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All Journal Indonesian Journal of Engineering and Science (IJES) Journal of Fuzzy Systems and Control (JFSC) Control Systems and Optimization Letters
Nguyen, Ngoc-Hung
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Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Materials Science & Nanotechnology Mechanical Engineering

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 1 
Design and Implementation of an IoT-Enabled Autonomous Fire-Fighting Robot Using Vision-Based Fire Detection Nguyen, Hoang-Thong; Nguyen, Quoc-Thuan; Tran, Phuoc-Dat; Nguyen, Quang-Khai; Le, Thi-Hong-Lam; Nguyen, Le-Minh-Kha; Nguyen, Van-Hiep; Nguyen, Thanh-Binh; Nguyen, Ngoc-Hung; Nguyen, Thi-Ngoc-Thao; Phung, Son-Thanh; Le, Hoang-Lam; Nguyen, Thanh-Toan; Nguyen, Hai-Thanh
Journal of Fuzzy Systems and Control Vol. 3 No. 3 (2025): Vol. 3 No. 3 (2025)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This paper presents the design and implementation of an IoT-enabled autonomous fire-fighting mobile robot for early hazard detection, remote monitoring, and emergency response. The proposed system integrates real-time deep learning–based fire detection using a YOLO model with fire and gas sensor–based monitoring for IoT-based alert transmission and SLAM-based environmental visualization to form a multifunctional robotic platform capable of performing a sequence of tasks from detection and warning to initial fire response. The robot is capable of autonomous movement with obstacle avoidance, while a 2D SLAM-based mapping module is employed to provide environmental visualization for monitoring and decision support. A mobile application enables remote supervision and control, and real-time alerts are delivered through an IoT platform to enhance situational awareness. Experimental results show that the proposed system achieves a fire detection and response success rate of approximately 70%, with reliable fire recognition and fast response time under indoor testing conditions. The developed robot demonstrates strong potential as a practical solution for improving safety and supporting early-stage fire response in residential and industrial environments.
EXPERIMENTAL ANFIS-FUZZY CONTROLLER FOR BALL AND BEAM SYSTEM Le, Tuan-Kiet; Nguyen, Le-Anh-Tuan; Le, Ngoc-Long; Nguyen, Van-Dong-Hai; Le, Thi-Hong-Lam; Le, Thi-Thanh-Hoang; Nguyen, Van-Hiep; Nguyen, Thanh-Binh; Phu, Thi-Ngoc-Hieu; Nguyen, Thi-Ngoc-Thao; Nguyen, Ngoc-Hung; Nguyen, Binh-Hau; Nguyen, Hai-Thanh
Indonesian Journal of Engineering and Science Vol. 7 No. 1 (2026): Table of Contents
Publisher : Asosiasi Peneliti Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51630/ijes.v7i1.206

Abstract

This paper presents the development of an Adaptive Neuro-Fuzzy Inference System (ANFIS) controller for a mid-pivot Ball and Beam system. The nonlinear dynamic model is derived using Euler–Lagrange formulation, followed by DC motor modeling to construct the full state-space system. An ANFIS controller is trained from PID-generated data to enhance adaptability under nonlinear conditions. Simulation and hardware experiments validate the controller’s performance. Results show that the proposed controller can stabilize the system with reasonable accuracy, although overshoot and oscillation remain. Directions for improving intelligent control and hardware design are discussed.
DEVELOPMENT AND IMPLEMENTATION OF THE MOTHER AND CHILD SHUTTLE SYSTEM FOR WAREHOUSE MANAGEMENT AND OPERATION Huynh, Anh-Tuan; Le, Quoc-Tuan; Lam, Xuan-Minh-Nhat; Nguyen, Thi-Ngoc-Thao; Le, Thi-Hong-Lam; Truong, Nhat-Bang; Vu, Bao-Huy; Nguyen, Kieu-Vinh; Tran, Huu-Nhan; Nguyen, Phong-Luu; Nguyen, Binh-Hau; Nguyen, Thanh-Binh; Nguyen, Van-Hiep; Nguyen, Ngoc-Hung
Indonesian Journal of Engineering and Science Vol. 7 No. 1 (2026): Table of Contents
Publisher : Asosiasi Peneliti Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51630/ijes.v7i1.215

