Implementing PID-Kalman Algorithm to Reduce Noise in DC Motor Rotational Speed Control - Kurniasari, Indah Dwi; Ma'arif, Alfian (International Journal of Robotics and Control Systems, 2024)
This research attempts to combine Proportional Integral Derivative (PID) control and Kalman filter as a noise filter for encoder sensor readings and reference tracking accelerator of JGA25-370 DC motor. Through experiments, the applied PID controller demonstrated its ability to maintain the stability of DC motor rotation under different load conditions. The control signal generated by the motor driver had different voltage outputs: 7.8V for PWM 125, 8.4V for PWM 150, 8.8V for PWM 175, 9.1V for PWM 200, 9.4V for PWM 225, and 9.6V for PWM 250, with an encoder constant multiplier of 1.71. In particular, the Kalman filter, whose parameter values of R = 0.1 and Q = 0.01, effectively reduced the noise of the JGA25-370 DC motor encoder sensor readings. When operating independently, the PID controller successfully optimized the motor control using Kp = 1, Ki = 0.5, and Kd = 0.01. However, superior results were achieved by integrating the Kalman filter (R = 0.1, Q = 0.01) with the PID controller (Kp = 1, Ki = 0.4, Kd = 0.1), with successful reference tracking within a rise time value of 1.037 seconds, a completion time of 2.093 seconds, and a surpassing of 1.073%. These findings formed an efficient methodology for reducing encoder sensor reading results and speeding up the DC motor in achieving reference values using a combined PID-Kalman approach.