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Journal of Fuzzy Systems and Control (JFSC)
Published by Peneliti Teknologi Teknik Indonesia
ISSN : -     EISSN : 29866537     DOI : https://doi.org/10.59247/jfsc.v1i1.24
Core Subject : Science, Engineering,
Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering
Journal of Fuzzy Systems and Control is an international peer review journal that published papers about Fuzzy Logic and Control Systems. The Journal of Fuzzy Systems and Control should encompass original research articles, review articles, and case studies that contribute to the advancement of the theory and application of fuzzy systems and control, and their integration with other technologies, such as artificial intelligence, machine learning, and optimization.
Arjuna Subject : Teknik (semua kategori) - Teknik Kontrol dan Sistem
Articles 85 Documents
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Monitoring the Technical Condition of Traction Substation Equipment using Thermal Imaging Technologies and Machine Vision Methods Ermachkov, G; Nezevak, V
Journal of Fuzzy Systems and Control Vol. 3 No. 1 (2025): Vol. 3, No. 1, 2025
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v3i1.270

Abstract

This article discusses the development and application of machine vision technologies and thermal imaging diagnostics for monitoring the technical condition of traction substation equipment. The focus is on improving the efficiency and reliability of detecting equipment overheating and identifying potential failures by integrating image processing methods with thermal monitoring systems. Previous studies have demonstrated the effectiveness of using thermal imaging for detecting overheating zones in electrical equipment, such as transformers, switchgear, and high-voltage cables. Recent works have also applied machine vision techniques for the automated analysis of temperature distribution and defect detection in substation equipment. However, the integration of these methods for real-time diagnostics and predictive maintenance is still in its early stages. In comparison with previous research, this article presents a novel combined approach that combines thermal imaging data with machine learning models to predict temperature trends and identify early signs of thermal aging in equipment. Unlike prior studies that focused primarily on static analysis of thermal images, this work contributes by proposing a dynamic monitoring system that continuously evaluates the thermal condition of key substation components.
Optimization of Linear Quadratic Regulator for Reaction Wheel Inverted Pendulum using Particle Swarm Optimization: Simulation and Experiment Binh, Hau Nguyen; Dinh , Dat Tran; Cong, Anh Doan
Journal of Fuzzy Systems and Control Vol. 3 No. 1 (2025): Vol. 3, No. 1, 2025
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v3i1.271

Abstract

This paper presents an optimization approach for the Linear Quadratic Regulator (LQR) applied to a Reaction Wheel Inverted Pendulum (RWIP) system, utilizing Particle Swarm Optimization (PSO). The study involves both simulation and real-world experimental verification. A mathematical model of the system is first developed using the Euler Lagrange method, and the LQR controller is designed to stabilize the highly nonlinear system, specifically a Single Input-Multiple Output (SIMO) system. PSO is employed to fine-tune the LQR parameters, optimizing performance metrics such as overshoot, settling time, and steady-state error. Simulation results, performed in MATLAB, are compared with experimental results obtained using an STM32F407 microcontroller-based hardware setup. PSO optimized LQR demonstrates significant improvements in stability and response time, outperforming standard optimization. The results confirm the efficiency of PSO in optimizing control systems for nonlinear dynamics, with potential applications in balancing robotics and self-stabilizing vehicles.
Analysis of Linear and Intelligent Control for Balancing Pendubot System Tran, Minh-Duy; Le, Diep-Thuy-Duong; Phan, Hong-Phuoc; Vo, Hoang-Viet; Ngo, Dang-Quang-Tinh; Nguyen, Ngoc-Duy; Nguyen, Tan-Phat; Tran, Nhat-Linh; Vo, Thanh-An; Le, Thi-Thanh-Hoang
Journal of Fuzzy Systems and Control Vol. 3 No. 1 (2025): Vol. 3, No. 1, 2025
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v3i1.272

Abstract

Pendubot is a typical under-actuated SIMO control system, commonly used in research on control algorithms. Rather than focusing on analyzing a single control algorithm, this paper provides an overview of control efficiency as well as differences between algorithms through analytical assessments. In this study, the authors analyzed algorithms including feedback linearization (a linear algorithm), LQR – optimal control (a linear algorithm), and fuzzy control (an intelligent algorithm) to stabilize the model at the equilibrium position of the TOP position – where both bars of the system stand upright in the opposite direction to gravity. The genetic algorithm (GA) is used to optimize control parameters for the model. These algorithms are simulated in MATLAB/Simulink, and the simulation results are compared, concluding that the LQR control algorithm is the most optimal for balancing this model.
Comparative Traditional Methods of Attributes with Fuzzy Quality Control Charts for Improving the Quality of a Product Omran, Salman Hussien; Shneen, Salam Waley; Ali, Moaz H.; Jawad, Qusay A.; Gitaffa, Sabah A.; Salman, Hayder Mahmood
Journal of Fuzzy Systems and Control Vol. 3 No. 1 (2025): Vol. 3, No. 1, 2025
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v3i1.273

