, and switching tables that generate variable frequencies. However, the operation of induction motors at low speeds—particularly the variations in stator resistance—significantly affects their performance. To address these challenges and optimize motor behavior, this study proposes an improved control approach. The control strategy has been enhanced through a sensorless method based on the Model Reference Adaptive System (MRAS) algorithm. This allows real-time estimation of speed, torque, and flux, eliminating the need for costly physical sensors. The MRAS algorithm not only reduces system complexity and cost but also adapts dynamically to changes in load and voltage, thereby improving overall reliability and energy efficiency. Moreover, it helps minimize component wear, thus extending the operational lifespan of the motor. The proposed MRAS-based sensorless DTC technique has been simulated using MATLAB/Simulink and implemented using DSpace DS1104, demonstrating significant improvements in motor performance and control system behavior.