• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권5호
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• pp.2400-2413
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• 2019

Doubly-selective (DS) fading channel is often occurred in many orthogonal frequency division multiplexing (OFDM) communication systems, such as high-speed rail communication systems and underwater acoustic (UWA) wireless networks. It is challenging to provide an accurate and fast estimation over the doubly-selective channel, due to the strong Doppler shift. This paper addresses the doubly selective channel estimation problem based on complex exponential basis expansion model (CE-BEM) in OFDM systems from the perspective of distributed compressive sensing (DCS). We propose a novel DCS-based improved sparsity adaptive matching pursuit (DCS-IMSAMP) algorithm. The advantage of the proposed algorithm is that it can exploit the joint channel sparsity information using dynamic threshold, variable step size and tailoring mechanism. Simulation results show that the proposed algorithm achieves 5dB performance gain with faster operation speed, in comparison with traditional DCS-based sparsity adaptive matching pursuit (DCS-SAMP) algorithm.

• 한국자동차공학회논문집
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• 제11권5호
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• pp.43-49
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• 2003

The common-rail fuel injection system is becoming a common technology for High Speed Direct Injection(HSDI) diesel engines. The injection timing and rate are important factors for combustion control and pollutants formation mechanisms during engine operation. This paper introduces an estimation methodology of the injection timing and rate of a common-rail injector for HSDI diesel engines. A sliding mode observer that is based on the nonlinear mathematical model of the common-rail injector is designed to overcome the model uncertainties. The injector model and the estimator we verified by relevant injection experiments in an injector test bench. The simulation and the experimental results show that the proposed sliding mode observer can effectively estimate the injection rate of the common-rail injector.

• 조명전기설비학회논문지
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• 제25권5호
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• pp.22-33
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• 2011

An induction motor operated with a conventional direct self controller(DSC) shows a sluggish response during startup and under changes of torque command. Fuzzy logic controller(FLC) is used in conjection with DSC to minimize these problems. A FLC chooses the switching states based on a set of fuzzy variables. Flux position, error in flux magnitude and error in torque are used as fuzzy state variables. Fuzzy rules are determinated by observing the vector diagram of flux and currents. This paper proposes hybrid fuzzy controller for direct torque control(DTC) of induction motor drives. The speed controller is based on adaptive fuzzy learning controller(AFLC), which provide high dynamics performances both in transient and steady state response. Flux position, error in flux magnitude and error in torque are used as FLC state variables. The speed is estimated with model reference adaptive system(MRAS) based on artificial neural network(ANN) trained on-line by a back-propagation algorithm. This paper is controlled speed using hybrid fuzzy controller(HFC) and estimation of speed using ANN. The performance of the proposed induction motor drive with HFC controller and ANN is verified by analysis results at various operation conditions.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• 제5B권4호
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• pp.350-357
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• 2005

This paper presents a mechanical sensorless vector-controlled system with parameter identification by the aid of image processor. Based on the flux observer and the model reference adaptive system method, the proposed sensorless system includes rotor speed estimation and stator resistance identification using flux errors. Since the mathematical model of this system is constructed in a synchronously rotating reference frame, a linear model is easily derived for analyzing the system stability, including motor operating state and parameter variations. Because it is difficult to identify rotor resistance simultaneously while estimating rotor speed, a low-accuracy image processor is used to measure the mechanical axis position for calculating the rotor speed at a steady-state operation. The rotor resistance is identified by the error between the estimated speed using the estimated flux and the calculated speed using the image processor. Finally, the validity of this proposed system has been proven through experimentation.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2004년도 전력전자학술대회 논문집(1)
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• pp.274-278
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• 2004

This paper presents a strategy to drive built in-type spindle induction motor which is used as CNC (Computer Numerical Control) in the industrial world. The direct vector control which is robust to the changed machine parameters in the high speed range is used in this motor control method. And electrical model of induction motor presents the basic idea based on observer structure, which is composed of voltage model and current model. But the former has the defects in low speed range, the latter has the defects of sensitivity to motor parameter. Thus Gopinath model flux estimator which is the closed loop flux observer based on two models for the rotor flut estimation is used in this paper. Moreover this paper presents to drive the spindle motor in the high speed range by using the flux weakening control.

• 한국건설관리학회논문집
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• 제14권2호
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• pp.96-107
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• 2013

초고층 건물공사에서 타워크레인의 양중계획은 전체 공사의 성패를 좌우할 수 있는 매우 중요한 요소 중 하나이다. 타워크레인의 양중계획에 있어 양중시간은 기본적인 요소 중 하나로 이를 바탕으로 양중부하 및 타워크레인을 선정하기 때문에 양중계획을 위해서는 정확한 양중시간의 예측이 필요하다고 할 수 있다. 현재 초고층 공사의 양중시간 예측은 기존의 실적자료와 시뮬레이션을 이용하여 수행하고 있지만 양중작업에 영향을 미치는 환경적인 요인에 대해서는 충분히 고려되지 못하고 있다. 따라서 본 연구에서는 양중작업에 영향을 크게 미치는 바람을 시뮬레이션에 반영하여 초고층 공사의 타워크레인 양중시간을 예측하는 시뮬레이션 모델을 개발하였다. 시뮬레이션 분석 결과 바람의 영향을 반영한 양중시간은 높이가 올라갈수록 증가하였으며, 초고층부의 경우 기계적 양중시간보다 바람의 영향에 의한 양중 지연시간이 더 크다는 것을 알 수 있었다. 또한 연구 대상지인 서울의 풍속은 4월이 강하고 10월이 약하게 나타났으며, 양중시간을 예측한 결과 둘 간의 큰 차이가 발생함을 알 수 있었다. 이 같은 결과는 향후 초고층 타워크레인 양중계획 시 바람이 양중에 미치는 영향을 예측하고 이를 고려하여 실제 상황과 동일한 양중계획을 세우는데 활용될 수 있을 것으로 기대된다.

