Association for Scientic Computing Electronics and Engineering (ASCEE): Open Journal Systems
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Power Regulation of a Three-Phase L-Filtered Grid-Connected Inverter Considering Uncertain Grid Impedance Using Robust Control
Full text linkUncertain grid impedance is often common in power distribution networks; therefore, it is crucial to design an efficient controller in this situation. Â An issue that frequently occurs is the problem of unpredictable grid impedance, which can cause voltage fluctuations, power quality problems, and potential damage to equipment. This work provides a systematic control strategy to tackle these issues by supplying well-regulated power from a DC source to an AC power grid. A linear matrix inequality (LMI)-based robust optimal control is proposed in this paper to provide stability to the inverter system without offset error at the output side. The convergence time to steady state is minimized by solving the LMI problem to maximize the eigen value of the closed-loop system with the inclusion of the uncertainty of the filter parameter and grid impedance. Furthermore, the uncertainties in this study include the potential variation of values for the filters and the grid's impedance. These uncertainties occur because the grid impedance can fluctuate fast in the event of a fault or termination of a transmission line, while the filter's impedance can also be affected by changes in operating temperature. The simulation study of this proposed control includes a comparison between wide and narrow uncertainty ranges, as well as a performance comparison under uncertain parameters. Furthermore, this approach exhibits a lower power ripple in comparison to existing PI control method
Optimization Combining with Digital Transformation of the Men's Shirts Processing at Small and Medium-Sized Garment Enterprises in Vietnam
Full text linkIndustry 4.0 has become a hype among the manufacturing industries across the globe. Recent developments require significant capital investments, but these technologies are yet to be established in developing countries such as Vietnam, especially the apparel industry.  Based on a survey of the current situation at small and medium-sized enterprises in Vietnam's textile industry, the paper proposes to apply technology, test and evaluate the effectiveness of applying and coordinating digital systems in management and chain supply. Multifaceted applications have been specifically explored including automatic equipment and digital systems, spanning the domains of automation, robotics, artificial intelligence, data analytics, and the Internet of Things (IoT). These technologies are posited as catalysts for transformative improvements in production efficiency and resource utilization. Furthermore, experimental results point out the symbiotic relationship between technology adoption and effective management strategies to achieve holistic operational enhancements. As the Vietnamese textile industry strives for competitive excellence in the global arena, this research offers actionable insights for industry practitioners, policymakers, and researchers
Design and Manufacturing Using 3D Printing Technology of A 5-DOF Manipulator for Industrial Tasks
Full text linkRobotic manipulators have become very necessary in industrial applications all over the world. In this paper, a 5-DOF robotic manipulator is designed and manufactured to simulate a real industrial task. The manipulator is intended to transfer an object with a weight of 30 grams from a known place to another known one, which is a pick and place task. Firstly, all parts of the manipulator are designed using SolidWorks software. During the design, all parts’ dimensions are considered. The end-effector of the manipulator is designed based on gear system. Secondly, 3D printing technology is used to manufacture these designed parts. The manufacturing process is very accurate and efficient. Servo motors are considered to do the motion of the manipulator, which are easily and directly connected to the control circuit. As, 5-DOF manipulator is manufactured, five servo motors are used: one motor for every joint. The motion of the motors is controlled by Arduino Uno unit which is a cheap and easy programming unit. Experiments are executed with the developed robot to show its effectiveness and success by preparing three boxes which the robot effectively transfers from one place to another. Eventually, the challenges during the design and manufacturing of this robot are mentioned in this paper.Â
Impact of Foaming Agent: Water Ratio on Foam Stability of Lightweight Concrete
