cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Alfian Ma'arif
Contact Email
alfian_maarif@ieee.org
Phone
-
Journal Mail Official
alfian_maarif@ieee.org
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
Control Systems and Optimization Letters
Published by Peneliti Teknologi Teknik Indonesia
ISSN : -     EISSN : 29856116     DOI : 10.59247/csol
Core Subject : Science, Engineering,
Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering
Control Systems and Optimization Letters is an open-access journal offering authors the opportunity to publish in all fundamental and interdisciplinary areas of control and optimization, rapidly enabling a safe and sustainable interconnected human society. Control Systems and Optimization Letters accept scientifically sound and technically correct papers and provide valuable new knowledge to the mathematics and engineering communities. Theoretical work, experimental work, or case studies are all welcome. The journal also publishes survey papers. However, survey papers will be considered only with prior approval from the editor-in-chief and should provide additional insights into the topic surveyed rather than a mere compilation of known results. Topics on well-studied modern control and optimization methods, such as linear quadratic regulators, are within the scope of the journal. The Control Systems and Optimization Letters focus on control system development and solving problems using optimization algorithms to reach 17 Sustainable Development Goals (SDGs). The scope is linear control, nonlinear control, optimal control, adaptive control, robust control, geometry control, and intelligent control.
Arjuna Subject : Teknik (semua kategori) - Teknik Kontrol dan Sistem
Articles 15 Documents
 1   2 
Search results for , issue "Vol 2, No 2 (2024)" : 15 Documents clear
Book Review on Hosting Capacity for Smart Power Grids, Ahmed F. Zobaa, Shady H. E. Abdel Aleem et al. Springer, 1 2020 Mousa, Hossam H. H.; Mahmoud, Karar; Lehtonen, Matti
Control Systems and Optimization Letters Vol 2, No 2 (2024)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v2i2.98

Abstract

Nowadays, the growing integration of new industrial technologies into modern power systems (MPSs) such as distributed energy resources (DERs) such as various types of renewable energy sources (RESs), electric vehicles (EVs), and energy storage systems (ESSs), caused various adverse impacts that should be considered broadly. These technologies cause various deteriorations on the performance indices (PIs), e. g. voltage deviation and reverse power flows. Therefore, the hosting capacity (HC) concept is declared to ensure that integration is managed efficiently to accommodate them without any PI violations. Various research fields investigated HC technologies in terms of calculation methods, tools, enhancement techniques, etc. in several articles and books. However, the book entitled “Hosting Capacity for Smart Power Grids, Ahmed F. Zobaa, Shady H.E. Abdel Aleem et al. Springer, 1 2020”, is the most recent prominent comprehensive reference for HC strategies in MPSs. Hence, this article proposes a book review and discussion of its most important contributions which helps the reader in realizing the recent developments in HC technologies based on this book’s contents.
A Review on Employing Weather Forecasts for Microgrids to Predict Solar Energy Generation with IoT and Artificial Neural Networks Islam, Md Monirul; Akter, Mst. Tamanna; Tahrim, H M; Elme, Nafisa Sultana; Khan, Md. Yakub Ali
Control Systems and Optimization Letters Vol 2, No 2 (2024)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v2i2.108

Abstract

In this study, an artificial neural network (ANN) based approach is studied about the prediction of solar energy generation in a microgrid using weather forecasting. The ANN is trained using historical data of solar energy generation and weather forecast data. The input parameters for the ANN include weather variables such as temperature, humidity, wind speed, and solar irradiance. The output parameter is the solar energy generation in kilowatt-hour (kWh). The proposed approach is implemented and tested using real-world data from a microgrid. The results indicate that the ANN-based approach is effective in predicting the solar energy generation with high accuracy. The proposed approach can be used for optimizing the operation of microgrids and facilitating the integration of renewable energy sources into the power grid. This study proposes the use of an Artificial Neural Network (ANN) to predict the solar energy generation in a microgrid using weather forecast data. Weather forecasting has become more precise and dynamic with the integration of IoT data with advanced analytics and machine learning models. These models are quite accurate at predicting solar irradiance and analyzing patterns. The microgrid comprises of a photovoltaic (PV) system which generates solar energy and a battery storage system which stores and supplies the energy to the load. Accurate prediction of solar energy generation is crucial for optimizing management of the microgrid. The inputs to the ANN model include temperature, humidity, wind speed, cloud cover and solar irradiance, which are obtained from weather forecast data. The output of the model is the predicted solar energy generation. The performance of the ANN model is evaluated using various performance metrics such as Mean Absolute Error (MAE), Root Mean Squared Error (RMSE) and Coefficient of Determination (R²). This study presents a practical approach for predicting solar energy generation in a microgrid using weather forecast data, which can be used for efficient management of the microgrid.
Challenges and Future Prospects of Electric Vehicles Using Hybrid Energy in Bangladesh - A Case Study Aziz, Tareq; Dodaev, Zohar Al; Hossain, Md. Taufiq; Khan, Md. Yakub Ali
Control Systems and Optimization Letters Vol 2, No 2 (2024)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v2i2.96

