• Journal of Power Electronics
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• v.17 no.1
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• pp.282-293
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• 2017

There exists a strong coupling between real and reactive power owing to the complex impedances in droop based islanded microgrids (MGs). The existing virtual impedance methods consider improvements of the impedance matching for sharing of the voltage controlled power (VCP) (reactive power for Q-V droop, and real power for P-V droop), which yields a 1-DOF (degree of freedom) tunable virtual impedance. However, a weak impedance matching for sharing of the frequency controlled power (FCP) (real power for $P-{\omega}$ droop, and reactive power for $Q-{\omega}$ droop) may result in FCP overshoots and even oscillations during load transients. This in turn results in VCP oscillations due to the strong coupling. In this paper, a 2-DOF tunable adaptive virtual impedance method considering impedance matching for both real and reactive power (IM-PQ) is proposed to improve the power sharing performance of MGs. The dynamic response is promoted by suppressing the coupled power oscillations and power overshoots while realizing accurate power sharing. In addition, the proposed power sharing controller has a better parametric adaptability. The stability and dynamic performances are analyzed with a small-signal state-space model. Simulation and experimental results are presented to investigate the validity of the proposed scheme.

• Journal of Communications and Networks
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• v.7 no.3
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• pp.337-352
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• 2005

In this paper, a fuzzy logic implementation of the random early detection (RED) mechanism [1] is presented. The main objective of the proposed fuzzy controller is to reduce the loss probability of the RED mechanism without any change in channel utilization. Based on previous studies, it is clear that the performance of RED algorithm is extremely related to the traffic load as well as to its parameters setting. Using fuzzy logic capabilities, we try to dynamically tune the loss probability of the RED gateway. To achieve this goal, a two-input-single-output fuzzy controller is used. To achieve a low packet loss probability, the proposed fuzzy controller is responsible to control the $max_{p}$ parameter of the RED gateway. The inputs of the proposed fuzzy controller are 1) the difference between average queue size and a target point, and 2) the difference between the estimated value of incoming data rate and the target link capacity. To evaluate the performance of the proposed fuzzy mechanism, several trials with file transfer protocol (FTP) and burst traffic were performed. In this study, the ns-2 simulator [2] has been used to generate the experimental data. All simulation results indicate that the proposed fuzzy mechanism out performs remarkably both the traditional RED and Adaptive RED (ARED) mechanisms [3]-[5].

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.858-863
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• 1988

A micro-processor based control system for a brushless DC motor used in the motor-driven electromechanical total artificial heart was developed. Functionally, the control system is composed of two parts. The first part is the velocity and position controller to assure that the motor follows a predetermined optimal velocity profile with minimal energy consumption, and to guarantee the full stroke length. This part also utilize the passive adaptive control method to be robust against the load disturbance, system parameter variation, and uncertainty which is the environment of artificial heart system. The pump output control is the second part, and this part provides the required responses of the artificial heart to the time-varying physiologic demands. The basic requirements of these responses are preload sensitivity, afterload insensitivity, and the balanced ventricular outputs. The performance and reliability of this control system was evaluated through a series of mock circulation tests and animal implantation, and the results are very encouraging.

• JSTS:Journal of Semiconductor Technology and Science
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• v.13 no.4
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• pp.318-330
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• 2013

This paper presents a high-linearity low-noise small-size programmable gain amplifier (PGA) based on a new low-noise low-distortion differential amplifier and a proposed reconfiguration technique. The proposed differential amplifier combines an inverter-based differential pair with an adaptive biasing circuit to reduce noise and distortion. The reconfiguration technique saves the chip size by half by utilizing the same differential pair for the input transconductance and load-stage, interchangeably. Fabricated in $0.18-{\mu}m$ CMOS, the proposed PGA shows a dB-linear control range of 21dB in 16 steps from -11 dB to 10 dB with a gain error of less than ${\pm}0.33$ dB, an IIP3 of 7.4~14.5 dBm, a P1dB of -7~1.2 dBm, a noise figure of 13dB, and a 3-dB bandwidth of 270MHz at the maximum gain, respectively. The PGA occupies a chip area of $0.04mm^2$ and consumes only 1.3 mA from the 1.8 V supply.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.4
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• pp.231-238
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• 2017

Detecting small infrared targets from the low-SCR images at a long distance is very hard. The previous Local Contrast Method (LCM) algorithm based on the human visual system shows a superior performance of detecting small targets by a background suppression technique through local contrast measure. However, its slow processing speed due to the heavy multi-scale processing overhead is not suitable to a variety of real-time applications. This paper presents a lightweight real-time small target detection algorithm, called by the Improved Selective Local Contrast Method (ISLCM), to reduce the scale-invariant computational overhead. The proposed ISLCM applies the improved local contrast measure to the predicted selective region so that it may have a comparable detection performance as the previous LCM while guaranteeing low scale-invariant computational load by exploiting both adaptive scale estimation and small target feature feasibility. Experimental results show that the proposed algorithm can reduce its computational overhead considerably while maintaining its detection performance compared with the previous LCM.