Full text linkFoamed concrete, renowned for its lightweight nature and thermal insulating properties, has gained substantial interest in the construction industry. The stability of foamed concrete is directly related to the stability of preformed foam used for making foamed concrete. Foam stability is the prime factor which influences the overall performance and properties of the foamed concrete. Foam stability refers to the ability of the foam to maintain its structure and volume over time. The stability of foamed concrete is greatly impacted by the selection of the foaming agent and the ratio of foaming agent to water (FA/W). Protein based foaming agent (as per ASTM C796/C796M-19) has been used for this study. An excess of water can weaken the foam structure, leading to instability, while inadequate water can lead to issues such as reduced workability and uneven distribution of foam within the mixture. This paper investigates the effect of FA:W ratio on the stability of foam concrete. Three different FA:W ratio i.e. 1:10, 1:20 and 1:30 has been used for this study. Respective slumps to these ratios have also been investigated at different time intervals to check their consistencies. Three mix proportions were used to produce foam concrete of 1000kg/m3 density. Impact of aforementioned FA/W ratios on the properties of foamed concrete (As per; IS 2185 part-4) were discussed in this article
Digital literacy of Heart Communication for reducing bullying model
Full text linkOne of the most worrying forms of juvenile delinquency is bullying. Heart communication integrated with digital literacy is a solution to overcome bullying. This study aims to analyze the effect of heart communication digital literacy on reducing bullying behavior in 30 Senior High Schools and Vocational High Schools (Jogja Smart School) in the Special Region of Yogyakarta and to find a Heart Communication Digital Literacy model to reduce bullying. The theories used are Heart Communication Theory, Digital Literacy Theory, and Cognitive Theory. This study uses mixed methods sequential explanatory, which begins with quantitative methods and then qualitative methods. Quantitative methods with surveys on a sample of 400 students as research subjects. Quantitative data analysis techniques use regression analysis. Qualitative methods include interviews and FGD techniques, and data analysis is done using the Miles and Huberman method. The results of quantitative research show that the heart communication digital literacy variable with the dimensions “Tahu Komunikasi Hati,†“Tanggap Komunikasi Hati,†and “Tangguh Komunikasi Hati†has a significant contribution to reducing bullying behavior, with an R Square value of 28%. This study concludes that the Heart Communication Theory has been proven to reduce bullying in Jogja Smart School Senior High School and Vocational High School students in the Special Region of Yogyakarta. The results of qualitative research found a novelty in the form of a digital literacy of heart communication to reduce bullying model
Sensorless Speed Estimation Basing on MRAS Model for a PMSM Machine Application
Full text linkWind energy systems utilizing synchronous machines can encounter challenges with speed detection at high rotational speeds due to increasing motor temperatures affecting parameters like stator resistance. This paper addresses these challenges by proposing a novel high-speed estimator algorithm based on the Model Reference Adaptive System (MRAS) approach. The primary contribution of this research is the development of an MRAS-based speed estimator that leverages a reactive power model to maintain robustness against variations in stator resistance, even at elevated speeds. To optimize the estimator’s performance, we employed a particle optimization algorithm for tuning, which overcomes issues related to regulator parameter identification. We implemented the proposed algorithm in Matlab and validated it on a real machine prototype capable of high-speed operation. After a comparison wth 5 different methods, the results indicate that the estimator performs effectively up to 42,000 RPM (600 Hz), demonstrating a maximum speed estimation error of 50 Hz. Stability analyses across various speed regions and practical lab tests confirm the robustness and accuracy of the proposed control scheme. The findings highlight the estimator’s improved performance in high-speed scenarios, showcasing its potential for enhancing speed detection in wind energy systems
Hybrid PI-MPC Control System for a Four-Phase Interleaved Boost Converter: Performance Evaluation in Reducing Current Ripple in Electric Car Battery Charging
Full text linkElectric car batteries face two primary challenges: the substantial number of batteries used, leading to increased weight and costs, and the limited battery lifespan, which results in high maintenance expenses. To address these issues, a power supply with high voltage gain and optimal efficiency is essential. Currently, switching mode power supplies are preferred due to their superior efficiency over linear systems. Among these, DC-DC boost converters are key components. However, conventional boost converters face limitations such as restricted voltage gain and significant current ripple, which negatively affect battery performance and system efficiency. This study aims to design a hybrid control system for a four-phase interleaved boost converter, integrating Model Predictive Control (MPC) with Proportional-Integral (PI) control. The hybrid control system dynamically adjusts the PI controller's setpoint based on real-time input variations, enhancing the system’s responsiveness and stability under fluctuating load and voltage