• 전기학회논문지
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• 제67권5호
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• pp.635-643
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• 2018

This paper propose a method to identify the motor parameters and improve input voltage error which affect the low speed position error of the back-emf(back electromotive force) based sensorless algorithm and to secure the operation reliability and stability even in the case where the load fluctuation is severe and the start and low speed operation frequently occurs. In the model-based observer used in this paper, stator resistance, inductance, and input voltage are particularly influential factors on low speed performance. Stator resistance can cause resistance value fluctuation which may occur in mass production process, and fluctuation of resistance value due to heat generated during operation. The inductance is influenced by the fluctuation due to the manufacturing dispersion and at a low speed where the change of the current is severe. In order to find stator resistance and inductance which have different initial values and fluctuate during operation and have a large influence on sensorless performance at low speed, they are commonly measured through 2-point calculation method by 2-step align current injection. The effect of voltage error is minimized by offsetting the voltage error. In addition, when the command voltage is used, it is difficult to estimate the back-emf due to the relatively large distortion voltage due to the dead time and the voltage drop of the power device. In this paper, we propose a simple circuit and method to detect the voltage by measuring the PWM(Pulse Width Modulation) pulse width and compensate the voltage drop of the power device with the table, thereby minimizing the position error due to the exact estimation of the back-emf at low speed. The suitability of the proposed algorithm is verified through experiment.

• 대한전기학회논문지:전력기술부문A
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• 제48권10호
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• pp.1317-1326
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• 1999

As the integration ratio and operation speed increase, it has become an important problem to estimate the dissipated power during the design procedure as a method to reduce the TTM(time to market). This paper proposed a prediction model to estimate the maximum dissipated power of a CMOS logic gate. This model uses a calculational method. It was formed by including the characteristics of MOSFETs of which a CMOS gate consists, the operational characteristics of the gate, and the characteristics of the input signals. As the modeling process, a maximum power estimation model for CMOS inverter was formed first, and then a conversion model to convert a multiple input CMOS gate into a corresponding CMOS inverter was proposed. Finally, the power model for inverter was applied to the converted result so that the model could be applied to a general CMOS gate. For experiment, several CMOS gates were designed in layout level by $0.6{\mu}m$ layout design rule. The result by comparing the calculated results with those from HSPICE simulations for the gates showed that the gate conversion model has within 5% of the relative error rate to the SPICE and the maximum power estimation model has within 10% of the relative error rate. Thus, the proposed models have sufficient accuracies. Also in calculation time, the proposed models was more than 30 times faster than SPICE simulation. Consequently, it can be said that the proposed model could be used efficiently to estimate the maximum dissipated power of a CMOS logic gate during the design procedure.

• Journal of Electrical Engineering and Technology
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• 제13권3호
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• pp.1156-1165
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• 2018

This paper presents a detailed realization of direct torque controlled induction motor drive for elevator applications. The drive is controlled according to the well-known space vector modulated direct control scheme (SVM-DTC). As the elevator drives are usually equipped with speed sensors, flux estimation is carried out using a current model where two stator currents are measured and accurate instantaneous rotor speed measurement is used to overcome the need for measuring stator voltages. Speed profiling for a comfortable elevator ride and other supervisory control activities to provide smooth operation are also explained. The drive performance is examined and controllers' parameters are fine-tuned using MATLAB/SIMULINK. The blocks used for flux and torque estimation and control in the offline simulation are compiled for real-time using dSPACE Microlabox. The performance of the drive has been verified experimentally. The results show good performance under transient and steady state conditions.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 춘계학술대회 논문집 에너지변화시스템부문
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• pp.32-34
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• 2009

The field oriented control of induction motors is widely used in high performance applications. However, detuning caused by parameter disturbance still limits the performance of these drives. In order to accomplish variable speed operation, conventional PI-like controllers are commonly used. These controllers provide limited good Performance over a wide range of operation, even under ideal field oriented conditions. This paper is proposed model reference adaptive fuzzy control(MFC) and artificial neural network(ANN) based on the vector controlled induction motor drive system. Also, this paper is proposed control of speed and current using fuzzy adaption mechanism(FAM), MFC and estimation of speed using ANN. The proposed control algorithm is applied to induction motor drive system using FAM, MFC and ANN controller. Also, this paper is proposed the analysis results to verify the effectiveness of this controller.