Comparative Performance Study of Different Controllers for Speed Regulation of DC Motor

Abstract

Due to extensive research into DC motor speed regulation, many techniques have been created. The most popular compensating controller in nonlinear systems is the Proportional Integral Derivative (PID) controller. The wide range of control systems to which PID may be applied makes it valuable. PID parameter adjustment is essential since these parameters significantly impact the control system's stability and effectiveness. The efficacy of PID, Fractional Order Proportional Integral Derivative (FOPID) and Neural Network Controllers (NNC) for controlling the speed of a DC motor is presented in this paper. However, in addition to the most famous traditional controller tuning methods like the Ziegler-Nichols and Cohen-Coon procedures, a Neural Network Tuner is created to optimize the processes by reducing the error between a process variable and its set point. The performance of three distinct controllers and tuning techniques have been examined using time response characteristics. To investigate the performance of DC motor with various controllers, a MATLAB/SIMULINK model is created. © 2022 IEEE.