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28,188 Article Results

A model predictive control strategy for enhance performance of totem-pole PFC rectifier

10.11591/ijpeds.v16.i3.pp1687-1700
Le Chau Duy , Nguyen Dinh Tuyen
This paper proposed a simple but effective finite control set-based model predictive control (FCS-MPC) method to control a totem-pole bridgeless boost PFC rectifier (TBBR). The control algorithm selects from the possible switching states an appropriate one that fulfills a predefined cost function. This method also successfully eliminates the zero-crossing current distortion so that the grid current can synchronize well with the grid voltage. The theoretical analysis was presented and verified by simulation. Finally, a 3.3 kW/400 Vdc prototype was fabricated and investigated through various working conditions to realize the effectiveness of the proposed control strategy. Both simulation and experimental results show that the proposed control method can ensure accurate control of DC link output voltage and sinusoidal input current with unity power factor.
Volume: 16
Issue: 3
Page: 1687-1700
Publish at: 2025-09-01

Smart energy management in renewable microgrids: integrating IoT with TSK-fuzzy logic controllers

10.11591/ijpeds.v16.i3.pp1620-1627
Moazzam Haidari , Vivek Kumar
Hybrid microgrids powered by renewable energy sources are gaining popularity globally. Photovoltaic (PV) and permanent magnet synchronous generator (PMSG)-based wind energy systems are widely used due to their ease of installation. However, wind and solar energy are unpredictable, leading to fluctuating power generation. Simultaneously, load demand varies randomly, making it necessary to integrate storage devices to maintain a balance between generation and consumption. To enhance system economy, a small battery is combined with a hydrogen-based fuel cell and electrolyzer for efficient energy storage and management. A robust energy management system (EMS) is critical to ensure power quality and reliability across all microgrid components. Maximum power point trackers (MPPTs) are employed to maximize renewable energy utilization. Frequency stability and ensuring power balance is important in autonomous microgrids, especially during rapid load or source variations. This paper presents a novel fuzzy rule-driven Takagi-Sugeno-Kang (TSK) controller for the EMS, ensuring fast, precise responses and improved microgrid reliability.
Volume: 16
Issue: 3
Page: 1620-1627
Publish at: 2025-09-01

Comparative reliability and performance analysis of PV inverters with bifacial and monofacial panels

10.11591/ijpeds.v16.i3.pp1970-1982
Muneeshwar Ramavath , Rama Krishna Puvvula Venkata
In the realm of solar energy systems, the reliability and performance of photovoltaic (PV) inverters play a critical role in ensuring efficient energy conversion and long-term operation. This study delves into a comprehensive reliability-oriented performance assessment of PV inverters, with a particular focus on the comparative analysis between bifacial and monofacial panels. Reliability evaluation is carried out by considering a yearly mission profile with a one-minute sample at Hyderabad, India. A test case of a 3-kW PV system for grid-connected applications is considered. By integrating reliability metrics with performance indicators, we aim to provide a holistic evaluation of PV inverters operating under varying conditions inherent to both panel types. The research methodology involves detailed simulations and field data analysis to capture the nuances of inverter performance influenced by the unique characteristics of bifacial panels, such as their ability to capture light from both sides, compared to the traditional monofacial panels. In this paper, performance parameters such as junction temperature, MCS, and B10 lifetime (system level (SL) and component level (CL)) are evaluated. Key findings highlight the impact of these differences on inverter reliability. The Bi-PV panel exhibits a decreasing trend. In India, CL reliability (B10) is decreased from 34 years to 1.5 years, and SL reliability (B10) is decreased from 24 years to 1 year. In comparison with monofacial panels, the thermal stress on the PV inverter due to the bifacial panel is increased, and reliability is decreased.
Volume: 16
Issue: 3
Page: 1970-1982
Publish at: 2025-09-01

