control. Due to a nonlinear structure of asynchronous motors, it is very difficult to control. ANFIS controllers as an adaptive and learning system are aimed at improving speed control performance to ensure better performance and accuracy in speed control of asynchronous motors. For ANFIS, Fuzzy Logic Control (FLC) and traditional PI type controllers, asynchronous motors are operated at different speeds and under load conditions. The performance of three controllers is examined in Matlab/Simulink environment and the simulated results are compared. The performance of the three controllers was analyzed based on the performance parameters such as rise time, overshoot, settling time, and steady state error. Step input is applied as the asynchronous motor reference speed value (t = 0-0.5 seconds for 700 rpm, t = 0.5-1 seconds for 1100 rpm, t = 1-2 seconds for 1350 rpm, t = 2-2.5 seconds for 1100 rpm, and t = 2.5-3 seconds for 700 rpm). By observing the performance parameters such as rise time and settling time, the proposed controller has reached the changing reference speed more rapidly compared to FLC and PI-type controller. According to the simulation results, the adaptive neuro-fuzzy controller provided a remarkable success compared to traditional PI and fuzzy logic controllers.
Performance Analysis of ANFIS, FLC and PI Controller for Asynchronous Motor Drive
2017-01-01
Article (Journal)
Electronic Resource
English
DDC: | 629 |
IMPLEMENTATION AND PERFORMANCE ANALYSIS OF BLDC MOTOR DRIVE BY PID, FUZZY AND ANFIS CONTROLLER
BASE | 2021
|IMPLEMENTATION AND PERFORMANCE ANALYSIS OF BLDC MOTOR DRIVE BY PID, FUZZY AND ANFIS CONTROLLER
BASE | 2017
|