Abstract

The main objective of this paper is to review the current challenges and prospects of Electric Vehicles based hybrid energy in Bangladesh. Electric cars (EVs) are a viable way to lessen transportation's negative environmental effects and wean us from fossil fuels. EV adoption has a lot of promise in Bangladesh, where environmental sustainability and energy security are major concerns. However, there are a few obstacles to the general adoption of EVs, including limited infrastructure, high upfront prices, and range anxiety. The difficulties and potential benefits of EVs using hybrid energy in Bangladesh are examined in this case study. It has been reviewed the infrastructure's preparedness, present level of EV adoption, and main obstacles for implementation. In addition, it has been suggested tactics to address these issues, such as public awareness campaigns, infrastructure development, and regulatory changes. It is considered to look at how hybrid energy systems, which combine traditional power grids and renewable energy sources, can power EVs and improve energy sustainability. Bangladesh can achieve sustainable transportation goals, decrease greenhouse gas emissions, and expedite the shift to electric mobility by utilizing hybrid energy solutions and tackling systemic issues. Policymakers, industry stakeholders, and scholars can use this case study to gain important insights into how Bangladesh's energy transition and EV adoption are changing.
A Review on Integration Challenges for Hybrid Energy Generation Using Algorithms Aziz, Tareq; Dodaev, Zohar Al; Halim, Md. Abdul; Khan, Md. Yakub Ali
Control Systems and Optimization Letters Vol 2, No 2 (2024)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v2i2.85

Abstract

The main objective of this paper is to review the challenges associated with the integration used in multiple energy generation from renewable energy sources. There are a number of obstacles that must be overcome for the successful integration of various energy sources and storage technologies in a hybrid energy generation system. Algorithms are very crucial for multiple energy generation due to the integration of renewable energy sources, optimum resource allocation, load balancing, system stability and real time decision making. Demand response, load forecasting, and intelligent decision-making algorithms are examples of successful management tactics that may be used to allocate power from various sources according to availability and cost-effectiveness. To operate effectively, algorithms must take into consideration many variables such as state of the batteries, load changes, and weather. The difficulties with circuit design, algorithm design, source management and switching control in hybrid energy generation systems with numerous sources are covered in this paper. These difficulties include maximizing power generation and usage from each source, dynamic power output adjustment based on energy availability and demand, and smooth source changeover. The paper emphasizes how crucial integration of renewable energy sources, using proper algorithm and switching control among energy sources are for successfully integrating various energy sources. Voltage compatibility, current balance, and surge protection are among the difficulties in circuit design. Switching control techniques are very important fact to guarantee smooth switching between energy sources but minimizing power disturbance during source switching and maintaining a steady power supply throughout the process are challenges in switching control. The challenges in circuit and algorithm design for hybrid energy generation systems with multiple sources are highlighted in this review. Hybrid energy generation systems can accomplish effective use of renewable energy sources and contribute to a sustainable energy future by successfully overcoming these obstacles. Algorithms for optimization could be used to weigh environmental sustainability against economic viability while accounting for energy prices, carbon emissions, and lifecycle analysis.
The Integration of Renewable Energy Sources into Mechanical Systems, Focusing on Efficiency and Reliability - A Case Study Khan, Saidul Islam; Dodaev, Zohar Al; Haque, Abrarul
Control Systems and Optimization Letters Vol 2, No 2 (2024)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v2i2.92

