• Journal of Power Electronics
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• v.19 no.4
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• pp.881-893
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• 2019

This paper proposes a practical sliding-mode controller design for shaping the impedances of cascaded boost-converter power decoupling circuits for reducing the second order harmonic ripple in photovoltaic (PV) current. The cascaded double-boost converter, when used as power decoupling circuit, has some advantages in terms of a high step-up voltage-ratio, a small number of switches and a better efficiency when compared to conventional topologies. From these features, it can be seen that this topology is suitable for residential (PV) rooftop systems. However, a robust controller design capable of rejecting double frequency inverter ripple from passing to the (PV) source is a challenge. The design constraints are related to the principle of the impedance-shaping technique to maximize the output impedance of the input-side boost converter, to block the double frequency PV current ripple component, and to prevent it from passing to the source without degrading the system dynamic responses. The design has a small recovery time in the presence of transients with a low overshoot or undershoot. Moreover, the proposed controller ensures that the ripple component swings freely within a voltage-gap between the (PV) and the DC-link voltages by the small capacitance of the auxiliary DC-link for electrolytic-capacitor elimination. The second boost controls the main DC-link voltage tightly within a satisfactory ripple range. The inverter controller performs maximum power point tracking (MPPT) for the input voltage source using ripple correlation control (RCC). The robustness of the proposed control was verified by varying system parameters under different load conditions. Finally, the proposed controller was verified by simulation and experimental results.

• Advances in nano research
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• v.10 no.2
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• pp.151-163
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• 2021

The main target of this study is to investigate nonlinear transient responses of moving polymer nano-size plates fortified by means of Graphene Platelets (GPLs) and resting on a Winkler-Pasternak foundation under a transverse pressure force and a temperature variation. Two graphene spreading forms dispersed through the plate thickness are studied, and the Halpin-Tsai micro-mechanics model is used to obtain the effective Young's modulus. Furthermore, the rule of mixture is employed to calculate the effective mass density and Poisson's ratio. In accordance with the first order shear deformation and von Karman theory for nonlinear systems, the kinematic equations are derived, and then nonlocal strain gradient scheme is used to reflect the effects of nonlocal and strain gradient parameters on small-size objects. Afterwards, a combined approach, kinetic dynamic relaxation method accompanied by Newmark technique, is hired for solving the time-varying equation sets, and Fortran program is developed to generate the numerical results. The accuracy of the current model is verified by comparative studies with available results in the literature. Finally, a parametric study is carried out to explore the effects of GPL's weight fractions and dispersion patterns, edge conditions, softening and hardening factors, the temperature change, the velocity of moving nanoplate and elastic foundation stiffness on the dynamic response of the structure. The result illustrates that the effects of nonlocality and strain gradient parameters are more remarkable in the higher magnitudes of the nanoplate speed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1492-1499
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• 2020

A weather radar system generally shows the weather phenomena related with rainfall and wind velocity. These systems are usually very helpful to monitor the relatively high altitude weather situation for the wide and long range area. However, since the weather hazards due to the strong hail and heavy rainfall occurring locally are observed frequently in recent days, it is important to detect these wether phenomena. For this purpose, it is necessary to detect the fast varying low altitude weather conditions. In this environment, the effect of surface clutter is more evident and the antenna dwell time is much shorter. Therefore, the conventional Doppler spectrum estimation method may cause serious problems. In this paper, the AR(autoregressive) Doppler spectrum estimation methods were applied to solve these problems and the results were analyzed. Applied methods show that improved Doppler spectra can be obtained comparing with the conventional FFT(Fast Fourier Transform) method.

• Journal of IKEEE
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• v.26 no.3
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• pp.349-354
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• 2022

In thermal power plants, boiler models have been used widely in evaluating logic configurations, performing system tuning and applying control theory, etc. Furthermore, proper plant models are needed to design the accurate controllers. Sometimes, mathematical models can not exactly describe a power plant due to time varying, nonlinearity, uncertainties and complexity of the thermal power plants. In this case, a neural network can be a useful method to estimate such systems. In this paper, the models of boiler steam system in a thermal power plant are developed by using a generalized regression neural network(GRNN). The models of the superheater, reheater, attemperator and drum are designed by using GRNN and the models are trained and validate with the real data obtained in 540[MW] power plant. The validation results showed that proposed models agree with actual outputs of the drum boiler well.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.12
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• pp.437-444
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• 2022

Recently, research on mobile edge services has been conducted to handle computationally intensive and latency-sensitive tasks occurring in wireless networks. However, MEC, which is fixed on the ground, cannot flexibly cope with situations where task processing requests increase sharply, such as commuting time. To solve this problem, a technology that provides edge services using UAVs (Unmanned Aerial Vehicles) has emerged. Unlike ground MEC servers, UAVs have limited battery capacity, so it is necessary to optimize energy efficiency through load balancing between UAV MEC servers. Therefore, in this paper, we propose a load balancing technique with consideration of the energy state of UAVs and the mobility of vehicles. The proposed technique is composed of task offloading scheme using genetic algorithm and task migration scheme using Q-learning. To evaluate the performance of the proposed technique, experiments were conducted with varying mobility speed and number of vehicles, and performance was analyzed in terms of load variance, energy consumption, communication overhead, and delay constraint satisfaction rate.

