• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.6
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• pp.16-28
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• 2012

This paper proposes a quasi Z-source converter(QZSC) with a diode-capacitor output filter to improve the output DC voltage boost ability. The proposed converter has the same quasi Z-source network topology compared with the conventional converter. But the proposed method is adopted a diode-capacitor filter as its output filter, since the conventional method is used an inductor-capacitor as its output filter. Under the condition of the same input-output DC voltage, the proposed method has more lower shoot-through duty ratio than the conventional method. Also, because the proposed converter has same voltage boost factor under lower shoot-through duty ratio compared with the conventional converter, the proposed converter can be operated with the lower capacitor voltage of Z-source network and the lower input current. To confirm the validity of the proposed method, PSIM simulation and a DSP based experiment were performed to acquire the output DC voltage 120[V] under the input DC voltage 80[V]. And the capacitor voltage and inductor current in Z-source network, the output voltage of each converter were compared and discussed.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.93.3-93
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• 2001

We propose the cascade PID type fuzzy control method for a good performance such as robustness. The one of proposed method, the first stage have two input variables of an error and a derivative error, and one output variable, and the next stage have two input variables of the output of first stage and an integral error, and one output variable, have two stages. The other, the first stage has one input of an error, and one output variable, and the second stage have two input of the output of first stage and a derivative error, and one output variable, and the third stage have two input of the output of the second stage and an integer error, and one output variable ...

• Journal of international Conference on Electrical Machines and Systems
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• v.1 no.2
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• pp.85-90
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• 2012

This paper presents a topology structure and control method for an input-parallel-output-series(IPOS) inverter system which is suitable for high input current, high output voltage, and high power applications. In order to ensure the normal operation of the IPOS inverter system, the control method should achieve input current sharing(ICS) and output voltage sharing(OVS) among constituent modules. Through the analysis in this paper, ICS is automatically achieved as long as OVS is controlled. The IPOS inverter system is controlled by a three-loop control system which is composed of an outer common-output voltage loop, inner current loops and voltage sharing loops. Simulation results show that this control strategy can achieve low total harmonic distortion(THD) in the system output voltage, fast dynamic response, and good output voltage sharing performance.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.10
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• pp.1031-1036
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• 2015

Proportional-integral-derivative (PID) controllers are widely used in industrial sites. Most tuning methods for PID controllers use an empirical and experimental approach; thus, the experience and intuition of a designer greatly affect the tuning of the controller. The representative methods include the closed-loop tuning method of Ziegler-Nichols (Z-N), the C-C tuning method, and the Internal Model Control tuning method. There has been considerable research on the tuning of PID controllers for single-input single-output systems but very little for multi-input multi-output systems. It is more difficult to design PID controllers for multi-input multi-output systems than for single-input single-output systems because there are interactive control loops that affect each other. This paper presents a tuning method for the PID controller for a two-input two-output system. The proposed method uses a real-coded genetic algorithm (RCGA) as an optimization tool, which optimizes the PID controller parameters for minimizing the given objective function. Three types of objective functions are selected for the RCGA, and each PID controller parameter is determined accordingly. The performance of the proposed method is compared with that of the Z-N method, and the validity of the proposed method is examined.

• Journal of Power System Engineering
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• v.7 no.1
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• pp.74-81
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• 2003

A system identification is to estimate the mathematical model on the base of input output data and to measure the output in the presence of adequate input for the controlled system. In the traditional system control field, most identification problems have been thought as estimating the unknown modeling parameters on the assumption that the model structures are fixed. In the system identification, it is possible to estimate the true parameter values by the adjusted least squares method in the input output case of no observed noise, and it is possible to estimate the true parameter values by the total least squares method in the input output case with the observed noise. We suggest the adjusted least squares method as a consistent estimation method in the system identification in the case where there is observed noise only in the output. In this paper the adjusted least squares method has been developed from the least squares method and the efficiency of the estimating results was confirmed by the generating data with the computer simulations.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.9
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• pp.133-141
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• 1994

