Development and Comparison of Controllers Based On ANFIS for Speed Control of a DC Motor

DC motors are widely used in industrial applications, robotic manipulators appliances due to their high reliability, flexibility and low cost. In this case, it is necessary to effectively control the speed of such a motor to increase its performance. Thus, the development of a controller that provides effective control of the speed of a DC motor is an urgent task. Currently, an adaptive neuro-fuzzy inference system (ANFIS) is designed to implement a controller that can increase the efficiency of controlling the speed of a DC motor. Because, this system will do more to reduce the rise time, the settling time and the overshoot of the specification of the transient regime of DC motor when compared with other non-adaptive systems.This article discusses the development of a controller based on ANFIS for the effective control of the speed of DC motor with load. The mathematical model of the developed controller in the environment of Matlab-Simulink is implemented. The comparison between the developed controller and other well-known controllers: proportional-integral-differential controller and fuzzy logic controller, is carried out according to the following characteristics: rise time, settling time and overshoot. In the work, the results of comparison by their speed are confirmed in an oscilloscope obtained from Matlab-Simulink. The results obtained in the work show that the developed ANFIS controller reduces the rise time compared to FL by 50%, the settling time compared to PID by 65% and FL by 45%, and the overshoot time by compared with PID by 13%.