Speed control of induction motor using three fuzzy logic-based controllers

Abstract

This work portrays the methods for controlling an induction motor using three different types of fuzzy controllers: single-stage fuzzy controller; fuzzy-PID controller and adaptive- fuzzy-PID controller. The comparative performance of these three techniques has been presented and analyzed in this work. The proposed scheme uses indirect field oriented control and is simulated using MATLAB. The IFOC accepts two inputs: the reference torque from the speed controller and the measured current feedback. Using the Clark and Park transformations, the current is transformed from the three phase to the rotating reference frame. The new reference currents are then measured before being transformed back to the three phase using inverse Park and Clark. The new reference current will be fed to the hysteresis current controller for current tracking then to the three-phase inverter. Finally, the inverter is connected to the squirrel cage induction motor. The first speed controller consists of a simple single-stage fuzzy controller. This fuzzy controller regulates the output torque depending on the error and error ratio ranges, which are chosen according to the if-then rules. The second controller demonstrates the speed control using a fuzzy-PID control. A PID controller is connected to the fuzzy controller. The gain parameters of the PID are fixed. The third controller displays the Adaptive-fuzzy PID controller. It is also called multiple-stage controller since three fuzzy blocks are used. Each controller is used to adjust the gain values of the PID, depending on the changes in the error and error ration. The ranges of the membership functions are determined using error-and-trial method. Then the PID uses these gain values, alongside the error value to calculate the torque value.