Abstract

The increasing complexity of warehouse operations and the rapid growth of e-commerce demand advanced Automated Storage and Retrieval Systems (AS/RS) that are efficient, flexible, and reliable. This study presents the design and implementation of a Mother and Child Shuttle System integrated with a hybrid communication architecture and an intelligent control interface. The system is developed based on kinematic and dynamic analysis to optimize shuttle motion using an acceleration–constant velocity–deceleration profile, ensuring stable operation and accurate positioning. A block-based control architecture incorporating PLC, sensors, motor drivers, and wireless communication enables coordinated system operation. The hardware prototype, including the Mother Shuttle, Child Shuttle, and storage rack, is successfully constructed and validated under real conditions, demonstrating stable performance and effective component integration. In addition, a user-friendly interface is developed to support real-time monitoring, control, and alarm management, enhancing system reliability and operational safety. The proposed system provides a practical solution for improving efficiency and scalability in modern warehouse automation.
Trajectory Tracking Controller Design for a One-degree-of-Freedom Robotic Arm using Fuzzy Logic and Neural Controllers Nguyen, Quang-Thien; Nguyen, Anh-Huy; Le, Hoang-Linh; Nguyen, Hai-Thanh; Le, Thi-Hong-Lam; Nguyen, Ngoc-Hung; Nguyen, Van-Hiep; Nguyen, Thanh-Binh; Nguyen, Thi-Ngoc-Thao; Nguyen, Minh-Tam; Nguyen, Phong-Luu; Le, Hoang-Lam; Phung, Son-Thanh
Control Systems and Optimization Letters Vol 4, No 1 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v4i1.271

Abstract

The one-degree-of-freedom (1-DOF) robotic arm is a fundamental platform widely used in laboratories for teaching and evaluating position and trajectory control strategies. This paper presents the modeling, simulation, and experimental implementation of a 1-DOF robotic arm system using intelligent control approaches. A Fuzzy Logic Controller (FLC) and a neural network controller (NNC) based on a multi-layer perceptron (MLP) were designed and evaluated in MATLAB/Simulink and implemented in real time on an STM32F4 embedded hardware platform. Both controllers were tested under step and sinusoidal reference inputs, achieving tracking errors below 5°, settling times of approximately 0.1 s (within ±2%), and limited overshoot. Although the neural network successfully reproduced the general control behavior of the FLC, the fuzzy controller demonstrated slightly smoother responses and lower control effort under multi-level step conditions. A primary contribution of this work is the development and validation of a low-cost STM32F4G-based embedded platform for implementing and experimentally evaluating intelligent control algorithms, providing a practical and scalable solution for intelligent control research and laboratory education in universities.
Co-Authors Huynh, Anh-Tuan Lam, Xuan-Minh-Nhat Le, Hoang-Lam Le, Hoang-Linh Le, Ngoc-Long Le, Quoc-Tuan Le, Thi-Hong-Lam Le, Thi-Thanh-Hoang Le, Tuan-Kiet Nguyen, Anh-Huy Nguyen, Binh-Hau Nguyen, Hai-Thanh Nguyen, Hoang-Thong Nguyen, Kieu-Vinh Nguyen, Le-Anh-Tuan Nguyen, Le-Minh-Kha Nguyen, Minh-Tam Nguyen, Phong-Luu Nguyen, Quang-Khai Nguyen, Quang-Thien Nguyen, Quoc-Thuan Nguyen, Thanh-Binh Nguyen, Thanh-Toan Nguyen, Thi-Ngoc-Thao Nguyen, Van-Dong-Hai Nguyen, Van-Hiep Phu, Thi-Ngoc-Hieu Phung, Son-Thanh Tran, Huu-Nhan Tran, Phuoc-Dat Truong, Nhat-Bang Vu, Bao-Huy