Conventional competitive learning algorithms compute the Euclidien distance to determine the winner neuron out of all predetermined output neurons. In such cases, there is a drawback that the performence of the learning algorithm depends on the initial reference(=weight) vectors. In this paper, we propose a new competitive learning algorithm that dynamically generates output neurons. The proposed method generates output neurons by dynamically changing the class thresholds for all output neurons. We compute the similarity between the input vector and the reference vector of each output neuron generated. If the two are similar, the reference vector is adjusted to make it still more like the input vector. Otherwise, the input vector is designated as the reference vector of a new outputneuron. Since the reference vectors of output neurons are dynamically assigned according to input pattern distribution, the proposed method gets around the phenomenon that learning is early determined due to redundant output neurons. Experiments using speech data have shown the proposed method to be superior to existint methods.

• Journal of Power Electronics
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• v.19 no.6
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• pp.1380-1392
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• 2019

Input filters are very important to matrix converters (MCs). They are used to improve grid side current waveform quality and to reduce the input voltage distortion supplied to the grid side. Due to the effects of the input filter and the output power, the grid side power factor (PF) is not at unity when the input power factor angle is zero. In this paper, the displacement angle between the grid side phase current and the phase voltage affected by the input filter parameters and output power is analyzed. Based on this, a new grid side PF unity compensation method implemented in the indirect space vector pulse width modulation (ISVPWM) method is presented, which has a larger compensation angle than the traditional compensation method, showing a higher grid side PF at unity in a wide output power range. Simulation and experimental results verify that the analysis of the displacement angle between the grid side phase current and the phase voltage affected by the input filter and output power is right and that the proposed compensation method has a better grid side PF at unity.

• IE interfaces
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• v.22 no.1
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• pp.44-55
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• 2009

We propose a method for selection of input-output factors in DEA. It is designed to select better combinations of input-output factors that are well suited for evaluating substantial performance of DMUs. Several selected DEA models with different input-output factors combinations are evaluated, and the relationship between the computed efficiency scores and a single performance criterion of DMUs is investigated using decision tree. Based on the results of decision tree analysis, a relatively better DEA model can be chosen, which is expected to well represent the true performance of DMUs. We illustrate the effectiveness of the proposed method by applying it to the efficiency evaluation of 101 listed companies in steel and metal industry.

• Journal of Environmental Science International
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• v.2 no.3
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• pp.193-199
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• 1993

This study has two objectives. One is developing the runoff model for Hoe-Dong Reservoir basin located at the upstream of Su-Young River in Pusan. To develop the runoff model, basic hydrological parameters - curve number to find effective rainfall, and storage coefficient, etc. - should be estimated. In this study, the effective rainfall was calculated by the SCS method, and the storage coefficient used in the Clark watershed routing was cited from the report of P.E.B. The other is the derivation of transfer function for Hoe-Dong Reservoir basin. The linear, discrete, input-output model which contained six parameters was selected, and the parameters were estimated by the least square method and the correlation function method, respectively. Throughout this study, rainfall and flood discharge data were based on the field observation in 1981.8.22 - 8.23 (typhoon Gladys). It was observed that the Clark watershed routing regenerated the flood hydrograph of typhoon Gladys very well, and this fact showed that the estimated hydrological parameters were relatively correct. Also, the calculated hydrograph by the linear, discrete, input-output model showed good agreement with the regenerated hydrograph at Hoe-Dong Dam site, so this model can be applicable to other small urban areas. Key Words : runoff, effective rainfall, SCS method, clark watershed iou상ng, hydrological parameters, parameter estimation, least square method, correlation function method, input-output model, typhoon gladys.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.1
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• pp.21-26
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• 2001

In this study, we propose a two degree of freedom robust output tracking control method for a class of nonlinear system. We consider hyperbolically nonminimum phase single-input single-output uncertain nonlinear systems. We also consider the case that the nominal input-state equation is differentially flat. Nominal stable state trajectory is obtained in the flat output space via the flat output. Nominal feedforward control input is also computed from the nominal state trajectory. Due to the nature of the method, the generated flat output trajectory and control input are noncausal. Robust feedback control is designed to stabilize the systems around the nominal trajectory. A numerical example is given is given to demonstrate that robust tracking is achieved.