conditions. The experimental setup includes a four-phase interleaved boost converter with split inductance and capacitance bypass techniques to mitigate ripple effects. Our hypothesis posits that the hybrid PI-MPC control system will reduce current ripple and improve system performance in electric vehicle battery applications. Results show a significant reduction in input current ripple (0.0014%) and output current ripple (0.042%), indicating improved performance compared to conventional converters. Despite these improvements, the study acknowledges limitations related to the scalability of the proposed system and potential challenges in integrating this topology into larger systems. Further investigation is required to assess its long-term performance and economic feasibility in diverse EV applications
Antecedent of consumer purchase decisions on pegipegi.com
Full text linkTechnology advances have created a map of competition in the Online Travel Agent (OTA) service provider industry in Indonesia. Pegipegi.com as an online service provider is one of the competitors whose sales fluctuate from year to year. In this study used 97 respondents with data analysis using Smart PLS 3.0. examination the research conducted revealed that brand trust had a significant positive impact on purchasing decisions, then experiential marketing also had a significant positive impact on purchasing decisions and so does e-promotion variables which had a significant positive effect on purchases decisions
Impact of Smart Greenhouse Using IoT for Enhanced Quality of Plant Growth
Full text linkGreenhouses play a crucial role in manipulating environmental conditions for optimal plant growth. While existing greenhouses enhance control over environmental factors, manual controls such as watering and humidity regulation often lead to suboptimal production and increased costs. This study proposes the development of a smart greenhouse with an automatic control system using fuzzy logic, specifically fuzzy Sugeno, to regulate watering and lighting based on soil moisture, temperature, and light intensity. The system's architecture involves sensor inputs, microcontroller processing, and the activation of actuators, such as UV lights and water pumps. Fuzzy logic is applied to interpret soil moisture and temperature inputs and determine optimal irrigation durations. The system's functionality is tested and validated through functional testing, Blynk application testing, and fuzzy Sugeno testing. Results indicate the successful implementation of the proposed smart greenhouse system. Functional testing demonstrates accurate sensor readings, including temperature and soil moisture. The Blynk application enables real-time monitoring and control of environmental conditions. Fuzzy Sugeno testing validates the irrigation control system, with an average error rate of 1.3%, affirming the system's alignment with desired specifications. Plant testing in different conditions showcases the effectiveness of the smart greenhouse in supporting plant growth and development
Selection and Evaluation of Robotic Arm based Conveyor Belts (RACBs) Motions: NARMA(L2)-FO(ANFIS)PD-I based Jaya Optimization Algorithm
Full text linkScholars worldwide have shown considerable interest in the industrial sector, mainly due to its abundant resources, which have facilitated the adoption of conveyor belt technologies like Robotic Arm-Based Conveyor Belts (RACBs). RACBs rely on four primary movements: (i.e., joint, motor, gear, and sensor), which can have a significant impact on the overall motions and motion estimation. To optimize these operations, an assistive algorithm has been developed to enhance the effectiveness of motion by achieving favorable gains. However, each motion requires specific criteria for Fractional Order Proportional Integral Derivative (FOPID) controller gains, leading to various challenges. These challenges include the existence of multiple evaluation and selection criteria, the significance of these criteria for each motion, the trade-off between criterion performance for each motion, and determining critical values for the criteria. As a result, the evaluation and selection of the Proposed Jaya optimization algorithm for RACB motion control becomes a complex problem. To address these challenges, this study proposes a novel integrated approach for selecting the Jaya optimization algorithm in different RACB motions. The approach incorporates two evaluation methods: the Nonlinear Autoregressive Moving Average with exogenous inputs (NARMA-L2) controller for Neural Network (NN) weighting of the criteria, and the Adaptive Neuro-Fuzzy Inference System (ANFIS) for selecting the Jaya optimization algorithm. The approach consists of three main phases: RACB-based NARMA-L2 Controller Identification and Pre-processing, Development of NARMA-L2 controller-based NARMA(L2)-FO(ANFIS)PD-I, and Evaluation of FOPID criteria based on JOA. The proposed approach is evaluated based on NARMA(L2)-FO(ANFIS)PD-I that given 0.4074, 0.3156, 0.3724, 0.1898 and 0.2135 for K_p_joint, K_i_motor, K_d_sensor, λ_gear, and µ_N respectively, which verifies the soundness of the proposed methodology