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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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Investigating an Anomaly-based Intrusion Detection via Tree-based Adaptive Boosting Ensemble Onoma, Paul Avweresuo; Agboi, Joy; Geteloma, Victor Ochuko; Max-Egba, Asuobite ThankGod; Eboka, Andrew Okonji; Ojugo, Arnold Adimabua; Odiakaoase, Christopher Chukwufunaya; Ugbotu, Eferhire Valentine; Aghaunor, Tabitha Chukwudi; 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.v3i1.279

Abstract

The eased accessibility, mobility, and portability of smartphones have caused the consequent rise in the proliferation of users' vulnerability to a variety of phishing attacks. Some users are more vulnerable due to factors like personality behavioral traits, media presence, and other factors. Our study seeks to reveal cues utilized by successful attacks by identifying web content as genuine and malicious data. We explore a sentiment-based extreme gradient boost learner with data collected over social platforms, scraped using the Python Google Scrapper. Our results show AdaBoost yields a prediction accuracy of 0.9989 to correctly classify 2148 cases with incorrectly classified 25 cases. The result shows the tree-based AdaBoost ensemble can effectively identify phishing cues and efficiently classify phishing lures against unsuspecting users from access to malicious content.
Voice-based Dynamic Time Warping Recognition Scheme for Enhanced Database Access Security Onoma, Paul Avweresuo; Ugbotu, Eferhire Valentine; Aghaunor, Tabitha Chukwudi; Agboi, Joy; Ojugo, Arnold Adimabua; Odiakaose, Christopher Chukwufunaya; Max-Egba, Asuobite ThankGod; Niemogha, Star Umiyemeromesu; Binitie, Amaka Patience; Abdullahi, Mustapha Barau
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.v3i1.293

Abstract

Rapid transformation with database security has remained imperative as unauthorized access exposes sensitive data to adversaries. To curb this, we suggest using a secured dynamic time-warp scheme to improve access to the database schemas. The study integrates voice biometrics with two-factor authentication to yield a robust, user-friendly platform, which utilizes time-warping to authenticate voice patterns against the variability in utterance speed. Results showcase high accuracy and resiliency in its usage against spoofing attacks as compared to state-of-the-art voice recognition systems. The model ensures the minimal possibility of credential theft by binding the access of databases to the voice features of authorized users. The study shows the system's architecture, implementation, and performance evaluation, highlighting its potential to revolutionize database security in various applications. The findings underscore the importance of leveraging advanced biometric techniques to safeguard critical information systems.
A Study of Optimized-LQR Control for Rotary Inverted Pendulum by Particle Swarm Optimization Le, Thanh-Tri-Dai; Pham, Thanh-Cong; Bui, Duc-Thanh-Long; Nguyen, Quang-Truong; Vo, Van-Nhat-Truong; Dinh, Quoc-Lap; Tran, Le-Hieu; Truong, Thien-Bao; Nguyen, Tan-Loc; Nguyen, Duy-Tan; Nguyen, Tuan-Anh; Nguyen, Viet-Anh; Le, Thi-Thanh-Hoang
Journal of Fuzzy Systems and Control Vol. 3 No. 2 (2025): Vol. 3, No. 2, 2025
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v3i2.301

Abstract

Rotary Inverted Pendulum (RIP) is a classical but effective model in testing control algorithms. Besides designing controllers, it can also be a model for testing the evolution algorithms (EAs) in optimizing control parameters. In this paper, we apply particle swarm optimization (PSO), which is an EA, to optimize the parameters of the LQR controller for this model. In the study, an experimental model in which system parameters are already measured and identified in former studies is used. The LQR control method is inherited from former results, and the weighing matrices (Q and R) are optimized by the PSO method. In each case, the control matrix K is obtained from Q and R to apply for RIP. Through both simulation and experiment, LQR control parameters are found better through generations by using PSO. The responses of RIP, in which controllers are designed under optimized Q and R in later generations, are better in quality, and values of the fitness function also supports that opinion. Thence, through this study, beside genetic algorithm (GA), this study proves that PSO is a suitable searching algorithm that can be applied for balancing this single input- multi output (SIMO) system. Also, the experimental platform of RIP in this research confirms its ability to control tests.
A Study of Adaptive Model Predictive Control for Rotary Inverted Pendulum Huynh, Phuc-Hoang; Le, Khac-Chan-Nguyen; Nguyen, Truong-Phuc; Tran, Hoang-Dang-Khoa; Dang, Su-Truong; Nguyen, Thanh-Quyen; Le, Thang-Phong; Nguyen, Huu-Hanh; Tran, Pham-Hong-Linh; Nguyen, Hau-Phuong; Nguyen, Hoang-Son; Nguyen, Tai-Truong; Nguyen, Hai-Thanh
Journal of Fuzzy Systems and Control Vol. 3 No. 2 (2025): Vol. 3, No. 2, 2025
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v3i2.302

