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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics
Sukontanakarn, Viroch
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Computer Science & IT Electrical & Electronics Engineering Engineering

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TMS320F28379D microcontroller for speed control of permanent magnet direct current motor Chalardsakul, Tanawat; Piliyasilpa, Chotnarin; Sukontanakarn, Viroch
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i3.pp2816-2828

Abstract

This paper aims to study the behavior of the proportional integral derivative (PID) and the fuzzy-based tuning PI-D controller for speed control of a permanent magnet direct current (PMDC) motor. The proposed method used a fuzzy-based tuning PI-D controller with a MATLAB/Simulink program to design and real-time implement a TMS320F28379D microcontroller for speed control of a PMDC motor. The performance of the study designed fuzzy-based tuning PI-D and PID controllers is compared and investigated. The fuzzy logic controller applies the controlling voltage based on motor speed errors. Finally, the result shows the fuzzy-based tuning PI-D controller approach has a minimum overshoot, and minimum transient and steady state parameters compared to the PID controller to control the speed of the motor. The PID controllers have poorer performance due to the non-linear features of the PMDC motor.
Design of internet of things-integrated programmable logic controller for demonstrating automated sorting systems Intawong, Narit; Saengchandr, Banjerd; Inkamchuer, Manit; Thongprom, Morakot; Sukontanakarn, Viroch
Bulletin of Electrical Engineering and Informatics Vol 14, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i4.9426

Abstract

This project presents an automated workpiece sorting demonstration system controlled by a programmable logic controller (PLC) and a touch screen interface. The system integrates an internet of things (IoT) gateway that communicates with the PLC via Modbus remote terminal unit (RTU) over RS-485, allowing the transfer of digital data. This data is processed using JavaScript within the Node-RED platform to manage machine operations and display the operational status. The system supports both manual control and IoT-based management, enabling the sorting of cylindrical workpieces to designated areas. Metal and non-metal detection is achieved using capacitive and inductive sensors, respectively, which inform a stepper motor to manipulate the workpieces via a gripper pneumatic to the specified locations. Test results indicate a high detection capability of the sensors: the capacitive sensors achieved a 95% detection rate over 100 trials, while the inductive sensors recorded a 97% detection rate. Furthermore, the precision of placing workpieces at the target locations was 92% across 100 attempts. This system showcases an effective combination of automation and IoT technologies, improving efficiency in workpiece sorting processes.
Co-Authors Chalardsakul, Tanawat Inkamchuer, Manit Intawong, Narit Piliyasilpa, Chotnarin Saengchandr, Banjerd Thongprom, Morakot