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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 118 Documents
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Wood Type Identification System using Naive Bayes Classification Muhammad Anas Yulianto; Abdul Fadlil
Control Systems and Optimization Letters Vol 1, No 3 (2023)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v1i3.52

Abstract

Wood, a forest product and natural resource, is a raw material used to make household goods. Some types of wood have almost the same pattern or structure. Wood quality varies greatly depending on the tree species and the environmental conditions in which it grows. This makes it challenging to identify the type of wood, especially for wooden furniture users. Therefore, wood classification is essential to ensure that the wood used meets the required quality standards and requirements. Automatic classification of wood using image processing has several advantages and can make it easier for humans. One of the image processing methods for wood classification is the Naïve Bayes method. Feature extraction technique using GLCM using contrast, correlation, energy, and homogeneity attributes. The GLCM methods can be combined to create a system design to distinguish five wood species using an image-based wood type identification system. The study results have successfully designed a system to determine five types of wood using the framework of an image-based wood type identification system. An application system has been produced to distinguish five types of wood using the framework of an image-based wood type identification system with the GLCM feature extraction method and the Naive Bayes classification method. The application system successfully identified wood species with a test accuracy rate of 88%.
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.
Hexapod Robot Movement Control for Uneven Terrain Yusuf Prasetio; Nuryono Satya Widodo
Control Systems and Optimization Letters Vol 1, No 2 (2023)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v1i2.23

Abstract

Hexapod robot is a robot that has 6 legs with joints or structures that resemble insect legs. This study uses the inverse kinematic method with the aim of finding points and effectors of the robot's legs that will make the robot's legs pass through uneven obstacles such as uneven flor, stairs, bolong-bolong obstacles, bolong-non-obvious obstacles and non-objective obstacles. This inverse kinematic is accessed with the Open Cm 9.04 microcontroller to control the dynamixel servo on the robot leg. The results of testing the robot's movement using inverse kinematics have succeeded in overcoming uneven obstacles using the inverse kinematic method. For testing the stability of the robot it is still not stable enough because the mechanical part of the foot is still not precise. The conclusion of the study, from 6 trials that average and uneven obstacles were obtained in the range of 85% - 95%. The inverse kinematic method using a proximity sensor on the front of the robot, the average success that can be obtained is in the range of 80% - 90%.
An Overview of the Growth of Bangladesh's Renewable Energy Sector, Outlining Current Challenges and Future Prospects Aman Ullah; Md. Naeem Hussain; Firoj Ahamad; Saifullah Saifullah; Fahim Al Mahmud Roman
Control Systems and Optimization Letters Vol 2, No 1 (2024)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v2i1.67

Abstract

The main objective of this review is to develop renewable energy (RE) sectors and overcome any obstacles regarding this in Bangladesh. Bangladesh has been facing energy crisis in all sectors in need of electricity. The techno-economical and policy making challenges are the main barrier of renewable energy sources installment in Bangladesh. But in recent years, Bangladesh has achieved notable progress in the development of its renewable energy industry. Bangladesh produces 723.26 MW of electricity from renewable sources, which include 67.61% solar, 31.80% hydro, and 0.58% wind, biogas, and biomass. Of these, 489 MW are produced by more than 6 million (63, 25, 278) installed solar cells. This assessment offers a thorough examination of the nation's present renewable energy situation, stressing both the fundamental difficulties and noteworthy successes. The research reviews the many renewable energy sources, such as hydropower, biomass, mechanical vibration, wind, and solar electricity, and assesses how much of each the country needs to use. Analyzing the legal and policy environment that governs renewable energy in Bangladesh, the research highlights the necessity of focused measures to remove current obstacles. It talks about how overcoming obstacles and promoting sustainable growth can be accomplished through international cooperation and financial assistance. The research also looks at the socioeconomic effects of renewable energy programs, considering how they may affect employment and electrification in rural areas. The analysis provides an outlook on the prospects of the renewable energy sector in Bangladesh. Emerging technologies, possible market trends, and innovative prospects are covered. To assist stakeholders, investors, and legislators in navigating the shift to a more resilient and sustainable energy future, recommendations are offered. With an emphasis on highlighting successes and outlining challenges, this research provides a thorough analysis of Bangladesh's renewable energy industry. Bangladesh may establish itself as a regional leader in the adoption of renewable energy sources and support international efforts to mitigate climate change by recognizing the obstacles of the present and laying out a plan for future development. This research will help to the researchers and policymakers for making more renewable energy in Bangladesh without facing any difficulties.
DC Motor Rotary Speed Control with Arduino UNO Based PID Control Rikwan Rikwan; Alfian Ma'arif
Control Systems and Optimization Letters Vol 1, No 1 (2023)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v1i1.6

Abstract

Along with the development of the times, DC motors are often used in industrial equipment or household appliances, but in DC motors they often experience a decrease due to the given load, it requires a controller. This research uses PID (Proportional Derivative) controller. In this study, the DC motor can be controlled despite the load using the trial and error method. This study uses Arduino UNO software for testing using parameters Kp=1.5, Ki=0.87, Kd=0.27. parameter y is the parameter value Kp, Ki, Kd obtained from the system response according to the software used. the value of rise time = 0.9925 Tested, Time = 2.7368, Overshoot = 1.3333 and Steady State Error = 0
A Comprehensive Review of Integrated Energy Management for Future Smart Energy System Md Shopan Ali; Anik Sharma; Tamal Ahammed Joy; Md Abdul Halim
Control Systems and Optimization Letters Vol 2, No 1 (2024)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v2i1.77

