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All Journal Journal of Fuzzy Systems and Control (JFSC) Control Systems and Optimization Letters
Thi-Ngoc-Thao Nguyen
Ho Chi Minh City University of Technology and Engineering (HCM-UTE)
Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Intelligent Control for 2D-Crane System Trung-Son Huynh; Dang-Khoa Dinh; Trong-Bang Tran; Huu-Loc Dang; Dinh-Nguyen-Phuc Le; Hung-Thinh Bui; Hoang-Lam Le; Thanh-Binh Nguyen; Van-Hiep Nguyen; Le-Nhat-Minh Nguyen; Thien-Quoc Dang; Ngoc-Hung Nguyen; Thi-Ngoc-Thao Nguyen; Huynh-Duc Pham; Xuan-Tien Nguyen; Van-Dong-Hai Nguyen
Journal of Fuzzy Systems and Control Vol. 4 No. 1 (2026): Vol. 4 No. 1 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v4i1.350

Abstract

This paper presents an Intelligent Learning-based Control approach for a 2D Crane System, aiming to evaluate the learning capability of various intelligent techniques based on a baseline Fuzzy Logic Controller (FLC). The initial fuzzy controller is designed for position and sway control, while Genetic Algorithm (GA), Artificial Neural Network (ANN), and Adaptive Neuro-Fuzzy Inference System (ANFIS) are employed in simulation to retrain and enhance its performance. Comparative results show that intelligent learning methods can significantly improve system response, reduce overshoot, and increase robustness compared to the original fuzzy controller. Moreover, an experimental setup using the baseline FLC is implemented to verify the practical effectiveness of the fuzzy control approach on a real 2D crane system. The findings highlight the potential of intelligent learning techniques for future real-time implementation.
Development of an Automated PCB Inspection, Error Statistics, and Classification System Truong-Nguyen Phan; Thi-Ngoc-Tram Tran; Thanh-Viet Ho; Binh-Hau Nguyen; Minh-Tri Hoang; Hai-Nam Tran; Nhat-Nam Nguyen; Nguyen-Cong-Anh Tran; Le-Huu-Tri Do; Thi-Ngoc-Thao Nguyen; Nam-Long Tran; Duong-Thuan Nguyen; Van-Huy Le; Van-Tuan Nguyen; Huynh-Anh-Tuan Pham
Journal of Fuzzy Systems and Control Vol. 4 No. 1 (2026): Vol. 4 No. 1 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v4i1.353

Abstract

In the electronics manufacturing industry, Printed Circuit Boards are critical to electronic devices, and their quality directly affects product performance and reliability. Common assembly defects, such as missing components, misalignment, or wrong parts, must be detected promptly to reduce waste and maintain reputation. In Vietnam, PCB inspection is largely manual, limiting speed, accuracy, and consistency. The system integrates a YOLOv5-based machine vision module for detecting missing and misaligned components, a Siemens S7-1200 PLC for controlling an XY gantry and conveyor system, and a web interface for real-time monitoring. The primary contributions include: a fully integrated cyber-physical prototype suitable for educational and small-scale industrial use; a novel method for component misalignment detection using fiducial-based relative positioning; and seamless communication between vision, control, and HMI modules. Experimental results on two common PCB types, L298N and ULN2003, demonstrate a classification and error detection accuracy of up to 93%. The system achieves a throughput suitable for laboratory and small-batch production, with a positioning accuracy of ±0.5 mm. The system aims to achieve high accuracy, fast processing, and practical applicability in production lines.
A Study of a Laser Engraving System Based on a Cartesian Robot with Image Processing Thai-Duong Hoang; Manh-Dung Nguyen; Chi-Phat Pham; Thi-Ngoc-Thao Nguyen; Tan-Phat Nguyen; Anh-Son Tran; Quang-Thuan Le; Phuoc-Thinh Dang; Thai-Hiep Nguyen; Quang-Tung Trinh; Hoai-Bao-Nhan Nguyen; Huu-Nhan Nguyen; Thanh-Binh Nguyen
Journal of Fuzzy Systems and Control Vol. 4 No. 1 (2026): Vol. 4 No. 1 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v4i1.361

