cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Hari Maghfiroh
Contact Email
jfsc.journal@gmail.com
Phone
-
Journal Mail Official
jfsc.journal@gmail.com
Editorial Address
Jl. Empu Sedah No. 12, Pringwulung, Condongcatur, Kec. Depok, Kabupaten Sleman, Daerah Istimewa Yogyakarta 55281, Indonesia
Location
Kab. sleman,
Daerah istimewa yogyakarta
INDONESIA
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 116 Documents
 8   9   10   11   12 
A Heuristic Evolutionary Multi-Objective Method for Indoor LED Lighting Optimization with DIALux and Experimental Validation Faizal Abdul Rouf Asyahari; W Warindi; I Inayati
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.v4i2.425

Abstract

Indoor lighting optimization is commonly addressed using population-based metaheuristic algorithms such as the genetic algorithm and multi-objective particle swarm optimization. However, these methods generally rely on crossover, mutation, or swarm-update operators, resulting in relatively high computational complexity while placing greater emphasis on algorithmic optimization than on practical implementation and experimental validation. This study proposes a heuristic evolutionary multi-objective method for indoor LED lighting optimization that integrates constraint-aware candidate generation, lexicographical multi-objective ranking, and photometric evaluation to determine energy-efficient lighting layouts. Unlike conventional evolutionary algorithms, the proposed method directly generates feasible candidate solutions without employing crossover or mutation operators, thereby reducing computational complexity while maintaining solution quality for structured indoor lighting layouts. The optimized lighting configurations were validated through numerical photometric calculations based on SNI 6197:2020, DIALux simulations using a Lambertian photometric model, and direct luxmeter measurements. Experimental validation confirmed that the optimized lighting layouts satisfied the required illuminance and uniformity criteria, with average illuminance deviations ranging from 6% to 17% between computational predictions and practical measurements. The optimized lighting layouts also achieved Lighting Power Density (LPD) values ranging from 4.89 to 5.50 W/m², which are below the maximum allowable limit specified by SNI 6197:2020, demonstrating that the proposed optimization framework effectively reduces energy consumption while maintaining the required lighting performance. The proposed method provides a practical alternative to conventional evolutionary optimization methods by integrating efficient multi-objective optimization with comprehensive simulation and experimental validation, enabling reliable, energy-efficient, and standards-compliant indoor LED lighting design.
Development of a Vision-Based Color Sorting and Packaging System Using a 3-DOF Robotic Arm and PLC Control Kha-Vy Ngo; Hien-Dat Phan; Nguyen-Thanh-Phong Dang; Chi-Huy Lu; Quoc-Thinh Nguyen; Minh-Thang Vo; Binh-Hau Nguyen; Van-Tien Tran; Bao Pham; Long-Phi Pham; Nguyen-Duc-Duong Le; Quoc-Khanh Trinh; Tuan-Kiet 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.v4i2.391

Abstract

Automated sorting and packaging play an important role in improving manufacturing productivity while reducing manual labor. An integrated automation platform for color sorting and packaging was designed and implemented by combining a three-degree-of-freedom (3-DOF) robotic arm, machine vision, and PLC-based control. Product images were acquired by a webcam for color recognition and position estimation, while system coordination was performed by a Siemens S7 1214 PLC controlling the conveyor, robotic arm, pneumatic capping mechanism, and supervisory functions. Real-time monitoring and basic operating functions were provided through an Android application communicating via the Modbus RTU protocol. Cycle testing demonstrated a theoretical capacity of 144 items per hour based on a 25-second processing duration and a 70% success rate. Parallel task scheduling in the PLC reclaimed approximately 2.5 seconds per run by removing idle delays between actuators. The physical rig brings together camera-based detection, PLC logic, robotic handling, and pneumatic tooling on one bench. Such performance benchmarks validate the design for academic experimentation and small-scale manufacturing.
Adaptive Sliding Mode Control with a Nonlinear Sliding Surface for DC-Bus Voltage Regulation in a Renewable-Energy-Based DC Microgrid Rudi Uswarman; Rifqi Firmansyah; Firmansyah Nur Budiman; Taufal Hidayat; Triawan Nugroho
Journal of Fuzzy Systems and Control Vol. 4 No. 3 (2026): Vol. 4 No. 3 2026
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v4i3.410

Abstract

This study proposes an adaptive sliding mode control (ASMC) scheme incorporating a nonlinear sliding surface (NSS), denoted ASMC-NSS, for direct-current (DC)-bus voltage regulation in a renewable-energy-based DC microgrid. ASMC augments conventional sliding mode control (CSMC) through channel-wise switching-gain scheduling based on the integral absolute error (IAE), while the NSS introduces bounded, state-dependent scaling of the current-tracking surface. The gain schedule adjusts the switching authority as the accumulated tracking error crosses prescribed thresholds, whereas the NSS shapes the reaching dynamics to improve transient tracking and suppress overshoot. The controller is applied to a system integrating a wind turbine, a photovoltaic (PV) array, and battery energy storage. MATLAB/Simulink comparisons with CSMC and ASMC without the NSS show that ASMC-NSS reduces the current-tracking IAE by 90.5% and 87.3%, respectively, and achieves a current settling time of 0.054 s. It maintains the 500 V DC bus with a maximum overshoot of 0.28 V and a 0.02 s recovery time to the ±0.5 V band. Lyapunov analysis establishes asymptotic stability of the ideal inner current loops and uniform ultimate boundedness under bounded matched uncertainties.
Optimization of Photovoltaic (PV) Hosting Capacity in 20 kV Distribution System Using Grey Wolf Optimizer (GWO) Algorithm Syah Ridho Natiqoh; Atikah Surriani; Jimmy Trio Putra; Ahmad Adhiim Muthahhari
Journal of Fuzzy Systems and Control Vol. 4 No. 3 (2026): Vol. 4 No. 3 2026
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v4i3.426