Advancing power quality via distributed power flow control solutions

10.11591/ijpeds.v16.i3.pp1801-1811
Abdelkader Yousfi , Fayçal Mehedi , Khelifa Khelifi Otmane , Youcef Bot
The growing demand for enhanced power quality and reliable transmission has driven advancements in power flow control technologies. The distributed power flow controller (DPFC) represents an advancement over the unified power flow controller (UPFC). In contrast to the UPFC, the DPFC removes the DC link connecting the shunt and series converters, and redistributes the series converters along the transmission line as single-phase static series compensators. This modification enhances grid performance while maintaining full power flow control capabilities. The DPFC offers several advantages over the UPFC, including higher reliability, improved controllability, and greater cost-effectiveness. The system comprises a shunt converter in conjunction with multiple series converters, each with its own control circuit, all managed by a central control unit. This article presents the implementation of a DPFC model in MATLAB/Simulink. The simulation outcomes indicate that the DPFC significantly contributes to improved voltage stability and enhanced power transfer capability, thereby reinforcing system performance and reliability.
Volume: 16
Issue: 3
Page: 1801-1811
Publish at: 2025-09-01

Enhancement of power quality of grid integrated photo voltaic system using active power filter

10.11591/ijpeds.v16.i3.pp2017-2029
Praveen Kamat , Anant Naik
The world's population's energy needs are growing daily, while at the same time, fossil fuels are being reduced at an alarming rate. Fossil fuel burning also increases pollution and causes global warming. Renewable energies are now being extensively used to generate electricity, so the dependence on fossil fuels is considerably reduced. Among the primary sources of alternative energy used to create power is photovoltaic (PV) technology. A grid connected PV system is the most widely recommended. When PV is linked to the grid, two main issues are the maximum power that can be taken out of it and the quality of the electricity placed into it. With the help of neural networks, the maximum power point tracking (MPPT) technology has been developed to increase the PV array's power harvesting. An active power filter (APF) had been created and analyzed using Instantaneous Reactive Power Theory, including the Chebyshev II low-pass filter. As required by IEEE 519, the total harmonic distortion (THD) with injected source current has been confirmed well within 5%. These results demonstrate that this method is a simple and efficient way to inject harmonic-free currents into the grid.
Volume: 16
Issue: 3
Page: 2017-2029
Publish at: 2025-09-01

Machine learning techniques for solar energy generation prediction in photovoltaic systems

10.11591/ijpeds.v16.i3.pp2055-2062
J. Sumithra , J. C. Vinitha , M. J. Suganya , M. Anuradha , P. Sivakumar , R. Balaji
For photovoltaic (PV) systems to be as effective and dependable as they possibly can be, it is vital to make an accurate prediction of the amount of power that will be generated by the sun. Using machine learning, it is now much simpler to forecast the amount of solar energy that will be generated. These approaches are more accurate and are able to adapt to the ever changing conditions of the nature of the environment. We take a look at the most recent machine learning algorithms for predicting solar energy and examine their methodology, as well as their strengths and drawbacks, in this paper. Using performance metrics like root mean squared error (RMSE), mean absolute error (MAE), and mean squared error (MSE) makes it possible to evaluate important algorithms like support vector machines, decision trees, and linear regression. The results show that machine learning could help make predictions more accurate, lower the amount of uncertainty in operations, and help people make decisions in real time for PV systems. The study also points out important areas where research is lacking and suggests ways to move forward with the use of machine learning in systems that produce renewable energy.
Volume: 16
Issue: 3
Page: 2055-2062
Publish at: 2025-09-01

