Simulation of AI-Based PID Controllers on DC Machines Using the MATLAB Application

Abstract

The Proportional-Integral-Derivative (PID) controller is a widely used industrial feedback control algorithm that consists of proportional, integral, and derivative components. This PID control can measure process variables and calculate errors to generate accurate control signals. PID controllers are often used for DC motor speed control applications based on desired parameters. By applying artificial intelligence, PID controller performance can be improved by determining optimal values, automatically adjusting parameters, and responding quickly and accurately to changes in process variables. This article discusses the design of a DC motor PID controller for CNC machines using the MATLAB 2017a application. In this research, a numerical approach is employed using the Action Research (AR) method to enhance practitioners' methods/ways of understanding material learned in higher education. Implementing a DC motor controller with a closed loop PID controller block can reduce the rise time value in the design transfer function. The lowest settling time and the overshoot in the PID control can result in the lowest rise time value of 136,893 ms. These findings can serve as a reference for determining the appropriate tuning method to adjust the values of proportional gain, integral gain, and derivative gain in the PID control system, thereby enhancing the production effectiveness of CNC machines.