DC (Direct Current) motors are widely used as controllers in the industrial and robotics fields. In the rotation of the DC motor, there is still an unstable rotational speed so that a controller is needed to be able to stabilize the speed at the rotation of the DC motor. The control used in this study used the PID (Proportional Integral Derivative) control method. The PID control system works by processing calculations based on control variables Kp, Ki, and Kd to achieve conditions according to the expected setpoints. To achieve the expected conditions, the trial and error method is used. PID control in this study was implemented on a DC motor with a brushed type using an Arduino Mega microcontroller. The speed of the DC motor is read by the encoder sensor and entered in the PID equation. The output of the PID value will produce data in the form of PWM (Pulse Width Modulation) which will be the input of the L298N driver via Arduino Mega. The DC motor will produce a rotational speed in the form of RPM (Revolution Per Minute) data up to the specified set point. The implementation of PID was produced by giving parameter values to Kp, Ki, and Kd. The best PID parameter usage in this study was in the form of Kp = 0.6; Ki=0.3; and Kd=0.01. The application of the PID parameter obtains a stable system response curve at a predetermined set point. The resulting Kp, Ki, and Kd parameter data is used as graph data in MATLAB software.
The power factor is a value obtained by comparing the actual power value and apparent power in an electric circuit. Because it is related to the quality of the distributed power, this power factor needs to be monitored. Devices with inductive loads generally cause power factor distortion, causing losses. Power factor monitoring is carried out periodically to ensure the efficiency of electricity distribution to the building. Power factor monitoring is usually done on the control panel of a building by measuring the voltage and current flowing. Manual monitoring could be more ineffective in terms of time and effort and has the potential for recording errors. This study proposes a power factor monitoring system on the control panel to facilitate recording. The system created is integrated with IoT technology so that it can monitor and record automatically anywhere and anytime. The developed system has an error percentage of 1.53% for the voltage sensor and 5.02% for the current sensor.
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