• Proceedings of the Korea Society for Simulation Conference
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• 1999.04a
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• pp.212-216
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• 1999

We propose a method for simulation optimization using stochastic genetic algorithm(GA) to get the best design and operating policies in a Direct-Input-Output Automated Manufacturing System (DIOMS).

• Journal of IKEEE
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• v.22 no.1
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• pp.110-120
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• 2018

In this paper, we apply the input-output linearization technique to tracking the follow-up trajectory r(t) in the ball-beam system. There exist system disturbance and various uncertainties, the conventional input-output linearization based control yields some noticeable errors in tracking performance. As a result, a new robust control technique for the uncertainty of the system was proposed and its improved performance verified through simulation and experimental results. So, more realistic system model is obtained with unmatched uncertainties and disturbance. Then, in order to improve the control performance, a new optimal bang-bang control input is additionally added.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.21 no.3
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• pp.213-216
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• 2008

The voltages for pixel electrodes on LCD panels are supplied with analog voltages from LCD Driver ICs (LDIs). The latest LDI developed for large LCD TV's has suffered from the degradation of analog output characteristics (target voltage: AVO and output voltage deviation: dVO). By the failure analysis, humps in $I_D-V_G$ curves have been observed in high voltage (HV) NMOS devices for input transistors in amplifiers. The hump is investigated to be the main cause of the deviation for the driving current in HV NMOS transistors. It also makes the matching between two input transistors worse and consequently aggravates the analog output characteristics. By simply modifying the active layout of HV NMOS transistors, this hump was removed and the analog characteristics (AVO &dVO) were improved significantly. In the help of the improved analog characteristics, it also became possible to reduce the size of the input transistors less than a half of conventional transistors and significantly improve the integration density of LDIs.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.376-378
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• 1996

This paper presents a new PFC control method which replaces a fast line current measurement with a filtered load current measurement. Using the power balance relation between the input and the output of the boost converter. the input current can be described as the function of load current. Thus the PWM signal which effects the switching control of the boost converter is generated using the PFC input voltage, the PFC output voltage and the load current as input variables. By using a filter between the bridge rectifier and a dc-to-dc converter, the input voltage of the dc-to-dc converter is forced to always maintain above zero volt. Then the input current traces a sinewave in phase. The proposed scheme accomplishes a very high power factor and a low harmonic distortion of the line current. The validity of this scheme is demonstrated through simulation.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.601-604
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• 2000

In this paper, we compare the classification performance of both data fusion and clustering algorithms (Data Bagging, Variable Selection Bagging, Parameter Combining, Clustering) to logistic regression in consideration of various characteristics of input data. Four factors used to simulate the logistic model are (1) correlation among input variables (2) variance of observation (3) training data size and (4) input-output function. Since the relationship between input & output is not typically known, we use Taguchi design to improve the practicality of our study results by letting it as a noise factor. Experimental study results indicate the following: Clustering based logistic regression turns out to provide the highest classification accuracy when input variables are weakly correlated and the variance of data is high. When there is high correlation among input variables, variable bagging performs better than logistic regression. When there is strong correlation among input variables and high variance between observations, bagging appears to be marginally better than logistic regression but was not significant.

• Nuclear Engineering and Technology
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• v.33 no.5
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• pp.457-467
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• 2001

It is well known that the performance of a fuzzy neural network strongly depends on the input features selected for its training. In its applications to sensor signal estimation, there are a large number of input variables related with an output As the number of input variables increases, the training time of fuzzy neural networks required increases exponentially. Thus, it is essential to reduce the number of inputs to a fuzzy neural network and to select the optimum number of mutually independent inputs that are able to clearly define the input-output mapping. In this work, principal component analysis (PCA), genetic algorithms (CA) and probability theory are combined to select new important input features. A proposed feature selection method is applied to the signal estimation of the steam generator water level, the hot-leg flowrate, the pressurizer water level and the pressurizer pressure sensors in pressurized water reactors and compared with other input feature selection methods.

• Journal of Korea Technology Innovation Society
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• v.21 no.4
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• pp.1313-1344
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• 2018

This study aims at investigating the effects of Government R&D subsidies. We analyse the effects of inputs and behavioral additionality on the output additionality. We also measure the moderate effects of the experiences of benefiting from government R&D on the relationship between inputs and behavioral additionality and the output additionality. We conducted a structured questionnaire on the companies who have participated in promotion program of the Korea Innovation Cluster. 126 responses were collected and alnalysed using the OLS technique. Empirical results show that the relationship between input/behavioral additionality (management, follow-up, cognitive capacity) and output additionality had positive effect. The moderating effects of experiences of R&D subsidy on the relationship between input additionality and output additionality and the relationship between cognitive additionality and the output additionality appear to be statistically significant.

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.270-273
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• 2000

A new phase shift PWM parallel-input/series-output modularized dual converter is proposed in this paper. This converter is operated with a fixed duty ratio and its output voltage is regulated by phase shift between each module. Since the operating duty ratio of each module is fixed it is sufficient to implement a simple open loop drive circuitry for each module and the cost of total system can be much reduced. The operation of the converter is analyzed in this paper and verified by computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1213-1218
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• 1993

Variable structure control is applied to the robust output tracking control problem of general nonlinear multi-input multi-output (MIMO) systems. Using the concept of relative degree and minimum phase, input/output(I/O) linearization is undertaken. For I/O the linearized system, a new sliding hyperplanes design method is proposed. In this procedure, we can construct very robust and efficient sliding mode controller for general nonlinear systems of relative degree higher than two. The control results are illustrated by adopting a numerical example.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.301-314
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• 2007

The aim of this paper is to deal with a method to construct a separate fuzzy regression model with crisp input and fuzzy output data using a best response function for the center and the width of the predicted output. Also we introduce the crisp mean and variance of the predicted fuzzy value and also give some examples to compare a performance of the proposed fuzzy model with various other fuzzy regression model.