Dual-aware EV charging scheduling with traffic integration

10.11591/ijpeds.v16.i3.pp1446-1456
Maneesh Yadav , Satyaranjan Jena , Chinmoy Kumar Panigrahi , Ranjan Keshari Pati , Jayanta Kumar Sahu
Electric vehicle adoption is a trend in many countries, and the demand for charging station infrastructure is at a rapid pace. The placement of charging stations is the key research topic of many researchers, but charging scheduling is also a problem that is going to rise in the near future. The proper charger utilization, maintaining coordination between charging stations, and satisfying users' demands are some of the key challenges. The traffic pattern is uncertain, coordination of distances between charging stations and users is done by Euclidean distance. The traffic-aware fair charging scheduling (TAFCS) strategy is proposed, which will have a balance on charger utilization and user prioritization, and keep the fairness by equal distribution of electric vehicles among all the charging stations having a centralized charging system monitored by an aggregator. The distribution of the traffic pattern of electric vehicles is performed by Monte Carlo simulation. The proposed system is tested on the IEEE 33 bus standard system using the predefined voltage limits of each bus and limiting power loss to lessen its burden. The discharging process of 50 electric vehicles (V2G) is performed by optimal placement by obtaining the weakest buses, which makes it an intelligent distribution system. This proposed charging framework is validated on MATLAB R2020a.
Volume: 16
Issue: 3
Page: 1446-1456
Publish at: 2025-09-01

Analysis of cascaded H-Bridge multilevel inverters using SPWM with multi-sinusoidal reference

10.11591/ijpeds.v16.i3.pp1740-1751
Azrita Alias , Wahidah Abdul Halim , Maaspaliza Azri , Jurifa Mat Lazi , Muhammad Zaid Aihsan
Multilevel inverters have become the preferred choice for medium voltage and high-power applications due to their superior waveform quality, reduced stress on switching components, and overall enhanced performance. Among these, the cascaded H-bridge inverter stands out for its simpler control and modulation techniques, as well as its greater efficiency compared to other multilevel inverter topologies. This paper presents the design and performance evaluation of a cascaded H-bridge multilevel inverter (CHMI) for five, seven, nine, eleven, thirteen, and fifteen levels, utilizing sinusoidal pulse width modulation (SPWM) in MATLAB Simulink. The proposed technique, the multi-sinusoidal reference, is implemented by comparing multiple sinusoidal wave signals with a carrier triangular signal, with the resulting comparison pulses used to control the inverter's switching. The output results indicate that as the number of levels in multilevel inverters increases, the total harmonic distortion (THD) decreases, and the output voltage improves.
Volume: 16
Issue: 3
Page: 1740-1751
Publish at: 2025-09-01

Attitude as a mediator between socio-ecological factors and non-communicable disease management: a study protocol

10.11591/ijphs.v14i3.25308
Azrin Shah Abu Bakar , Haliza Abdul Rahman , Ahmad Iqmer Nashriq Mohd Nazan
Non-communicable diseases (NCDs) have risen in Malaysia, and people with low socioeconomic status are more vulnerable to NCDs. Previous studies on the management of non-communicable disease have focused on aspects of socioeconomic factors, individual factors, and psychosocial factors. However, there is limited information on socio-ecological factors (e.g. intrapersonal, interpersonal, organizational, community, and societal factors) and their direct and indirect effect of socio-ecological factors on non-communicable disease management mediated by attitude has not been investigated. Thus, this study aimed to investigate the role of attitude as a mediator between socio-ecological factors and non-communicable disease management among support staff in Putrajaya, Malaysia. A cross-sectional study using cluster random sampling will be conducted at selected Ministries, in Putrajaya Malaysia. The questionnaire will assess respondents’ background information, knowledge of non-communicable disease, attitude towards preventing non-communicable disease and chronic illness resources survey (CIRS) to measure socio-ecological factors. Descriptive and inferential statistics will be used in data analysis using SPSS and SEM with AMOS software. The findings will provide a theoretical model for understanding the various factors that determine towards non-communicable disease management through mediation of attitude.
Volume: 14
Issue: 3
Page: 1387-1393
Publish at: 2025-09-01

Robot Gaussian-historical relocalization: inertial measurement unit-LiDAR likelihood field matching