Abstract

Traditional CNC laser engraving systems often face limitations in flexibility, requiring manual alignment and pre-defined G-code files. This paper proposes an advanced automated laser engraving system based on a 3-axis Cartesian robot that bridges the gap between industrial control reliability and modern computer vision. The core novelty of this research lies in the seamless integration of a Mitsubishi Q03UDE Programmable Logic Controller (PLC) with a Python-based image processing framework. By utilizing the OpenCV library for real-time edge detection and trajectory generation, the system can autonomously identify object positions and convert complex patterns into precise motion commands. Communication is established via the MC Protocol over Ethernet, ensuring high-speed data synchronization between the vision system and the servo-driven hardware. Experimental results demonstrate that the proposed system achieves high precision in engraving, significantly reduces setup time by eliminating manual calibration, and maintains the robust stability required for industrial environments. This approach provides a scalable solution for intelligent manufacturing and personalized production.
An Enhanced PID-Based Motion Control Framework for Autonomous Line-Following Robot Nguyen-Thanh-Loc Tran; Viet-Tien-Dung Bui; Hong-Nho Bui; Hoang-Nguyen Nguyen; Thi-Ngoc-Thao Nguyen; Thanh-Sang Nguyen; Hung-Ky Nguyen; Huynh-Duc-Anh Nguyen; Thanh-Binh Phan; Hoang-Sang Luong; Le-Minh-Tan Nguyen; Vo-Minh-Khoa Tran; Tien-Dat Nguyen; Huynh-Khanh-Nam Pham; Duc-Dat Nguyen; The-Nhan Nguyen
Journal of Fuzzy Systems and Control Vol. 4 No. 1 (2026): Vol. 4 No. 1 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v4i1.368

Abstract

PID controller is widely used in automatic control systems because it is simple, reliable, and easy to apply. It is especially suitable for mobile robots, such as line-following robots. The main contribution of this work is an experimental method to tune PID parameters. Instead of using complex algorithms, the parameters are adjusted and tested directly on a real robot. This makes the method easier to apply, especially for low-cost and educational systems. Experiments were conducted to evaluate how PID parameters (Kp, Ki, and Kd) affect the robot’s performance. The robot was tested on different paths, including straight lines, curves, and 90-degree turns. The results show that the optimal parameters are Kp = 65, Ki = 0.1, and Kd = 13. With these values, the robot moves smoothly, responds quickly, and follows the path accurately.
Driver Drowsiness Detection and Warning System Using Computer Vision and Neural Networks on Embedded Platforms Chi-Phat Pham; Quang Tran; Binh-Hau Nguyen; Van-Dong-Hai Nguyen; Thi-Hong-Lam Le; Ngoc-Hung Nguyen; Van-Hiep Nguyen; Thanh-Binh Nguyen; Thi-Ngoc-Thao Nguyen; Hoang-Lam Le
Journal of Fuzzy Systems and Control Vol. 4 No. 2 (2026): Vol. 4 No. 2 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v4i2.372

Abstract

Driver drowsiness is one of the leading causes of traffic accidents worldwide. Traditional monitoring approaches, such as vehicle-based parameter analysis or physiological signal measurement, often require intrusive sensors or deep access to vehicle systems. To overcome these limitations, this paper proposes a real-time driver drowsiness detection and warning system using computer vision combined with a neural network classifier on an embedded platform. Facial landmarks are extracted using the dlib 68-point model, and the Eye Aspect Ratio (EAR) is computed to evaluate eye-closure behavior. A deep neural classifier is trained on eye-state and temporal EAR sequences collected from 25 subjects to classify normal and drowsy conditions. The system is deployed on a Raspberry Pi 3 B+ embedded platform, integrated with an Arduino-based alarm module to deliver audio–visual alerts when drowsiness is detected. Experimental results demonstrate a training accuracy of 98.4% and a testing accuracy of 92.8% with real-time performance of 15–20 FPS under daylight conditions, stable performance in real time, and feasibility for installation in passenger cars, trucks, and buses. The proposed method contributes a low-cost, efficient, and deployable solution for reducing road accidents with a focus on lightweight embedded implementation.
Development of an AI and Webserver-integrated Smart Automated Storage and Retrieval System Quang-Thien Nguyen; Thien-Bao Truong; Tan-Huy Tran; Tan-Loc Nguyen; Ngoc-Son Vo; Nguyen-Khang Bui; Van-Dong-Hai Nguyen; Thanh-An Cao; Thi-Ngoc-Thao Nguyen; Thi-Hong-Lam Le
Journal of Fuzzy Systems and Control Vol. 4 No. 2 (2026): Vol. 4 No. 2 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v4i2.381