Abstract

The transition toward sustainable energy systems to mitigate global warming caused by greenhouse gas emissions from fossil fuel-based power generation has accelerated the integration of photovoltaic (PV) systems into distribution networks. However, massive and uncontrolled PV integration may lead to operational issues in power systems. Therefore, hosting capacity studies are required to determine the maximum PV capacity that can be integrated without violating technical operating constraints. Due to the complex, non-linear, and non-convex nature of the hosting capacity problem, effective optimization techniques are necessary. This study proposes the Grey Wolf Optimizer (GWO) algorithm to determine the optimal location and capacity of PV with the objectives of maximizing the PV penetration while minimizing system power losses. The Site Planning Model (SPM) method is employed to identify candidate buses for PV installation, thereby reducing space and computational time. By coupling GWO's global search with SPM-based candidate-bus pre-selection, this study reduces the optimization search space while preserving solution quality. The IEEE 33-bus 20 kV test system is used to evaluate the performance of the proposed method in single and multiple PV installations with inverter power factors of unity and 0.95 lagging. The results show that the GWO algorithm achieves stable and consistent convergence, with a maximum PV penetration rate of 87.99% and a system power loss reduction of 85.57% in the scenario involving three PV units on three busbars at a 0.95 lagging power factor. Furthermore, an inverter power factor closer to unity tends to reduce the maximum achievable PV penetration. The proposed approach also improves voltage profiles, reduces line loading, and enhances overall distribution system performance.
Sorting Model using Robotic Arm with Image Processing Nguyen-Khoa Tran; Dinh-Khang Nguyen; Phong Luu Nguyen; Nhat-Anh Huynh; Thanh-Hung Tran; Khac-Dinh Nguyen; Xuan-Anh Dinh; Binh-Hau Nguyen; Gia-Phu Nguyen; Minh-Phuoc Cu
Journal of Fuzzy Systems and Control Vol. 4 No. 3 (2026): Vol. 4 No. 3 2026
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v4i3.387

Abstract

This paper presents the design and implementation of a product sorting model using a robotic arm integrated with image processing techniques. The system consists of a conveyor belt, a vision module, and robotic manipulators that work together to identify and classify objects through a camera and computer vision algorithms that detect product characteristics. The robotic arm then performs the corresponding sorting operation according to product quality requirements. The hardware design includes the construction of the robotic arm, control circuits, and integration with actuators, while the software design focuses on developing image processing algorithms and communication between the vision system and the robot controller. Experimental results show that the system achieves an average size measurement error of approximately ±2 mm, a classification accuracy of about 95%, and an average processing time of 2–3 seconds per product. These results demonstrate reliable recognition and classification performance compared to some previous research models. The proposed model emphasizes the feasibility of combining robotic manipulation and computer vision for automated sorting tasks in industrial applications such as food processing, household tools, and medical instruments, while also serving as a practical training platform for students in technical education. Future improvements may include optimizing vision algorithms, enhancing the mechanical design of the robotic arm, integrating artificial intelligence to improve safety, and expanding the system’s capability to handle more complex classification tasks.
Image Processing-Based Morris Water Maze Rat Tracking System: Design and Analysis Sutrisno Ibrahim; Gayatri Dewani; Joko Hariyono; Faisal Rahutomo; Nanang Wiyono; Ratih Yudhani
Journal of Fuzzy Systems and Control Vol. 4 No. 3 (2026): Vol. 4 No. 3 2026
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v4i3.411

Abstract

Four experimental rats consisting of one normal rat and three Alzheimer's-induced rats were analyzed. The proposed system employed ImageJ integrated with the RatsTrack and Macro RatsTrack plugins using a centroid based tracking approach. The system successfully extracted movement trajectories, distance travelled, speed, acceleration, and quadrant dwell time during acquisition and probe trials. The system performance was validated by comparing quadrant dwell times obtained from the proposed system with manual observations. The percentage differences ranged from 2.29% to 70.97%. demonstrating that the proposed system can effectively represent rat behavioral patterns, although discrepancies remain in certain quadrants requiring further refinement.

Page 12 of 12 | Total Record : 116

 8   9   10   11   12 

Filter by Year

2023 2026


Reset
Filter By Issues
All Issue Vol. 4 No. 3 (2026): Vol. 4 No. 3 2026 Vol. 4 No. 2 (2026): Vol. 4 No. 2 (2026) Vol. 4 No. 1 (2026): Vol. 4 No. 1 (2026) Vol. 3 No. 3 (2025): Vol. 3 No. 3 (2025) Vol. 3 No. 2 (2025): Vol. 3, No. 2, 2025 Vol. 3 No. 1 (2025): Vol. 3, No. 1, 2025 Vol. 2 No. 3 (2024): Vol. 2, No. 3, 2024 Vol. 2 No. 2 (2024): Vol. 2, No. 2, 2024 Vol. 2 No. 1 (2024): Vol. 2, No. 1, 2024 Vol. 1 No. 3 (2023): Vol. 1, No. 3, 2023 Vol. 1 No. 2 (2023): Vol. 1, No. 2, 2023 Vol. 1 No. 1 (2023): Vol. 1, No. 1, 2023 More Issue