10.11591/ijra.v14i3.pp438-450
Ye-Ming Shen , Min Kang , Jia-Qiang Yang , Zhong-Hou Cai
Robot localization is a foundational technology for autonomous navigation, enabling task execution and adaptation to dynamic environments. However, failure to return to the correct pose after power loss or sudden displacement (the “kidnapping” problem) can lead to critical system failures. Existing methods often suffer from slow relocalization, high computational cost, and poor robustness to dynamic obstacles. We propose a novel inertial measurement unit (IMU)-LiDAR fusion relocalization framework based on Gaussian historical constraints and adaptive likelihood field matching. By incorporating IMU-derived yaw constraints and modeling historical poses within a 3σ Gaussian region, our method effectively narrows the LiDAR search space. Curvature and normal vector-based feature extraction reduces point cloud volume by 50–70%, while dynamic obstacle filtering via multi-frame differencing and neighborhood validation enhances robustness. An adaptive spiral search strategy further refines pose estimation. Compared to ORB-SLAM3 and adaptive Monte Carlo localization (AMCL), our method maintains comparable accuracy while significantly reducing relocalization time and CPU usage. Experimental results show a relocalization success rate of 84%, average time of 1.68 seconds, and CPU usage of 38.4%, demonstrating high efficiency and robustness in dynamic environments.
Volume: 14
Issue: 3
Page: 438-450
Publish at: 2025-09-01

Global stability of SEIM tuberculosis model with two infection phases and medication effects

10.11591/ijphs.v14i3.25899
Jovian Dian Pratama , Anindita Henindya Permatasari
Tuberculosis (TB), caused by mycobacterium tuberculosis (MTB), remains a significant global health issue, leading to high morbidity and mortality rates despite being a preventable and curable disease. The dynamics of TB transmission and the effects of treatment are critical to improving disease management. This study aims to analyze the global stability of a susceptible, exposed, infected, medicated (SEIM) model for TB transmission, incorporating the effects of medication and infection phases on disease progression. A deterministic SEIM model is proposed, dividing the population into four compartments: susceptible, exposed, infected, and medicated. The model accounts for treatment effects, including non-permanent immunity and the potential dormancy of MTB. Stability analysis was conducted using Lyapunov functions to evaluate equilibrium points, and the basic reproduction number (ℜ0) was derived to determine disease dynamics. The analysis reveals that when ℜ0 < 1, the system is globally asymptotically stable at the non-endemic equilibrium, indicating disease eradication. Conversely, when ℜ0 >1, the system converges to the endemic equilibrium, signifying sustained transmission within the population. These findings highlight the critical role of treatment and infection dynamics in controlling TB spread. The SEIM model provides a comprehensive framework for understanding TB transmission dynamics and emphasizes the importance of reducing (ℜ0) through effective public health interventions. Further research is recommended to validate the model with empirical data and explore its applicability in different epidemiological settings.
Volume: 14
Issue: 3
Page: 1137-1150
Publish at: 2025-09-01

The correlation between family empowerment and the role of family health tasks in preventing anemia during pregnancy

10.11591/ijphs.v14i3.25974
Mira Triharini , Sylvia Dwi Wahyuni , Ni Ketut Alit Armini , Elida Ulfiana , Zurinda Dwi Nur Lailiyaturrohmah , Ananda Amalia Ramadhani
Anemia in pregnancy can harm the mother and baby. Prevention of anemia in pregnant women cannot be separated from the role of the family. Increasing the role of the family requires family empowerment, especially from the husband. This study aimed to analyze the correlation between family empowerment and family role in preventing anemia during pregnancy. This study used a descriptive correlational approach. Sample was 150 of pregnant women who received antenatal care at the Klampis Ngasem and Pacar Keling Health Center, East Java, Indonesia, and were selected using a consecutive sampling method. A statistical test to examine the relationship between independent and dependent variables is conducted using Spearman's Rho. and Chi-square. This study indicates a significant correlation between family empowerment and family role in prevention anemia during pregnancy (p = 0.000; r = 0.578). There is a relationship between the components of family empowerment and family function. Motivation (p = 0.000; r = 0.643), cognitive (p = 0.000; r = 0.552), and personal traits (p = 0.000; r = 0.565) correlated with family role in preventing anemia during pregnancy. Health workers need to provide education to increase family empowerment to increase the role of the family in the five family tasks in preventing anemia during pregnancy.
Volume: 14
Issue: 3
Page: 1375-1386
Publish at: 2025-09-01