Abstract

In recent years, Automated Storage and Retrieval Systems (AS/RS) and their development have been a notable trend of modern warehouse management by automating the sequential and precise processes of storing, sorting, and retrieving goods. Driven by the convergence of mechatronic systems, Industrial Internet of Things (IIoT), Artificial Intelligence (AI), cloud storage, and edge-based management systems, the potential and practical benefits of AS/RS can be significantly amplified when effectively combined with these trends. In this field, although some works are presented, they often lack specialization for the Vietnamese industrial environment and sustainability. Therefore, this research presents the development of an intelligent AS/RS, incorporating AI-based label processing and webserver-based control to enhance warehouse management efficiency. Experimental evaluations demonstrate that the system achieves high reliability in product classification and storage tasks, providing a scalable solution for modern smart logistics with real-time data synchronization capabilities via a Node-RED web server.
Stabilization of Double Inverted Pendulum using LQR-based Information Fusion Fuzzy Control Truong-Phuong-Nam Pham; Le-Thao-Nguyen Nguyen; TrongBang Tran; Dai-An Ly; Anh-Phong Nguyen; Van-Tung Dau; Nhut-Nam Nguyen; Ba-Thien Tran; Tri-Bao Tran; Dinh-Binh Vo; Van-Duc Nguyen; Thi-Ngoc-Thao Nguyen; Thanh-Tung Nguyen
Journal of Fuzzy Systems and Control Vol. 4 No. 2 (2026): Vol. 4 No. 2 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v4i2.370

Abstract

Modeling the six-state Double Inverted Pendulum on Cart (DIPC) is highly challenging due to its strong nonlinearities and underactuated dynamics. To address this, the system model in this study is derived using a systematic forward-kinematics-based formulation from robotics theory, previously validated for accuracy in both LQR experiments and ANFIS simulations reported in earlier work. Building on this validated foundation, the present study proposes an Information Fusion Fuzzy Logic Controller (IF-FLC) to overcome the curse of dimensionality commonly encountered when designing fuzzy controllers for high-order systems. The method compresses the six measured state variables into two synthesized linguistic inputs—Synthesized Error (E) and Error Change (EC)—allowing the construction of an efficient 49-rule fuzzy controller without compromising essential system dynamics. Simulations incorporating encoder quantization and realistic measurement constraints show that the proposed IF-FLC provides stable balancing performance and improved robustness compared with the LQR benchmark. The results indicate that information-fusion-based fuzzy design is a promising approach for reducing controller complexity while maintaining high performance, offering a practical pathway for implementing intelligent control strategies on nonlinear and underactuated systems such as the DIPC.
Conveyor Speed Control with Fuzzy-PID Minh-Nam Phan; Van-Thao Nguyen; The-An Nguyen; Thi-Ngoc-Thao Nguyen; Thanh-Binh Nguyen; Thi-Hong-Lam Le; Van-Hiep Nguyen; Hoang-Lam Le; Van-Phuc Nguyen; Phong-Nam Huynh; Vi-Cuong Hong; Tuan-Minh Truong; Kieu-Vinh Nguyen; Huu-Nhan Tran
Journal of Fuzzy Systems and Control Vol. 4 No. 2 (2026): Vol. 4 No. 2 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v4i2.379

Abstract

Conveyor belt systems are essential components in industrial automation, but controlling their speed accurately is a significant challenge. Classic PID controllers, while common, struggle to handle the inherent nonlinearities of these systems, such as varying friction and sudden load changes. The adaptive Fuzzy-PID controller, which auto-tunes its parameters, has been proposed as a superior alternative. However, most existing research is limited to software simulations, leaving a gap between theoretical performance and practical, real-world applicability. This paper addresses this gap by presenting the complete design, construction, and experimental verification of a Fuzzy-PID controller implemented on a physical conveyor belt model. The methodology includes system identification via multi-sine input to extract a baseline transfer function, followed by the deployment of the control algorithm on an embedded Arduino Nano microcontroller. Experimental results are presented and directly compared with those of a conventional PID controller to evaluate its performance. Quantitative findings confirm that the embedded Fuzzy-PID controller provides superior performance, reducing the rise time to 0.16 s (from 0.20 s) and significantly decreasing the settling time to 0.56 s (a 48.1% improvement over the PID's 1.08 s). Furthermore, the steady-state error was reduced by 36.4%, demonstrating its superior stability and efficiency in a practical hardware environment and confirming its feasibility for industrial applications.
Design and Implementation of PID and Fuzzy-PID Controllers for Ball-on-Plate Quoc-Khanh Tran; Pham-Minh-Trong Vo; Hoang-Dung Nguyen; Tran-Nhat Dang; Thi-Ngoc-Thao Nguyen; Thi-Hong-Lam Le; Phong-Luu Nguyen; Thanh-Binh Nguyen; Van-Hiep Nguyen; Ngoc-Long Le
Journal of Fuzzy Systems and Control Vol. 4 No. 2 (2026): Vol. 4 No. 2 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v4i2.380

