Hariyadi, M. Amin ORCID: https://orcid.org/0000-0001-9327-7604, Fadila, Juniardi Nur ORCID: https://orcid.org/0000-0002-5965-9243 and Sifaulloh, Hafizzudin (2023) 433Mhz based robot using Proportional Integral Derivative (PID) for precise facing direction. JOIV : International Journal on Informatics Visualization, 7 (3). pp. 991-999. ISSN 2549-9610 (print) | 2549-9904 (online)
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Abstract
This research endeavor aims to evaluate the effectiveness of the robot's direction control system by employing PID (Proportional Integral Derivative) output and utilizing wireless communication LoRa E32 433MHz. The experimental robot used in this study was a tank model robot equipped with 4 channels of control. LoRa was implemented in the robot control system, in conjunction with an Android control application, through serial data communication. The LoRa E32 module system was selected based on its established reliability in long-range communication applications. However, encountered challenges included the sluggishness of data transmission when using LoRa for transferring control data and the decreased performance of the robot under Non-Line of Sight conditions. To overcome these challenges, the PID method was employed to generate control data for the robot, thereby minimizing the error associated with controlling its movements. The PID system utilized feedback from a compass sensor (HMC5883L) to evaluate the setpoint data transmitted by the user, employing Kp, Ki, and Kd in calculations to enable smooth movements toward the setpoint. The findings of this study regarding the direct control of the robot using wireless LoRa E32 communication demonstrated an error range of 0.6% to 13.34%. A trial-and-error approach for control variables determined the optimal values for Kp, Ki, and Kd as 10, 0.1, and 1.5, respectively. Future investigations can integrate additional methodologies to precisely and accurately determine the PID constants (Kp, Ki, and Kd) mathematically.
Item Type: | Journal Article |
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Keywords: | control system; LoRa E32 433MHz; PID |
Subjects: | 08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080199 Artificial Intelligence and Image Processing not elsewhere classified 09 ENGINEERING > 0906 Electrical and Electronic Engineering > 090602 Control Systems, Robotics and Automation 09 ENGINEERING > 0913 Mechanical Engineering > 091302 Automation and Control Engineering |
Divisions: | Faculty of Technology > Department of Informatics Engineering |
Depositing User: | M.T. Juniardi Nur Fadila |
Date Deposited: | 20 Sep 2023 08:13 |
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