• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.305-308
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• 1988

Pole assignment controller with variable forgetting factor is generalizaed to allow the output and/or input variance to be reduced. The algorithm can give significant reductions in variance for little extra computational effort and is presented for servo-tracking using leat-squares estimation. Moreover, the use of a variable forgetting factor with correct choice of information bound can avoid 'blowing-up' of the covariance matrix of the estimates and subsequent unstable control.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.54 no.10
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• pp.497-504
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• 2005

For maximum output power, wind turbines are usually controlled at the speed which is determined by the optimal tip-speed ratio. This method requires information of wind speed and the power conversion coefficient which is varied by the pitch angle control. In this paper, a new maximum output power control algorithm using fuzzy logic control is proposed, which doesn't need this information. Instead, fuzzy controllers use information of the generator speed and the output power. By fuzzy rules, the fuzzy controller produces a new generator reference speed which gives the maximum output power of the generator for variable wind speeds. The proposed algorithm has been implemented for the 3[kW] cage-type induction generator system at laboratory, of which results verified the effectiveness of the algorithm.

• Korean Journal of Ecology and Environment
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• v.43 no.1
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• pp.161-167
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• 2010

In this study, we implemented an experimental approach of ecological model development in order to emphasize the importance of input variable selection with respect to time-delayed arrangement between input and output variables. Time-series modeling requires relevant input variable selection for the prediction of a specific output variable (e.g. density of a species). Inadequate variable utility for input often causes increase of model construction time and low efficiency of developed model when applied to real world representation. Therefore, for future prediction, researchers have to decide number of time-delay (e.g. months, weeks or days; t-n) to predict a certain phenomenon at current time t. We prepared a total of 3,900 equation models produced by Time-Series Optimized Genetic Programming (TSOGP) algorithm, for the prediction of monthly averaged density of a potamic phytoplankton species Stephanodiscus hantzschii, considering future prediction from 0- (no future prediction) to 12-months ahead (interval by 1 month; 300 equations per each month-delay). From the investigation of model structure, input variable selectivity was obviously affected by the time-delay arrangement, and the model predictability was related with the type of input variables. From the results, we can conclude that, although Machine Learning (ML) algorithms which have popularly been used in Ecological Informatics (EI) provide high performance in future prediction of ecological entities, the efficiency of models would be lowered unless relevant input variables are selectively used.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.2
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• pp.253-259
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• 2016

This paper introduces a new variable power divider circuit with an arbitrary power division ratio ranging from $1:{\infty}$ to ${\infty}:1$. The proposed power divider circuit consists of one branch-line coupler to be a good input matching characteristic, two variable phase shifters with 90-degree phase variation to be connected two output paths of the branch-line coupler, and one ring-hybrid coupler to combine output signals of two variable phase shifter. The power division ratio between the two output ports of the proposed power divider can be easily controlled by the phase variation of the two phase shifter. The proposed power divider circuit fabricates on laminated RF-35 (h = 20 mil, er=3.5; Taconic) with a center frequency of 2 GHz. The power division ratio of the fabricated prototype varies from about 1:1000 to 5000000:1, with an input reflection characteristic(S11) of below -20 dB, an insertion loss of about -1.0 dB, and an isolation characteristic of below -17 dB between two output ports in the range 1.9-2.1 GHz.

• Journal of IKEEE
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• v.23 no.4
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• pp.1353-1359
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• 2019

It is presented in this paper that the static output feedback (SOF) pole-assignment problem of some linear time-invariant systems can be completely resolved by parametrization in real Grassmann space. For the real Grassmannian parametrization, the so-called Plucker matrix is utilized as a linear matrix formula formulated from the SOF variable's coefficients of a characteristic polynomial constrained in Grassmann space. It is found that the exact SOF pole assignability is determined by the linear independency of columns of Plucker sub-matrix and by full-rank of that sub-matrix. It is also presented that previous diverse pole-assignment methods and various computation algorithms of the real SOF gains for 2-input, 2-output, 4^th order systems are unified in a deterministic way within this real Grassmannian parametrization method.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.6
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• pp.92-97
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• 1999

This paper reports by simple method that is quickly corrected the effects of fluid temperature for the hot wire anemometer. We are concerned with a variable output of hot wire anemometer on arbitrary fluid temperature. Hot wire by measuring boundary layer of turbulent flow has been calibrated by arbitrary temperature lower than 10$0^{\circ}C$, and velocity lower than 20m/s. As a result, we could pick up the temperature factor affected by output of hot wire anemometer from related in output of arbitrary temperature to output of room temperature. By using temperature factor on the output of hot wire anemometer, we also obtained that the relationship of velocity was of no effect by temperature of fluids. About results of calibrated hot wire, uncertainly of velocity is 2.15% at room temperature and 3.1% at arbitrary temperature.

• Proceedings of the KIPE Conference
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• 2013.07a
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• pp.388-389
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• 2013

This paper presents the method for the fluctuation smoothing control by using relaxation time variable control of battery. When the output power of wind farm is changed suddenly, it is necessary to control the output power of wind farm. The smoothing relaxation time is changed within limits of battery output power. Using the hybrid energy storage system (HESS) combined with battery energy storage system and electric double layer capacitor, it is possible to control the output power of wind farm. The capacity of battery is determined by considering the case of the disconnecting wind farm from the grid. To verify the proposed method, simulations are carried out by using PSCAD/EMTDC with actual data of wind farm in the Jeju Island.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.8
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• pp.698-707
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• 1990

As proved in many studies, LZW algorithm, one of the widely used compression schemes, itself contains some types of redundancy, In this paper, VV-LZW coompression algorithm is presented which encodes variable length source string into variable size codewords and reduces such redundancies that the original LZW scheme has. Experiment shows that this scheme especially has good initial compression efficiency and produces more complex output strings than the original LZW. This scheme is very useful to the data compression with small size, and the applications such as crytography.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.1059-1066
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• 2016

In this paper we propose a robust version of varying coefficient models, which is based on the regularized regression with L1 regularization. We use the iteratively reweighted least squares procedure to solve L1 regularized objective function of varying coefficient model in locally weighted regression form. It provides the efficient computation of coefficient function estimates and the variable selection for given value of smoothing variable. We present the generalized cross validation function and Akaike information type criterion for the model selection. Applications of the proposed model are illustrated through the artificial examples and the real example of predicting the effect of the input variables and the smoothing variable on the output.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.9
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• pp.1085-1094
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• 1992

A variable-spacing cesium thermionic energy conversion test station is designed and fabricated for the study of power generation. The diode is in the form of a guard-ringed plane-parallel geometry in which a polycrystalline rhenium emitter of 2 cmS02T area faces a radiation-cooled polycrystalline rhenium collector of 1.9 cmS02T area. The emission of plasma from heated refractory electrode metal is the driving reaction in the direct conversion of heat to electricity by thermionic energy conversion. The plasma is produced from electrons and positive ions formed simultaneously by thermionic emission and surface ionization of cesium atoms incident on the hot emitter from the cesium vapor in the diode. And high plasma density causes plasma multiplication within the gap due to volume ionization that results in high power output. The variation of the saturation current of a Knudsen converter is investigated at an emitter-collector gap of 0.1 mm and an emitter temperatures. A maximum power output of 13.47 watta/cmS02T is observed at a collector temperature of 963 K and a cesium reservoir temperature of 603 K.