Abstract

This paper proposes an Adaptive Model Predictive Control (MPC) approach for the rotary inverted pendulum (RIP). The method combines Linear Time-Varying (LTV) models at each sampling instant with a Linear Time-Varying Kalman Filter (LTVKF) for state estimation. By predicting and adapting to dynamic system changes, the controller achieves trajectory tracking performance comparable to non-adaptive MPC. However, the Adaptive MPC extends the arm’s operating range by up to 1.5 times, making it a promising solution for strongly nonlinear or time-varying systems like the RIP.
Design of Embedded Control System with Fuzzy Controller and Nonlinear Controller for the Line Follower Robot Chiem, Nguyen Xuan; Nguyen, Nguyen Cong Binh
Journal of Fuzzy Systems and Control Vol. 3 No. 2 (2025): Vol. 3, No. 2, 2025
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v3i2.303

Abstract

In this paper, an embedded system for motion control of a Line Follower Robot (LFR) is presented. Line Follower Robot can change direction by changing the relative rotational speed of the wheels, and thus does not require additional steering motion. A robot designed at the Control Systems Laboratory, Le Quy Don Technical University, is chosen as the research platform in this paper. A fuzzy logic controller has been used to ensure the smallest position and angle deviation. The rules of the fuzzy logic controller are built based on the successor's experience when considering the Lyapunov function. The output of this controller is linear velocity and angular velocity, which are the achieved values ​​for the robot dynamics control loop. A nonlinear controller with blocked signals is synthesized based on the synergetic control theory (STC). The combination of control laws ensures the system is stable enough to measure noise and uncertainties in the robot's model and parameters. In addition, we realize that the control system is embedded. Simulation and experimental results with different scenarios demonstrate the effectiveness of the proposed control law.
LQR Controller Based on BAT Algorithm for Rotary Double Parallel Inverted Pendulum Le, Thanh-Tri-Dai; Nguyen, Ngoc-Kien; Le, Phuc-Truong; Bui, Minh-Nguyen-Bao; Nguyen, Trong-Tin; Tran, Chi-Anh; Doan, Phuong-Tu; Dao, Duc-Nhan; Nguyen, Van-Dong-Hai; Nguyen, Thanh-Tung
Journal of Fuzzy Systems and Control Vol. 3 No. 2 (2025): Vol. 3, No. 2, 2025
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v3i2.304

Abstract

This paper presents an enhanced approach to stabilizing the Rotary Double Parallel Inverted Pendulum (RDPIP) through a combination of the LQR method and the BAT algorithm. Traditionally, selecting appropriate Q and R matrices relies on designers' intuitions or trial-and-error processes, often resulting in suboptimal performance. By leveraging the BAT algorithm’s swarm intelligence, the proposed method automatically optimizes the cost function to yield improved control performance. Key improvements include shorter stabilization time, reduced overshoot, and minimized oscillations. Simulation results show that the BAT-enhanced LQR controller significantly outperforms traditional design in terms of convergence speed and system damping. These findings underscore the potential of metaheuristic algorithms in refining classical control strategies for complex, nonlinear systems.
An LQR-Based ANFIS Control for Double-Linked Inverted Pendulum on Cart Pham, Truong-Phuong-Nam; Tran, Trong-Bang; Nguyen, Van-Dong-Hai; Nguyen, Tai-Tue; Nguyen, Gia-Thinh; Nguyen, Duy-Phat; Nguyen, Dong-Khang; Ha, Van-An; Trinh, The-Nam-Chau; Nguyen, Trung-Thang
Journal of Fuzzy Systems and Control Vol. 3 No. 2 (2025): Vol. 3, No. 2, 2025
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v3i2.307