Abstract

The main objective of this review to analyze the efficiency and reliability of renewable energy technologies when integrated into mechanical infrastructure. The concerns of energy sustainability and environmental impact can be effectively addressed by incorporating renewable energy sources into mechanical systems. The use of renewable energy technology to mechanical systems is examined in this case study, with an emphasis on improving dependability and efficiency. The study explores the integration of solar, wind, and hydroelectric power generation into mechanical systems, such as HVAC (heating, ventilation, and air conditioning) systems, industrial machinery, and transportation systems, by means of a thorough analysis of a practical application. Studying the integration of solar, wind and hydroelectric thermal energy to raise building HVAC systems' dependability and efficiency are the main concern of this review. The design, implementation, and optimization of renewable energy systems are important topics covered because they optimize energy output while maintaining dependability and compatibility with the mechanical infrastructure already in place. In addition, the study assesses the technological issues, environmental advantages, and economic feasibility of integrating renewable energy sources, offering insights into successful strategies and difficulties faced. This case study is to educate decision-makers, engineers, and stakeholders about the potential and factors for sustainable energy solutions in mechanical engineering applications by examining the effectiveness and dependability of renewable energy integration in mechanical systems.
An Extensive Analysis of the Significance and Difficulties of Microgrids Based on Renewable Energy in Wireless Sensor Networks Hussain, Md. Naeem; Kader, Kazi Abdul; Ali, Md. Sumon; Ullah, Aman; Dodaev, Zohar Al
Control Systems and Optimization Letters Vol 2, No 2 (2024)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v2i2.102

Abstract

The main objective of this paper is to review the importance of renewable energy based microgrid on wireless sensor networks (WSNs) including challenges of renewable energy-based MGs. This paper explores the critical nexus between Wireless Sensor Networks (WSNs) and microgrids powered by renewable energy, explaining the rising importance of these networks and the issues they provide. Microgrids have become a promising technology in the worldwide search for sustainable energy solutions, since they allow for the effective integration of distributed energy management, local energy production, and Renewable Energy (RE) sources. WSNs allow for the microgrid-wide real-time monitoring of multiple parameters, including voltage, current, temperature, and humidity. The constant flow of data contributes to the preservation of ideal operating circumstances. When combined with WSNs' powers to enable data-driven decision-making and real-time monitoring, these two technologies have the potential to revolutionize a wide range of applications. This paper offers a thorough examination of the significance of this synergy, including topics like environmental effect mitigation, grid resilience, and energy sustainability. In addition, the study analyzes the complex issues related to energy management, communication protocols, security, scalability, and integration with intermittent renewable sources that arise when synchronizing microgrids with WSNs. Future directions and new trends are also examined, including the growth of Internet of Things and AI-driven energy optimization. This study intends to assist academics, policymakers, and practitioners in realizing the full potential of microgrid implementations based on renewable energy for a more sustainable and interconnected future by illuminating the symbiotic link between microgrids and WSNs.
The Role of IoT and Artificial Intelligence in Advancing Nanotechnology: A Brief Review Islam, Md Monirul; Hossain, Ikram; Martin, Md. Hasnat Hanjala
Control Systems and Optimization Letters Vol 2, No 2 (2024)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v2i2.124

Abstract

The main objective of this research is to review the importance of IoT and Artificial Intelligence for Nanotechnology. Several industries are seeing notable breakthroughs due to the convergence of nanotechnology, artificial intelligence, and the Internet of Things. This succinct overview examines how IoT and AI are essential for improving the capabilities and uses of nanotechnology. Real-time monitoring, data gathering, and control at the nanoscale are made possible by IoT, improving the accuracy and efficiency of operations including industrial manufacturing, healthcare monitoring, and environmental sensing. The design, optimization, and predictive modeling of nanomaterials and systems are made easier by artificial intelligence (AI), which provides strong tools for evaluating the complicated data produced by nanoscale devices. The convergence of IoT, AI, and nanotechnology facilitates the creation of intelligent systems that possess the ability to monitor themselves and make decisions on their own. IoT and AI amplify the potential of nanotechnology by enabling real-time data collection, advanced data analytics, and autonomous decision-making, with vast applications across industries from healthcare to energy. Even while this integration seems promising, there are still issues to be resolved, such as privacy issues, data security, and technical difficulties in creating dependable nanoscale Internet of Things devices. It is anticipated that as research advances, the confluence of these technologies will transform industries including smart manufacturing, environmental monitoring, and medicine, making this a critical area for future innovation.
Comparative Analysis of Different Control Strategies and Materials for a Community Microgrid - A Case Study Pranto, Jubaer Akon; Kadir, Md Moin; Khan, Md. Yakub Ali
Control Systems and Optimization Letters Vol 2, No 2 (2024)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v2i2.118