Abstract

The problems motivating the study, as a result of sudden changes in production quality levels, which affect the production process. Control charts are a major tool in statistical quality control. The aim of the study is to monitor the production quality of a product that is an engine used in the application of a hair dryer. The methodology followed, the hair dryer model was chosen to verify the possibility of improving the product quality using fuzzy logic and comparing the traditional Shewhart control charts (p-chart) with the fuzzy p-chart in the context of manufacturing, and the collected data were processed using Minitab 21 Statistical Software. The performance of a control chart using fuzzy logic was measured for the proposed industrial product type with specifications for 300 samples of the constant size and a production period of 25 days to identify the product quality. The basic criterion for drawing the chart using fuzzy logic depends on the fuzzy ordering function for each of w, λ and its values are within the limits of (0 < λ or w ≤ 1) is a weighting parameter. The necessary tests were conducted to monitor the product quality using (w = 0.1, 0.2) and (λ = 0.1, 0.2) when the fuzzy ordering function is used. Results, it was found that the fuzzy p-chart was more sensitive to process changes and could detect shifts in defect ratio faster and more accurately, the production process was under statistical control and within quality control limits, and the conventional deviation from nominal control charts showed a false alarm for the observation as out of control. Recommendations, the present method can be used to improve product quality and reduce defects for the motor department.
Anomaly-based Detection of Denial of Service via Deep Learning Memetic Trained Modular Network Ejeh, Patrick Ogholuwarami; Adjogbe, Fidelis Oghenevweta; Nwanze, David; Binitie, Amaka Patience
Journal of Fuzzy Systems and Control Vol. 3 No. 1 (2025): Vol. 3, No. 1, 2025
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v3i1.274

Abstract

Internet’s popularity for dissemination of data – has birthed the proliferation of attacks that exploit networks for personal gain. Attackers via social-engineering attacks, gain unauthorized access to a compromised device via subterfuge mode and deny users of network resources. Denial of service (DoS) attack is carefully crafted to exploit high levels of network infrastructures. Our study presents a deep learning scheme to effectively classify between genuine and malicious packets. With benchmark XGBoost, Random Forest, and Decision Tree – our resultant model yields an accuracy 0.9984 and F1 0.9945 to outperform the benchmark XGBoost, RF and DT (with F1 of 0.9925, 0.9881 and 0.9805 – and Accuracy of 0.9981, 0.9964 and 0.9815) respectively. Proposed model correctly classified 13,418 cases with a 0.9984 accuracy and has only 283 cases incorrectly classified. Proposed memetic ensemble effectively differentiates malicious from genuine packets using anomaly-based detection.
Backstepping Control for Ball and Beam: Simulation and Experiment Tran, Vo-Hoang-Lap; Le, Trung-Hieu; Hoang, Dai-Phuc; Nguyen, Van-Dong-Hai; Ho, Ngoc-Thinh; Do, Tien-Phat; Le, Tuan-Cuong; Tran, Thi-Xuan-Hy; Luong, The-Duy; Vo, Thanh-Son; Nguyen, Phuoc-Khanh; Nguyen, Minh-Tam
Journal of Fuzzy Systems and Control Vol. 3 No. 1 (2025): Vol. 3, No. 1, 2025
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v3i1.275

Abstract

This paper presents the modeling and control of the Ball and Beam system, a commonly used Single Input – Multiple Output (SIMO) system in control research experiments. In the study, the Backstepping method is applied to model and control the system. The linear differential equations describing the system's dynamics are derived based on fundamental mechanical principles, using the Euler-Lagrange method to develop an accurate mathematical model. Subsequently, the backstepping method is employed to design a controller that ensures the global stability of the system. Lyapunov theory is applied to prove the system's stability, with an appropriate Lyapunov function selected to guarantee the global stability of the controller. In addition to simulations, the study also conducts experiments to test the system's stability under Backstepping control. The results show that this controller is not only effective in maintaining balance and controlling the position of the ball on the beam but also addresses the limitations of traditional linear control methods. Both simulation and experimental results demonstrate the high performance and stability of the system, confirming the stability according to Lyapunov theory.
Trajectories Tracking Control for Rotary Inverted Pendulum using Backstepping Method Pham, Ha-Gia-Bao; Nguyen, Huy-Khai; Nguyen, Tran-Quoc-Tuan; Nguyen, Van-Dong-Hai; Dao, Ngoc-Quy; Ngo , Van-Quy-Hai; Tran, Thanh-Son; Phan, Hien-Dat; Chu, Gia-Huy; Huynh, Hoang-Tien-Phat
Journal of Fuzzy Systems and Control Vol. 3 No. 1 (2025): Vol. 3, No. 1, 2025
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v3i1.276

