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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 124 Documents
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A Review on Techno-Economic Perspective of a Smart Grid and its Challenges Rana, Md Juel; Tareq, Abdulla al; Hasan, Md Mehedi; Aziz, Tareq; Neidhe, Md Mushfiqur Rahman
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.v2i1.83

Abstract

This study undertakes a thorough analysis of the techno-economic perspective related to smart grids. It investigates how to improve sustainability and efficiency in power systems by integrating cutting-edge technology. Important elements included in the evaluation include distribution automation, improved metering infrastructure, communication technologies, and the incorporation of renewable energy sources. Examined are the financial effects of implementing smart grids, including cost-benefit analysis, operational effectiveness, and consumer empowerment. The study also lists and analyzes barriers to broad adoption, such as legislative frameworks, cybersecurity threats, and interoperability problems. The study discusses each of these issues in detail, providing insights into the underlying difficulties and possible solutions. It underlines how crucial it is for stakeholders to work together, invest in cutting-edge technology, and change regulations in order to get beyond these challenges and create an energy ecosystem that is more intelligent, effective, and sustainable.
Load Frequency Control of One and Two Areas Power System Using Grasshopper Optimization Based Fractional Order PID Controller Mohammed, A. S.; Dodo, A.
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.v1i1.12

Abstract

In this paper, grasshopper optimization based fractional order PID controller for load frequency control of single and multi-area power system is presented. It is paramount to minimize large frequency deviation in power system control. Large frequency deviation occurs when the parameter values of the various generating units of the power system like generators, turbine and governors keeps changing due to numerous on/off witching in the load side. As such, for a more realistic study, nonlinearities and boiler dynamics has been introduced into the power system design and measures also put in place to mitigate large frequency deviation. This is because large frequency deviation can damage equipment at the generation level and the consumer devices at the distribution level. Anti-windup control will then be used to compensate the effects of the nonlinearities. The gain of the FOPID controller will be optimized using grasshopper optimization algorithm and objective function for minimization is the Integral Square Error (ISE). The Errors to be minimized are the summation of frequency deviation, tie-line power deviation and the area control errors. Simulations were carried out on the designed power system using MATLAB/Simulink and results obtained show a significant improvement in mitigating frequency deviation. However, the proposed method took a longer time to balance the generated power and load demand. This is because the proposed method considers boiler dynamics and nonlinearities in the power system designed and results were compared with other designed method for power system without nonlinearities.
A Review on Attacks against Artificial Intelligence (AI) and Their Defence Image Recognition and Generation Machine Learning, Artificial Intelligence Hossain, Md. Tarek; Afrin, Rumi; Biswas, Mohd. Al- Amin
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.v2i1.73

Abstract

The main objective this paper is to review the adversarial assaults, data poisoning, model inversion attacks, and other methods that potentially jeopardize the integrity and dependability of AI-based image recognition and generation models. As artificial intelligence (AI) systems become more popular in numerous sectors, their vulnerability to attacks has arisen as a major worry. We focus on attacks especially targeting AI models used in picture identification and creation tasks in our review study. We investigate the wide range of assault strategies, including both traditional and more complex techniques. These attacks take use of flaws in machine learning algorithms, frequently resulting in misclassification, falsified picture production, or unauthorized access to sensitive data. We survey numerous defense strategies developed by scholars and practitioners to overcome these difficulties. Among these defenses are adversarial training, robust feature extraction, input sanitization, and model distillation. We explore the usefulness and limitations of each protection mechanism, highlighting the importance of a comprehensive approach that integrates numerous techniques to improve the resilience of AI models. Furthermore, we investigate the possible impact of these attacks on real-world applications such as driverless vehicles, medical imaging systems, and security monitoring, emphasizing the threats to public safety and privacy. The study also covers the legislative and ethical aspects surrounding AI security, as well as the responsibilities of AI developers in establishing adequate defense measures. This analysis highlights the critical need for continued research and collaboration to develop more secure AI systems that can withstand sophisticated attacks. As AI evolves and integrates into important areas, a concerted effort must be made to strengthen these systems' resilience against hostile threats and assure their responsible deployment for the benefit of society.
Design and Implementation of Arduino-Based Sterilization Robot Khalaf, Omar Raad; Almukhtar, Aya A.
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.v1i3.62

Abstract

In this paper, the primary objective is to design implement a low-cost mobile robot used for the sterilization and control of toxic and flammable gas leaks in the polluted areas. To implement the proposed robot, we employ a tank robot structure equipped with sensors/modules for detection, sterilization, and environmental analysis. The robot is outfitted with a camera to enhance its surveillance capabilities. For sterilization, we utilize ultraviolet rays emitted by a UV Lamp (220V Sterilizer 8W-T5 Tube) in infested areas. Special sensors are strategically placed to identify gases and viruses in the target locations. The sensors include MQ-2 for detecting gases like methane, butane, and smoke, MQ-9 for identifying carbon monoxide and flammable gases, and MQ-135 for continuous measurement of air purity. The UV rays can be remotely activated and deactivated through an infrared control system. Simultaneously, the sensor values (MQ-2, MQ-9, MQ-135) are consistently monitored and transmitted to a central authority responsible for remote surveillance. If any hazardous or toxic gases are detected, the system triggers an alarm, notifying relevant authorities to take prompt action. This integrated approach ensures the efficient sterilization of contaminated areas while actively monitoring and responding to potential gas leaks. The combination of sterilization technology, gas detection sensors, and remote monitoring enhances the safety and effectiveness of the entire system. In the future developments, many approaches can be used such as increasing the controlling area by using Wi-Fi or LoRa and using additional sensors for harmful gas detection.
Room Temperature and Humidity Control System Using Arduino and Blynk Purnomo, Beni; Sunardi, Sunardi
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.v1i2.46