Abstract

This paper presents a double-linked inverted pendulum on a cart system, which is highly nonlinear and inherently unstable. In the simulation, the state variable outputs are processed through three ENCODER blocks with a resolution of 1000 pulses, as we aim to develop a mathematical model that closely approximates real-world experiments. The objective of this study is to use an ANFIS controller to learn from data that closely resembles the actual system behavior under an LQR controller and apply it in a simulation environment to evaluate the stability and response of the system under both ANFIS and LQR controllers. The results show that the ANFIS controller provides better responses than the LQR controller.
A Study of Simulation and Modeling of Three-Phase Electric Transformers Shneen, Salam Waley; Oleiwi, Fadhil Mahmood; Dahloos, Jaber. O.
Journal of Fuzzy Systems and Control Vol. 3 No. 2 (2025): Vol. 3, No. 2, 2025
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v3i2.308

Abstract

Under the title “A Survey of Simulation and Modeling of a Three-Phase Electric Transformer,” the present work presents a proposed modeling and simulation process for two types of step-up and step-down transformers. To design and build the model, a suitable transformer specification must be established through mathematical representation. To conduct tests using MATLAB, the proposed tests are conducted for both step-up and step-down cases by varying the number of turns in the primary and secondary windings to a step-up ratio of up to ten times, from 300 V to 3000 V, and step-down to 150 V. Transformer considerations for both step-up and step-down cases include maintaining the number of turns in the primary winding at 100 turns, while for step-up, we use the number of turns in the secondary winding at 1000 turns, to obtain ten times the input voltage at the transformer output. In the second test case, the input voltage is 300 V, and the primary coil has 100 turns. Changing the secondary coil from 1,000 turns to 50 turns halves the transformer's input voltage, resulting in a voltage of 50 V. A set of tests can be tabulated to represent different cases suitable for multiple transformers that can be built for the same prototype, as well as to serve as a reference for future studies.
Firefly Algorithm-Based PID Optimization for Active Suspension Systems in Electric Vehicles Bui, Van-Cuong; Le, Van-Quynh; Ngo, Anh-Nguyet; Canh, Chi-Huan
Journal of Fuzzy Systems and Control Vol. 3 No. 2 (2025): Vol. 3, No. 2, 2025
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v3i2.311

Abstract

This paper presents the optimization of a PID controller for an active suspension (AS) system in the electric vehicle (EV) using the Firefly Algorithm (FA). The objective is to enhance ride comfort and vehicle stability by minimizing body acceleration (BA), suspension dynamic deflection (SDD), and wheel dynamic load (WDL). The proposed AS system is based on a quarter-car EV model. Random road excitation and harmonic disturbances are selected as input conditions to evaluate system performance. The FA is employed to determine the optimal PID parameters, improving the system’s overall efficiency. The AS system and PID controller are developed in the Matlab/Simulink environment. The results demonstrate that the optimized PID-controlled active suspension (AS-OPID) achieves significant performance improvements, reducing the root mean square (RMS) values of BA, SDD, and WDL by 23.05%, 19.78%, and 13.31%, respectively, compared to a passive suspension (PS) system under random road conditions at a vehicle speed of 70 km/h. These improvements highlight the effectiveness of FA in optimizing control parameters, leading to better ride quality and vehicle stability. The findings confirm that FA-based PID optimization is a promising approach for enhancing AS performance in EVs.
ANFIS-Based Fault Detection in Brushed and Brushless DC Motors: A Hybrid Intelligence Approach Chatterjee, Arunava
Journal of Fuzzy Systems and Control Vol. 3 No. 2 (2025): Vol. 3, No. 2, 2025
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v3i2.312

Abstract

Electric motors are a key component in industrial automation and renewable energy systems. Faults like short-circuit and overload conditions may cause performance deterioration, overheating, or even permanent damage. Conventional fault detection techniques depend on threshold-based methods, which are not efficient in handling nonlinear system behavior. The following research introduces an Adaptive Neuro-Fuzzy Inference System (ANFIS) method for fault detection of short-circuit and overload faults in BLDC and DC motors. Through the assessment of input parameters like current, voltage, speed, and temperature, the model efficiently classifies fault conditions with greater accuracy than traditional methods. The outcomes affirm the capability of ANFIS in dealing with nonlinear relationships and enhancing fault detection reliability.

Page 7 of 9 | Total Record : 85

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