Abstract

The main objective of this paper is to review the integration of energy management for future smart energy systems. The authors hope to address the developing landscape of energy management in the context of new smart energy systems in this review. The paper conducts a thorough review of integrated energy management methodologies that maximize energy generation, consumption, and distribution within these systems. The study assesses the multifarious solutions that enable effective and sustainable energy consumption by considering many components such as renewable energy sources, storage technologies, demand-side management, and grid interactions. The authors present insights into the problems and opportunities inherent in realizing the potential of future smart energy systems through an in-depth assessment of recent research, case studies, and advances in energy management. The assessment focuses on the inherent problems and opportunities associated with pursuing integrated energy management in smart energy systems. The application of cutting-edge sensing, communication, and control technologies to electrical grids has been studied to increase resilience, efficiency, and dependability. Real-time monitoring, analysis, and optimization of energy flows are made possible by the integration of cutting-edge sensors, communication systems, and control algorithms into electrical grids. Variable renewable energy sources, such solar PV and wind power, may now be seamlessly integrated into the grid thanks to advancements in renewable energy integration technologies. Case studies have shown how smart grid technologies can optimize energy management and save system costs. Integrating various DERs into grid operations has been the main focus of advancements in energy management. The paper navigates through the intricate considerations that stakeholders must make to maintain the resilience and sustainability of future energy systems, from dealing with the intermittent nature of renewable sources to maximizing energy dispatch mechanisms. The study reveals the revolutionary potential of a holistic approach to energy management by studying the changing role of digital technologies, data analytics, and predictive algorithms. Finally, this review contributes to a better knowledge of integrated energy management techniques, opening the path for a more robust, responsive, and environmentally friendly energy landscape.
Control of Water Flow Rate in a Tank Using the Integral State Feedback Based on Arduino Uno Hendriyanto, Raeyvaldo Dwi; Puriyanto, Riky Dwi; Ma'arif, Alfian; Vera, Marco Antonio Márquez; Nugroho, Oskar Ika Adi; Chivon, Choeung
Control Systems and Optimization Letters Vol 2, No 3 (2024)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v2i3.162

Abstract

In the industrial world, many tools have been made to facilitate human work in carrying out control and measurement that is made automatically in a production process. Because in some parts of a production process in the industry that is done manually is no longer effective so that accurate and precise automatic control is needed. The control that will be used in this study is the Integral State Feedback (ISF) control with Arduino Uno as a microcontroller to design and run the system. The actuator used is a 12V water pump with the sensor used is the YF-S401. The system will run the ISF control as long as the data is less than 300 and if it reaches 300 data, the system will stop processing the ISF control and turn off the 12V water pump. The sensor reading error obtained is 27%. Parameters Ki = 0.3, K1 = 6, and K2 = 2 obtained from MATLAB Simulink can be applied to the research tool but have a slow system response Delay Time and Rise Time, so the researcher made a modification parameter with a value of Ki = 1, K1 = 6, and K2 = 2 and obtained a faster system response Delay Time and Rise Time. So it can be concluded that the best parameters for this study use modified parameters.
Control of Leading-Edge Shock of Train Using Deep Neural Network to Prevent Unstart Acha, Stefalo; Yi, Sun; Ferguson, Frederick
Control Systems and Optimization Letters Vol 2, No 3 (2024)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v2i3.160

Abstract

The primary aim of this research is to create a comprehensive neural network model that can effectively regulate the position of the leading-edge shock in a scramjet by manipulating the required backpressure, thereby achieving, and maintaining hypersonic speeds. By utilizing computational fluid dynamic data, a dynamic model is constructed using a neural network-based approach to control the positions of the leading-edge shock train. The scramjet isolator, which is a duct where pressure increases from the inlet to the combustor via a series of shock waves, necessitates precise control of the leading-edge shock locations during scramjet operation. The model employed in this research project is a neural network adaptive controller implemented in MATLAB/Simulink software, which accounts for the nonlinear characteristics of the plant and predicts its future behavior. To enhance control performance, a robust controller is employed, integrating a learning rule that reduces the error percentage throughout the system's lifespan. The neural network is trained using flight behavior datasets, enabling it to learn from a set of training patterns. Plant identification is achieved through a neural network, capturing the system dynamics, and enabling the neural network to function as a controller. Additionally, the controller's performance is validated through simulations and optimization analyses. This research presents an adaptable, robust, and effective control system that provides added reliability and reduces disturbances.
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.
Genetic Algorithm-Optimized LQR for Enhanced Stability in Self-Balancing Wheelchair Systems Chotikunnan, Phichitphon; Khotakham, Wanida; Wongkamhang, Anantasak; Nirapai, Anuchit; Imura, Pariwat; Roongpraser, Kittipan; Chotikunnan, Rawiphon; Thongpance, Nuntachai
Control Systems and Optimization Letters Vol 2, No 3 (2024)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v2i3.161

Abstract

Balancing systems, exemplified by electric wheelchairs, require accurate and effective functioning to maintain equilibrium across many situations. This research looks at how well a standard linear quadratic regulator (LQR) and its genetic algorithm (GA)-optimized version keep an electric wheelchair stable when it stands on its own. The aim of the optimization was to improve energy economy, robustness, and responsiveness through the refinement of control settings. Simulations were performed under two scenarios: stabilizing the system from a tilt and recovering from an external force. Both controllers stabilized the system; however, the GA-optimized LQR demonstrated considerable improvements in control efficiency, decreased stabilization time, and enhanced response fluidity. It exhibited improved resilience to external disturbances, as indicated by a decrease in oscillations and an increase in fluid displacement recovery. These enhancements highlight the LQR's versatility, resilience, and appropriateness for real-world applications, including Segways, balancing robots, and patient wheelchairs. This study highlights the ability of evolutionary algorithms to enhance the effectiveness of traditional control systems in dynamic and unpredictable settings.

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