Abstract

This paper presents the design, implementation, and comparative evaluation of a conventional PID controller and a Fuzzy-PID controller for a nonlinear Ball-on-Plate (BoP). The primary objective is to stabilize the ball at a desired position on the plate while achieving a fast transient response and robustness against disturbances. A conventional PID controller is first designed and tuned using the Ziegler–Nichols method. To improve performance under nonlinear conditions, a Fuzzy-PID controller is developed in which fuzzy logic adaptively adjusts the PID gains online. The proposed controllers are evaluated through three stages: numerical simulation in MATLAB/Simulink, real-time implementation in Python, and experimental validation on a physical hardware platform. Compared with the conventional PID controller, the Fuzzy-PID controller achieves a reduction in maximum overshoot from 0.17% to below 0.1% in simulation, a shorter settling time (approximately 4.0 s for PID versus 2.8 s for Fuzzy-PID), and a reduction in steady-state positioning error of approximately 33–36% in hardware experiments (from ~3–14 pixels to ~2–9 pixels).
Design and Implementation of an IoT-Enabled Autonomous Fire-Fighting Robot Using Vision-Based Fire Detection Hoang-Thong Nguyen; Quoc-Thuan Nguyen; Phuoc-Dat Tran; Quang-Khai Nguyen; Thi-Hong-Lam Le; Le-Minh-Kha Nguyen; Van-Hiep Nguyen; Thanh-Binh Nguyen; Ngoc-Hung Nguyen; Thi-Ngoc-Thao Nguyen; Son-Thanh Phung; Hoang-Lam Le; Thanh-Toan Nguyen; Hai-Thanh Nguyen
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 | DOI: 10.59247/jfsc.v3i3.354

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.
Co-Authors Anh-Huy Nguyen Anh-Phong Nguyen Anh-Son Tran Ba-Thien Tran Binh-Hau Nguyen Binh-Hau Nguyen Chi-Phat Pham Cong-Tan Bien Dai-An Ly Dang-Khoa Dinh Dang-Khoa Tran Dinh-Binh Vo Dinh-Nguyen-Phuc Le Duc-Dat Nguyen Duong-Thuan Nguyen Hai-Nam Tran Hai-Thanh Nguyen Hang-Ri Nguyen Hoai-Bao-Nhan Nguyen Hoang-Dung Nguyen Hoang-Lam Le Hoang-Linh Le Hoang-Nguyen Nguyen Hoang-Phuc Le Hoang-Sang Luong Hoang-Thong Nguyen Hong-Nho Bui Hung-Ky Nguyen Hung-Thinh Bui Huu-Loc Dang Huu-Nhan Nguyen Huu-Nhan Tran Huynh-Anh-Tuan Pham Huynh-Duc Pham Huynh-Duc-Anh Nguyen Huynh-Khanh-Nam Pham Kieu-Vinh Nguyen Le-Huu-Tri Do Le-Minh-Kha Nguyen Le-Minh-Tan Nguyen Le-Nhat-Minh Nguyen Le-Thao-Nguyen Nguyen Manh-Dung Nguyen Minh-Nam Phan Minh-Tam Nguyen Minh-Tri Hoang Nam-Long Tran Ngoc-Hung Nguyen Ngoc-Long Le Ngoc-Son Vo Nguyen-Cong-Anh Tran Nguyen-Khang Bui Nguyen-Thanh-Loc Tran Nhat-Nam Nguyen Nhut-Nam Nguyen Pham-Minh-Trong Vo Phong-Luu Nguyen Phong-Nam Huynh Phuoc-Dat Tran Phuoc-Duy Nguyen Phuoc-Thinh Dang Quang Tran Quang-Khai Nguyen Quang-Thien Nguyen Quang-Thuan Le Quang-Tung Trinh Quoc-Khanh Tran Quoc-Thuan Nguyen Quoc-Trung Nguyen Son-Thanh Phung Tan-Huy Tran Tan-Loc Nguyen Tan-Phat Nguyen Thai-Duong Hoang Thai-Hiep Nguyen Thanh-An Cao Thanh-Binh Nguyen Thanh-Binh Phan Thanh-Sang Nguyen Thanh-Toan Nguyen Thanh-Tung Nguyen Thanh-Viet Ho The-An Nguyen The-Nhan Nguyen Thi-Hong-Lam Le Thi-Ngoc-Hieu Phu Thi-Ngoc-Tram Tran Thien-Bao Truong Thien-Quoc Dang Tien-Dat Nguyen Tran-Nhat Dang Tri-Bao Tran Trong-Bang Tran TrongBang Tran Trung-Kien Pham Trung-Son Huynh Truong-Nguyen Phan Truong-Phuong-Nam Pham Tu-Duc Nguyen Tuan-Minh Truong Van-Dong-Hai Nguyen Van-Duc Nguyen Van-Hiep Nguyen Van-Huy Le Van-Phuc Nguyen Van-Thao Nguyen Van-Tuan Nguyen Van-Tung Dau Vi-Cuong Hong Viet-Tien-Dung Bui Vo-Minh-Khoa Tran Xuan-Tien Nguyen