• Proceedings of the Ginseng society Conference
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• 1987.06a
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• pp.47-58
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• 1987

Ethanol exerts different effects on hepatic cellular metabolism, depending mainly on the duration of its intake. In the presence of ethanol following an acute load, a number of hepatic functions are inhibited, including lipid oxidation and microsomal drug metabolism. In its early stages, chronic ethanol consumption produces adaptive metabolic changes in the endoplasmic reticulum which result in increased metabolism of ethanol and drugs and accelerated lipoprotein production. Prolongation of ethanol intake may result in injurious hepatic lesions such as alcoholic hepatitis and cirrhosis A number of such metabolic effects of ethanol are directly linked to the two major products of its oxidation; hydrogen and acetaldehyde. The excess hydrogen from ethanol unbalances the liver cell's chemistry. In the presence of excess hydrogen ions the process is turned in a different direction. In this study, it was attempted to observe the effect of ginseng saponins on alcohol Oehydrogenase(ADH), aldehyde dehydrogenase(ALDH) and microsomal ethanol oxidizing system(MEOS) in vivo as well as in vitro. Furthermore, the effect of ginseng saponin on the hydrogen balance in the liver and the hepatic cellular distribution of (1-14C) ethanol, its incorporation into acetaldehyde and lipids was also investigated. It seemed that ginseng saponin stimulated the above enzymes and other related enzymes in ethanol metabolism, resulting in a rapid removal of acetaldehyde and excess hydrogen from the animal body,

• Nuclear Engineering and Technology
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• v.27 no.6
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• pp.833-844
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• 1995

In self-tuning predictive control algorithm for steam generator is presented. The control algorithm is derived by suitably modifying the generalized predictive control algorithm. The main feature of the unposed method relies on considering the measurable disturbance and a simple adaptive scheme for obtaining the controller gain when the parameters of the plant are unknown. This feature makes the proposed approach particularly appealing for water level control of steam generator when measurable disturbance is used. In order to evaluate the performance of the proposed algorithm, computer simulations are done for an PWR steam generator model. Simulation result show satisfactory performances against load variations and steam flow rate estimation errors. It can be also observed that the proposed algorithm exhibit better responses than a conventional PI controller.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.804-811
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• 2015

The presence of responsive loads in the promising active distribution networks (ADNs) would definitely affect the power system problems such as distributed generations (DGs) studies. Hence, an optimal procedure is proposed herein which takes into account the simultaneous placement of DGs and smart meters (SMs) in ADNs. SMs are taken into consideration for the sake of successful implementing of demand response programs (DRPs) such as direct load control (DLC) with end-side consumers. Seeking to power loss minimization, the optimization procedure is tackled with genetic algorithm (GA) and tested thoroughly on 69-bus distribution test system. Different scenarios including variations in the number of DG units, adaptive power factor (APF) mode for DGs to support reactive power, and individual or simultaneous placing of DGs and SMs have been established and interrogated in depth. The obtained results certify the considerable effect of DRPs and APF mode in determining the optimal size and site of DGs to be connected in ADN resulting to the lowest value of power losses as well.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.3C
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• pp.183-189
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• 2011

The LMS(Least Mean Square) algorithm is generally used because of tenacity, high mating spots and simplicity of realization. But the LMS algorithm has trade-off between nonuniform collect and EMSE(Excess Mean Square Error). To overcome this weakness, variable step size is used widely but it needs a lot of calculation load. In this paper we consider new algorithm, which can reduce calculations and adapt in case of environment changes, uses original signal and noise signal of IGC(Instantaneous Gain Control). For the real time processing of IGC algorithm, we remove the logarithmic function. The performance of proposed algorithm is tested to adaptive noise canceller in automobile. We show implemented LabVIEW FPGA system of IGC algorithm is more efficient than others.

• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.3
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• pp.122-129
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• 1996

The spark timing is one of major parameters to the engine performance and emissions. The ECU controls the spark timing based on preset values, which are functions of load and speed, in most of today's automotive SI engine. In this system, the preset spark timing can be different from optimum value due to the deviations from mass production, aging effects and so on. In the present study, a control logic is investigated for real time adaptation of spark timing to optimal value. It has been found that crank angle of miximum cylinder pressure is one of the appropriate parameters to estimate the optimum spark timing throught experiment. It has also been observed for spark timing convergence by variation of engineering model factors. The simulation program including engineering model for cycle by cycle variation of combustion is developed for surveying spark timing control logic. It is also shown that simulation results reflect experiment outputs and reasonableness of spark timing control logic for crank angle of maximum cylinder pressure.