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All Journal Journal of Fuzzy Systems and Control (JFSC) Scientific Journal of Engineering Research
Trong-Bang Tran
Konkuk University
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.
A Cost-Effective QR Code-Based Equipment Management System for Small-Scale Clinical Facilities Phong-Luu Nguyen; Dinh-Hai Vu; Trong-Bang Tran
Scientific Journal of Engineering Research Vol. 2 No. 3 (2026): September
Publisher : PT. Teknologi Futuristik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64539/sjer.v2i3.2026.430

Abstract

The rapid proliferation of medical devices in clinical settings necessitates efficient tracking and maintenance to ensure healthcare quality and cost optimization. (Gap) Despite technological advancements, many small to medium-sized clinics continue to rely on manual, paper-based equipment management systems. These traditional methods are prone to human error, lack real-time monitoring, and suffer from inefficient audit trails. (Objective) This study aims to develop a cost-effective, QR code-based equipment management system tailored specifically for small-scale clinical facilities. The proposed system integrates a Flutter-based cross-platform application with a centralized PostgreSQL database, utilizing standard webcams for QR code scanning to eliminate the need for expensive, dedicated scanning hard-ware. (Findings) Experimental implementations demonstrate that the system achieves a >95% QR code identification success rate at optimal scanning distances (0.3–1.0m) under standard lighting. Further-more, the architecture guarantees 99.2% network uptime, seamless real-time data synchronization, and supports up to 20 concurrent users with low database query latency (15–30 ms). Cost analysis indicates significant economic advantages, with first-year operational costs ranging from $300 to $600, markedly lower than commercial alternatives. (Implications) By replacing outdated manual methods with an auto-mated, role-based tracking system, this solution provides clinics with a robust, accessible, and scalable tool to enhance operational efficiency and streamline equipment lifecycle management.
Co-Authors Dang-Khoa Dinh Dinh-Hai Vu Dinh-Nguyen-Phuc Le Hoang-Lam Le Hung-Thinh Bui Huu-Loc Dang Huynh-Duc Pham Le-Nhat-Minh Nguyen Ngoc-Hung Nguyen Phong-Luu Nguyen Thanh-Binh Nguyen Thi-Ngoc-Thao Nguyen Thien-Quoc Dang Trung-Son Huynh Van-Dong-Hai Nguyen Van-Hiep Nguyen Xuan-Tien Nguyen