Abstract

The main objective of this study is to conduct a comparative analysis of various control strategies and materials used in the operation of community microgrids. An analysis that contrasts various methods for managing a microgrid's operations in a community context is called comparison research on control strategies for community microgrids. The study's objectives are to evaluate the benefits and drawbacks of various control systems and to pinpoint the best approach for maximizing the microgrid's performance and materials for microgrid. The study compares various control strategies, including islanded mode control, hybrid mode control, and grid-connected mode control. Advanced strategies that integrate economic dispatch with optimal power flow are also evaluated. A comparison is done taking into account variables including resilience, cost-effectiveness, efficiency, stability, and reliability. The findings provide valuable insights into the optimal control approach tailored to the specific needs of community microgrids, considering available resources, local energy consumption patterns, and other critical factors. The report also emphasizes the advantages of employing sophisticated control systems, including enhanced resilience and flexibility, increased cost-effectiveness, and improved integration with the main grid. In general, the comparative analysis of different control strategies for community micro-grids offers insightful knowledge to scholars, engineers, and decision-makers engaged in micro-grid design and operation, assisting in enhancing the efficiency and dependability of these systems for the good of communities.
Impact of IoT and Embedded System on Semiconductor Industry A Case Study Tareq, Abdulla Al; Rana, Md Juel; Mostofa, Md Riad; Rahman, Md Sadiqur
Control Systems and Optimization Letters Vol 2, No 2 (2024)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v2i2.111

Abstract

The fast growth of Internet of Things (IoT) devices and advances in embedded systems are causing major changes in the semiconductor business. Examining major trends, obstacles, and opportunities, this case study investigates how embedded systems, and the Internet of Things are affecting the semiconductor business. It explores how semiconductor technology has developed to satisfy the needs of Internet of Things applications, focusing on connectivity options, low-power design, and sensor integration. The report examines how technological advancements, competitive tactics, and market dynamics are reshaping the semiconductor industry. Because IoT devices are frequently integrated into wearable technology or deployed in remote areas, power efficiency becomes essential. Using sophisticated low-power design approaches and power management features, semiconductors must be engineered to function with the least amount of power possible. Miniaturization of semiconductor technology is required due to the requirement for increasingly compact and smaller devices in embedded systems and the Internet of Things. The strategic implications for semiconductor businesses navigating this dynamic ecosystem are highlighted by drawing insights from industry data, market analysis, and case studies. Through an analysis of actual cases and market developments, this case study offers insightful insights into the changing role of semiconductor technology in facilitating the Internet of Things revolution.
Motion System of a Four-Wheeled Robot Using a PID Controller Based on MPU and Rotary Encoder Sensors Sagita, Muhamad Rian; Ma’arif, Alfian; Furizal, Furizal; Rekik, Chokri; Caesarendra, Wahyu; Majdoubi, Rania
Control Systems and Optimization Letters Vol 2, No 2 (2024)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v2i2.150

Abstract

This research addresses the challenge of developing an effective motion system for a four-wheeled omnidirectional robot configured with wheels at a 45-degree angle, allowing for holonomic movement—motion in any direction without changing orientation. In this system, inverse kinematics calculates each wheel's angular velocity to optimize movement. PID control is implemented to stabilize motor speeds, while odometry guides and determines the robot’s position using initial and target coordinates. The robot operates on a 12-volt power supply and two STM32F103C microcontrollers, utilizing an MPU6050 sensor to maintain orientation and optical rotary encoders for accurate positional tracking. Experimental results demonstrate that the robot achieves optimal motion on x and y axes with PID settings of kP = 0.8, kI = 1.0, and kD = 0.08. This configuration yields a rise time of 0.95 seconds, overshoot of 7.36%, and steady-state error of -0.5 RPM at a setpoint of 350 RPM. Using odometry, the robot successfully navigates various movement patterns with average position errors of 1.2% on the x-axis and 1.6% on the y-axis for rectangular patterns, 2.1% on the x-axis and 2.2% on the y-axis for zig-zag patterns, and 1.75% on the x-axis and 1.15% on the y-axis for triangular patterns. The MPU6050 sensor maintains orientation with an error of 0.65% in triangular patterns and 0.85% in rectangular patterns. Through inverse kinematics, PID control, and sensor integration, the robot reliably follows designated coordinate points.

Page 1 of 2 | Total Record : 15

 1   2 

Filter by Year

2024 2024


Reset
Filter By Issues
All Issue Vol 3, No 3 (2025) Vol 3, No 2 (2025) Vol 3, No 1 (2025) Vol 2, No 3 (2024) Vol 2, No 2 (2024) Vol 2, No 1 (2024) Vol 1, No 3 (2023) Vol 1, No 2 (2023) Vol 1, No 1 (2023)