Abstract

The temperature and humidity of a room can be a problem that affects the comfort and health of its occupants. Issues such as excessively high or low temperatures and humidity levels can make it difficult for people to sleep and cause discomfort. Various solutions can be implemented, such as using IoT-based temperature and humidity monitoring systems, platform Blynk to optimize temperature and humidity control, and designing control circuits using actuators such as fans with relays. This control system uses the Blynk application to monitor and turn on and off the actuators in this study using a fan. Arduino Wemos D1 as the main processor, and for sensors, DHT22. Test method by placing the system in a room with an area of 3 x 3 m. The results of the test with the fastest average time were in the morning with a time of 10 minutes, 52 seconds. The longest average time was obtained during the day, with a test time of 14 minutes, 38 seconds. The difference in error between the system and the comparison is the highest at a temperature of 2.71% and at a humidity of 33.5%.
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.
Design a Condition Monitoring System for Rotating Machinery Gearboxes by Oil Quality Measurements and Vibration Analyses Gohari, Mohammad; Tahmasebi, Mona; Ghorbani, Mahdi
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.v1i1.18

Abstract

Every year high costs are expending to repair rotating machinery in factories and industrial centers due to failures. Most failures happen suddenly while by condition monitoring of systems prognosis and diagnosis are possible. By condition monitoring, the failures can be detected and solved in the early stages. Gearboxes are an element used widely, and applying condition monitoring for them makes a significant benefit for saving budget due to prognosis and removing failure before progress. The current paper aims to present a condition monitoring system for gearbox which is able to inspect lubricant by oil temperature and pH. Moreover, it can detect some defects in the gearbox by vibration analyses such as unbalance, bent shaft, looseness in bearing housing, and whirl of oil. The evaluation of the system shows that its accuracy is proper for use in gearboxes.
Book Review on Antonio Moreno-Munoz; Neomar Giacomini; Energy Smart Appliances: Applications, Methodologies, and Challenges (2023)‏ Mousa, Hossam H. H.; Mahmoud, Karar; Lehtonen, Matti
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.v2i1.84

Abstract

Recently, the integration of new industrial technologies is significantly increased into the utility grid such as renewable energy sources (RESs), distributed energy resources (DERs), energy source systems (ESSs), electric vehicles (EVs), and multi-carrier energy systems (MESs). So, robust energy management strategies are required to regulate the power-exchange between the generations and end-users for improving the power system's reliability and stability and reducing the energy costs. Thus, the demand-side management (DSM) strategies and demand response (DR) programs are utilized to control the energy smart appliances for residential building which achieving by various strategies, required infrastructure, energy market signals, etc. Several textbooks and articles investigate this important topic. However, the book entitled “Antonio Moreno-Munoz; Neomar Giacomini; Energy Smart Appliances: Applications, Methodologies, and Challenges (2023)”, is the most recent prominent comprehensive reference for DSM strategies in smart grids. Hence, this article proposes a book review and discussion of its most important contributions to DSM strategies by dividing them into four main contributions. Which helps the reader in realizing the recent developments on DSM strategies based on this book’s contents.
DC Motor Controller Using Full State Feedback Setiawan, Naufal Rahmat; Ma'arif, Alfian; Widodo, Nuryono Satya
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.v1i1.3

Abstract

This paper discusses the implementation of a full state feedback control system on DC motors to stabilize the speed of DC motors and fight the disturbances given to DC motors. Modern controls such as full state feedback use 2 sensor inputs, namely the Hall effect speed sensor OH42E and the INA219 current sensor and use 3 parameters namely K1 (Constant 1), K2 (Constant 2), and KI (Integral Constant) in designing the controller, the goal is to get a good system response according to the desired design specifications. The test was carried out with a hardware-in-the-Loop (HIL) scheme which uses an Arduino microcontroller as a DC motor plant control device in the form of a control mathematical model entered in the Arduino IDE software and by trial and error to find the desired response value. The test results showed that at the values of K1=1, K2=1, KI=0.9, a stable system response was obtained with tr(s)=3, ts(s)=4, and Os(%)=7% The addition of an integral constant () value affects a short rising time but is inversely proportional to a high overshoot value as well. Varying the values of K1 and K2 as multipliers on the sensor values has an impact on the stability of the system response or oscillations. The stability of this system response indicates that full state feedback can be relied upon as a control system.
Comprehensive Overview of Optimization Techniques in Machine Learning Training Karthick, K.
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.v2i1.69

Abstract

This article offers a comprehensive overview of optimization techniques employed in training machine learning (ML) models. Machine learning, a subset of artificial intelligence, employs statistical methods to enable systems to learn and improve from experience without explicit programming. The paper delineates the significance of optimization in ML, emphasizing its role in adjusting model parameters to minimize loss functions, thereby ensuring efficient model training and improved generalization. The discussion encompasses various optimization methods, including Gradient Descent Variants, Adaptive Learning Rate Methods, Second-Order Optimization Methods, Regularization Methods, Constraint-based Methods, and Bayesian Optimization. Each section elucidates the principles, applications, and benefits of these techniques, highlighting their relevance in addressing challenges such as overfitting, scalability, and computational efficiency. The article aims to guide researchers, practitioners, and enthusiasts in navigating the complex landscape of optimization techniques tailored for diverse machine learning algorithms and applications.

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