• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.12 no.11
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• pp.1031-1037
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• 2000

Isothermal vapor-liquid equilibrium(VLE) data have been obtained for the systems of propane(R290)+1,1,1,2-tetrafluoroethane(R134a) and 1,1,1,2-tetrafluoroethane(R134a)+isobutane(R60A) in the temperature range of 253.15 to 323.15K. Experiments were performed in a circulation type apparatus by injecting vapor through liquid pool using a magnetic pump. Both systems form azeotropes in the temperature range of this study. The experimental results were estimated with the Peng-Robinson equation of state. When the temperature-dependent binary interaction parameter was used in the Peng-Robinson equation of state, the absolute average deviation of the measured bubble point pressures from the values correlated by the Peng-Robinson equation was 0.65% and 0.78% for R290+R134a and R134a+600a, respectively. Azeotropic compositions for both systems were presented.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.6
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• pp.43-52
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• 1994

A design method of rule-based fuzzy modeling is presented for the model identification of complex and nonlinear systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of ``IF....,THEN...', using the theories of optimization theory , linguistic fuzzy implication rules and fuzzy c-means clustering. Three kinds of method for fuzzy modeling presented in this paper include simplified inference (type I), linear inference (type 2), and modified linear inference (type 3). In order to identify premise structure and parameter of fuzzy implication rules, fuzzy c- means clustering and modified complex method are used respectively and the least sequare method is utilized for the identification of optimum consequence parameters. Time series data for gas furance and those for sewage treatment process are used to evaluate the performance of the proposed rule-based fuzzy modeling. Comparison shows that the proposed method can produce the fuzzy model with higher accuracy than previous other studies.

• Journal of the Korean Data and Information Science Society
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• v.19 no.4
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• pp.1353-1360
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• 2008

An estimating procedure is introduced for the nonlinear mixed-effect Poisson regression, for longitudinal study, where data from different subjects are independent whereas data from same subject are correlated. The proposed procedure provides the estimates of the mean function of the response variables, where the canonical parameter is related to the input vector in a nonlinear form. The generalized cross validation function is introduced to choose optimal hyper-parameters in the procedure. Experimental results are then presented, which indicate the performance of the proposed estimating procedure.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.5
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• pp.311-318
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• 1988

An adaptive control problem for a plant with unmodelled dynamics is studied. The upper bounds of the output due to the unmodelled dynamics and measurement noise is assumed to be known. This problem was studied by Middleton et al. They used a modified form of the least square method in estimating the plant paramaters. In this paper, the bounds of the parameters are estimated by linear programming and the parameters are estimated by the projetion type algorithm incorporating the bounds of the parameters. The stability of the proposed adaptive control system can be proved in nearly the same way as the proof of Middleton. The performance of the proposed method is found to be much better than the method of Midlleton's with respect to the parameter convergence and plant output in computer simulations.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.11 no.7
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• pp.546-551
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• 1998

$Mn{1-X}Fe{2+X}O_4, Mg_{1-X}Fe_{2+X}O_4$ (x=0.0, 0.025, 0.1, 0.2) for negative temperature coefficient (NTC) thermistor was prepared by calcination at $800^{\circ}C$ and sintering at form 1100 to $1250^{\circ}C$ with $50^{\circ}C$ intervals. The best linear property was obtained in the Mn-based sample sintered at $1200^{\circ}C$ with x=0.0 composition. Temperature coefficient of resistance, $\alpha$, was $-5.6%/^{\circ}C$ in the Mn-based sample, $-5.2%/^{\circ}C$ in the MM-based sample, and $-1.6%/^{\circ}C$ in the Mg-based sample. thermistor parameter, B, was in the range of 2665~7780 K. The results show the possibility that Mn-Ni-Co based thermistor could be substituted by the composition used in this study.

• Journal of Integrative Natural Science
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• v.7 no.2
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• pp.138-144
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• 2014

Fisher information matrix plays an important role in statistical inference of unknown parameters. Especially, it is used in objective Bayesian inference where we calculate the posterior distribution using a noninformative prior distribution, and also in an example of metric functions in geometry. To estimate parameters in a distribution, we can use the Fisher information matrix. The more the number of parameters increases, the more its matrix form gets complicated. In this paper, by using Mathematica programs we derive the Fisher information matrix for 4-parameter generalized gamma distribution which is used in reliability theory.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.686-691
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• 2011

This study is concerned with the identification of fuzzy models. To address the optimization of fuzzy model, we proposed an improved space search evolutionary algorithm (ISSA) which is realized with the combination of space search algorithm and Gaussian mutation. The proposed ISSA is exploited here as the optimization vehicle for the design of fuzzy models. Considering the design of fuzzy models, we developed a hybrid identification method using information granulation and the ISSA. Information granules are treated as collections of objects (e.g. data) brought together by the criteria of proximity, similarity, or functionality. The overall hybrid identification comes in the form of two optimization mechanisms: structure identification and parameter identification. The structure identification is supported by the ISSA and C-Means while the parameter estimation is realized via the ISSA and weighted least square error method. A suite of comparative studies show that the proposed model leads to better performance in comparison with some existing models.

• Journal of Electrical Engineering and Technology
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• v.5 no.2
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• pp.276-281
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• 2010

The switched reluctance motor (SRM) is an older member of the electric machines family. Its simple structure, ruggedness and inexpensive manufacturing potential make it extremely attractive for industrial applications. However, these merits are overshadowed by its inherent high torque ripple, acoustic noise and difficulty to control. In this paper, a control strategy of the angle position control for the SRM drive based on fuzzy logic is illustrated. The input control parameter, the output control parameter and fuzzy control with FAM table formulation strategy are described and simulated with control patterns, and the decision form of the fuzzy control is illustrated and simulated, and the scope of implementing in a Fuzzy based ASIC chip is enlightened with literature support.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.1
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• pp.60-66
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• 1996

Brushless DC(BLDC) motor have been increasingly used in machine tools and robotics applications due to the reliability and the efficiency. In control of BLDC motor, it is important to construct the controller which is robust to parameter variations and external disturbances. Variable structure controller(VSC) has been known as a powerful tool in robust control of time varying systems. In practical systems, however, VSC has a high frequency chattering which deteriorates system performances. In this paper, a binary controller(BC) which takes the form of VSC and MRAC combined is presented to solve this problem. BC consists of the primary loop controller and the external loop controller to change the gain of primary loop controller smoothly. So it can generate the continuous control input and is insensitive to parameter variations in the given domain. To confirm the validity, various investigations of control characteristics for various design parameters in a position control system of BLDC motor are carried out. (author). 11 refs., 18 figs., 1 tab.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.6
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• pp.395-401
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• 2004

By using an adaptive algorithm, together with an additional dynamic system, this paper proposes a new approach to design of a state observer for a class of uncertain systems. We enlarge the class of linear systems from the canonical form of [1] by proposing an adaptive observer that allows unknown parameters to affect those unmeasured states. The result is based on a recent result which presents a design algorithm for an additional system to replace output derivative measurements with the additional dynamics. A numerical example illustrates the design procedure of the state observer.