Implementation of ANFIS Controller for DC motor on an Arduino Due Board

Abstract

In the industrial and robotic fields, the DC motor is the main device that provides high reliability and flexibility in the development of control algorithms. Therefore, it ensures effective control of the DC motor speed is an urgent task. This article represents DC motor speed control based on neural and adaptive fuzzy inference system (ANFIS) controller design for efficient, that can adapt to changes in the state of an object and input disturbances. Using neural networks controller do not require building a rule base and can operate in conditions of parametric uncertainty of the control object. Hybrid control systems that combine these principles can largely meet modern requirements for designed dynamic systems, as well as increase the reliability and flexibility of control. The mathematical model of the developed controller is simulated in the Matlab/Simulink and implemented on the Arduino Due board.