Abstract

Rotary inverted pendulum (RIP) is a fundamental yet challenging benchmark system in control engineering due to its nonlinear dynamics, instability, and underactuated nature. This study addresses the problem of trajectory tracking control for RIP, which is critical for ensuring system stability and accurate motion control in various engineering applications. Simulation results demonstrate that the backstepping approach achieves superior performance in terms of tracking accuracy, robustness, and convergence speed compared to traditional methods. The findings emphasize the effectiveness of backstepping in addressing control challenges in nonlinear systems, offering insights for future research in both theoretical advancements and real-world applications.
Experimental Swing-Up Control of Advanced Sliding and Energy-based Modes for Pendubot Tran, Minh-Duy; Trinh, Minh-Phu; Do, Nguyen-Son; Phan, Thai-Chan; Ngo, Tan-Bao-Chau; Nguyen, Viet-Thuan; Ngo, Viet-Dung; Hoang, Ngoc-Quan; Trinh, Tan-Phong; Le, Thi-Hong-Lam
Journal of Fuzzy Systems and Control Vol. 3 No. 1 (2025): Vol. 3, No. 1, 2025
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v3i1.277

Abstract

This study focuses on the implementation and comparative evaluation of two swing-up control strategies—Energy-Based Methods (EBM) and Advanced Sliding Mode Control (ASMC)—for pendubot, a nonlinear two-link robotic system. While previous research has extensively explored balancing algorithms for this model, swing-up strategies have primarily been analyzed through simulations, with limited application to real-world systems. This research addresses this gap by deploying both EBM and ASMC on a physical pendubot model. Practical results are presented to provide the most accurate evaluation of the control quality of each algorithm.
Comparative Analysis of Fuzzy Membership Functions for Step and Smooth Input Tracking in a 3-Axis Robotic Manipulator Chotikunnan, Phichitphon; Chotikunnan, Rawiphon; Pititheeraphab, Yutthana; Puttasakul, Tasawan; Wongkamhang, Anantasak; Thongpance, Nuntachai
Journal of Fuzzy Systems and Control Vol. 3 No. 1 (2025): Vol. 3, No. 1, 2025
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v3i1.278

Abstract

Robotic manipulators are essential in industrial and medical applications, requiring precise control to improve efficiency and reduce errors. This research looks at how well fuzzy logic controllers using Gaussian, generalized bell, triangular, and trapezoidal membership functions can handle step and smooth inputs for a robot system that is meant to move materials. Critical metrics like steady-state values, overshoot, rise time, integral absolute error (IAE), and root mean square error (RMSE) were tested using five different methods. The results showed that both the Gaussian and extended bell functions found a good balance between being stable and being responsive. This made them useful for situations with moderate to high input levels. While triangular functions displayed enhanced responsiveness, they also revealed heightened overshoot. In contrast, trapezoidal functions demonstrated significant stability at high saturation levels, although they had challenges in attaining smooth transitions. These findings highlight the necessity of choosing membership functions according to particular application needs. This study investigates the utilization of hybrid methodologies and adaptive optimization strategies to improve fuzzy control systems. These concepts offer compelling approaches to improve accuracy and resilience in dynamic robotic settings.
Position Control of 3-DOF Experimental Articulated Robot Arm using PID Controller Vo, Dinh-Hieu; Le, Nam-Chau; Nguyen, Thi-Y-Nhi; Huynh, Tran-Phuong; Huynh, Nhat-Truong; Tran, Kim-Huy; Nguyen, Ba-Chinh; Do, Truong-Giang; Tran, Gia-Huy; Nguyen, Van-Dong-Hai
Journal of Fuzzy Systems and Control Vol. 3 No. 1 (2025): Vol. 3, No. 1, 2025
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v3i1.291

Abstract

In this paper, we are simulating a 3-degrees of freedom (DOF) Articulated Robot Arm, calculating kinematics and building a PID controller for the 3-Dof Articulated Robot Arm. First, the design process of the 3-Dof robot arm model is done on the Solid works platform. Second, the PID control method is used to determine the "error" value which is the between the measured value of the variable parameter and the desired set value. The controller will minimize errors by adjusting the input control value. Finally, a real robot arm was controlled to move following the reference in the plane with the PID controller embedded on the Arduino microcontroller and collected data about the computer.

Page 6 of 9 | Total Record : 85

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