Implementation of data driven control system of DC motor by using system identification process

Abstract

This paper presents data driven control system of DC motor by using system identification process. In this paper we use component base modeling similar to real DC motor by using simscape electronic systems for obtaining the input voltage and output speed of DC motor, the system identification toolbox and the nonlinear autoregressive with exogenous input (NARX) neural network for identification and obtaining the model of an object. The object model and training the neural network for data driven control system are developed by using MATLAB/SIMULINK platform. So, simulation results of this paper present the advantage of the suggested control method and the acceptable accuracy with respect to dynamic characteristics of the system.