• Smart Structures and Systems
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• v.29 no.1
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• pp.41-51
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• 2022

Cables are critical components of cable-stayed bridges. A structural health monitoring system provides real-time cable tension recording for cable health monitoring. However, the measurement data involve multiple sources of variability, i.e., varying environmental and operational factors, which increase the complexity of cable condition monitoring. In this study, a one-class classification method is developed for cable condition assessment using Bayesian factor analysis (FA). The single-peaked vehicle-induced cable tension is assumed to be relevant to vehicle positions and weights. The Bayesian FA is adopted to establish the correlation model between cable tensions and vehicles. Vehicle weights are assumed to be latent variables and the influences of different transverse positions are quantified by coefficient parameters. The Bayesian theorem is employed to estimate the parameters and variables automatically, and the damage index is defined on the basis of the well-trained model. The proposed method is applied to one cable-stayed bridge for cable damage detection. Significant deviations of the damage indices of Cable SJS11 were observed, indicating a damaged condition in 2011. This study develops a novel method to evaluate the health condition of individual cable using the FA in the Bayesian framework. Only vehicle-induced cable tensions are used and there is no need to monitor the vehicles. The entire process, including the data pre-processing, model training and damage index calculation of one cable, takes only 35 s, which is highly efficient.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1863-1871
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• 2022

In the era of Fourth Industrial Revolution, secure networking technology is playing an essential role in the defense weapon systems. Encryption technology is used for information security. The safety of cryptographic technology, according to Kerchoff's principles, is based on secure key management of cryptographic technology, not on cryptographic algorithms. However, traditional centralized key management is one of the problematic issues in battlefield environments since the frequent movement of the forces and the time-varying quality of tactical networks. Alternatively, the system resources of each node used in the IoBT(Internet of Battlefield Things) environment are limited in size, capacity, and performance, so a lightweight key management system with less computation and complexity is needed than a conventional key management algorithm. This paper proposes a novel key escrow scheme in a lightweight manner for the IoBT environment. The safety and performance of the proposed technique are verified through numerical analysis and simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.6
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• pp.1659-1674
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• 2024

Conventional maritime communication struggles to provide high data rate services for Internet of Things (IoT) devices due to the variability of maritime environments, making it challenging to ensure consistent connectivity for onboard sensors and devices. To resolve this, we perform mathematical modeling of the maritime channel and compare it with real measurement data. Through the modeled channel, we verify the received beam gain at buoys on the ocean surface. Additionally, leveraging the modeled wave motions, we estimate future angles of the buoy to use the Extended Kalman Filter (EKF) for design beamforming strategies that adapt to the evolving maritime environment over time. We further validate the effectiveness of these strategies by assessing the results from an outage probability perspective. focuses on improving maritime communication by developing a dynamic model of the maritime channel and implementing a Kalman filter-based buoy motion tracking system. This system is designed to enable precise beamforming, a technique used to direct communication signals more accurately. By improving beamforming, the aim is to enhance the quality of communication links, even in challenging maritime conditions like rough seas and varying sea states. In our simulations that consider realistic wave motions, you've observed significant improvements in link quality due to the enhanced beamforming technique. These improvements are particularly notable in environments with high sea states, where communication challenges are typically more pronounced. The progress made in this area is not just a technical achievement; it has broad implications for the future of maritime communication technologies. This paper promises to revolutionize the way we approach communication in maritime environments, paving the way for more reliable and efficient information exchange on the seas.

• Ocean Systems Engineering
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• v.13 no.4
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• pp.349-365
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• 2023

Targeting a floating wave and offshore wind hybrid power generation system (FWWHybrid) designed in the Republic of Korea, this study examines the impact of the interaction, with multiple wave energy converters (WECs) placed on the platform, on platform motion. To investigate how the motion of WECs affects the behavior of the FWWHybrid platform, it was numerically compared with a scenario involving a 'single-body' system, where multiple WECs are constrained to the platform. In the case of FWWHybrid, because the platform and multiple WECs move in response to waves simultaneously as a 'multi-body' system, hydrodynamic interactions between these entities come into play. Additionally, the power take-off (PTO) mechanism between the platform and individual WECs is introduced for power production. First, the hydrostatic/dynamic coefficients required for numerical analysis were calculated in the frequency domain and then used in the time domain analysis. These simulations are performed using the extended HARP/CHARM3D code developed from previous studies. By conducting regular wave simulations, the response amplitude operator (RAO) for the platform of both single-body and multi-body scenarios was derived and subsequently compared. Next, to ascertain the difference in response in the real sea environment, this study also includes an analysis of irregular waves. As the floating body maintains its position through connection to a catenary mooring line, the impact of the slowly varying wave drift load cannot be disregarded. To assess the influence of the 2^nd-order wave exciting load, irregular wave simulations were conducted, dividing them into cases where it was not considered and cases where it was included. The analysis of multi-degree-of-freedom behavior confirmed that the action of multiple WECs had a substantial impact on the platform's response.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.12
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• pp.78-89
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• 1999

Previous wavelet network structures are determined by considering the relationship between wavelet windows distribution of training patterns that are transformed into time-frequency space. Because it is separated two algorithms that determines wavelet network structure and that modifies parameters of network, learning process that minimizes output error of network is executed after the network structure is determined. But this method has some weakness that training patterns must be transformed into time-frequency space by additional preprocessing and the network structure should be fixed during learning process. In this paper, we propose a new constructing method for wavelet network structure by using differences between the output and the desired response without preprocessing. Because the algorithm perform network construction and error minimizing process simultaneously, it can determine the number of hidden nodes adaptively as with the complexity of problems. In addition, the network structure is optimized by inserting new hidden nodes in the area that has maximum error and extracting hidden nodes that has no effect to the output of network. This algorithm has no constraint condition that all training patterns must be known, because it removes preprocessing procedure for training patterns and it can be applied effectively to systems that has time varying outputs.