Speed control of induction motor using adaptive fuzzy_PID controller based on direct torque control

Abstract

This study investigates the simulation of advanced control strategies for three-phase induction motors, focusing on Direct Torque Control (DTC) integrated by Fuzzy Logic Controllers (FLC) and Adaptive Fuzzy PID Controllers (AFPID). Induction motors, known for their durability, simplicity, and cost-effectiveness, are widely used in industrial applications. Precise control of motor speed and torque is critical for optimizing performance efficiency. The work begins with an exploration of the construction and operating principles of induction motors, emphasizing their electromagnetic induction mechanism. Various control techniques, including DTC, are examined for their ability to enhance motor performance. DTC is highlighted for its superior dynamic response and transient performance, achieved by directly controlling motor torque and flux without the need for complex mathematical models. The integration of FLC and AFPID with DTC is explored through theoretical analysis and simulation studies. FLCs offer robust control in uncertain and nonlinear systems, modeling human reasoning to adapt the changes conditions and disturbances. The combination of these advanced controllers with DTC is shown to improve motor control, providing fast and precise adjustments in industrial applications. The findings demonstrate the potential of these advanced control strategies to revolutionize motor control systems, leading to significant improvements in efficiency and reliability.