Localization and mapping of autonomous wheel mobile robot using Google cartographer

10.11591/ijra.v14i3.pp322-331
Qory Hidayati , Novendra Setyawan , Amrul Faruq , Muhammad Irfan , Nur Kasan , Fitri Yakub
COVID-19 has become a world concern because of the spread and number of cases that have befallen the world. Medical workers are the first exposed group because they have direct contact with patients. So, a vehicle is needed to replace tasks such as logistics, delivery, and patient waste transportation. An autonomous wheeled mobile robot (AWMR) is a wheeled robot capable of moving freely from one place to another. AWMR is required to have good navigation and trajectory control skills. The purpose of this study is to develop an AWMR navigation system model based on the simultaneous localization and mapping (SLAM) algorithm, accurately in a dynamic environment. With this research, developing a good navigation and trajectory method for AWMR, in the future, it can be applied to produce an AWMR platform for multipurpose. This research was conducted in two stages of development. The first year is the research that is currently being carried out, focused on sensor modeling, designing SLAM-based navigation models, and making navigation system testbeds. This research produces a trajectory navigation and control system that can be implemented on an AWMR platform for the purposes of logistics, transportation, and patient waste in hospitals.
Volume: 14
Issue: 3
Page: 322-331
Publish at: 2025-09-01

An Internet of Things based mobile-controlled robot with emergency parking system

10.11591/ijra.v14i3.pp370-380
Abdul Kareem , Varuna Kumara , Vishwanath Madhava Shervegar , Karthik S. Shetty , Manvith Devadig , Mahammad Shamma , Kiran Maheshappa
This paper presents an Internet of Things (IoT) based mobile-controlled car with an emergency parking system that integrates advanced functionalities to enhance safety and user convenience, utilizing the ESP32 microcontroller as its core. The system allows users to control the car remotely via a mobile application, leveraging Wi-Fi connectivity for seamless communication. Key features include LED indicators for various operations such as reversing, left and right turns, and brake activation, ensuring clear signaling in real-time. The innovative emergency parking system detects obstacles or emergencies using sensors and halts the vehicle automatically, reducing the risk of accidents. The car's lightweight, energy-efficient design, combined with the versatility of the ESP32, ensures a responsive and reliable operation. Additionally, the system provides an intuitive user interface through the mobile app, enabling precise control and real-time feedback. The proposed system is faster in response compared to the existing systems. Moreover, the proposed system consumes less energy, and hence, it uses the battery more efficiently, extending the time of operation. Lower power consumption ensures longer operation time, reducing the need for frequent charging and making the system more practical. This paper demonstrates the integration of IoT and embedded systems to create a smart vehicle solution suitable for various applications, including robotics, automation, and personal transport. Its cost-effectiveness and scalability make it a viable choice for both hobbyists and developers.
Volume: 14
Issue: 3
Page: 370-380
Publish at: 2025-09-01

Exploring the role of swimming in enhancing diet-based weight loss programs for athletes

10.11591/ijphs.v14i3.25330
Cherkaoui Sidi Hassan , Mouane Nezha
This study explores the synergistic effects of customized dietary strategies and aerobic exercise, specifically swimming, on achieving weight loss while preserving muscle mass in athletes. The research highlights the importance of a holistic approach to weight management, integrating personalized diet plans with tailored exercise regimens. The study segmented participants into two groups, one following a standard diet for weight maintenance and another adhering to a similar diet augmented by regular swimming sessions aimed at weight loss. Results indicate that the diet-plus-swimming group exhibited significantly greater reductions in weight and body mass index (BMI) compared to the diet-only group, suggesting that incorporating swimming enhances the effectiveness of dietary interventions. These findings emphasize the potential of combining physical activities such as swimming with dietary modifications to achieve optimal weight management outcomes, providing a comprehensive approach to athlete health management. The study also underscores the need for personalized strategies that consider individual characteristics and preferences to support sustainable weight loss and improved health outcomes.
Volume: 14
Issue: 3
Page: 1452-1458
Publish at: 2025-09-01
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