• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.3
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• pp.407-412
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• 2012

This study investigated the process of thermal-induced growth of micro-crack developed at the crystalline solar cell using EL image, determined the output characteristic according to the pattern of micro-crack, analyzed the I-V characteristic according to the pattern of crack growth, and predicted the output value using simulation. The purpose of this study was, therefore, to investigate the process of thermal-induced growth of micro-crack developed at the early stage of PV module completion using EL image, to analyze the resulting decrement of output and predict the output value using simulation. It was observed that the crack grew increasingly by the thermal condition, and accordingly the lowering of output was accelerated. The output values of crack patterns with various direction were predicted using simulation, resulting in close I-V curve with only around 4% of error rate. It is considered that it is possible to predict the electric characteristic of solar cell module using only pattern of micro-crack occurred at solar cell based on our results.

• Journal of Power Electronics
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• v.17 no.1
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• pp.1-10
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• 2017

This paper presents a novel predictive digital control method for boundary conduction mode PFC converters without the need for detecting the inductor current. In the proposed method, the inductor current is predicted by analytical equations instead of being detected by a sensing-resistor. The predicted zero-crossing point of the inductor current is determined by the values of the input voltage, output voltage and predicted inductor current. Importantly, the prediction of zero-crossing point is achieved in just a single switching cycle. Therefore, the errors in predictive calculation caused by parameter variations can be compensated. The prediction of the zero-crossing point with the proposed method has been shown to have good accuracy. The proposed method also shows high stability towards variations in both the inductance and output power. Experimental results demonstrate the effectiveness of the proposed predictive digital control method for PFC converters.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.3
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• pp.559-564
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• 2010

The GMDH(Group Method of Data Handling) algorithm can be used to predict the complex nonlinear systems. The traditional GMDH algorithm produces the prdicted output of the system model in the output layer through the input layer and the intermediate layers as the prescribed process. The outputs of each layer are produced only by the outputs of the former layer. However, in the traditional GMDH algorithm, though the optimal structure of each layer is derived, the overall structure may not be derived optimally. To overcome this problem, GMDH prediction model which has the overall optimal structure is constructed by feeding back the error between the predicted output and the real output. This can make the prediction more precise. The capability improvement of the proposed algorithm compared to the traditional algorithm is verified through computer simulation.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.627-630
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• 2002

A methodology based on factorial design and Motto Carlo methods is developed and implemented for incorporating uncertainties within a multiphase subsurface flow and transport simulation system. Due to uncertainties in intrinsic permeability and longitudinal dispersivity, the predicted output is also uncertain based on the well-developed multiphase compositional simulator. The simulation results reveal that the uncertainties in input parameters pose considerable influences on the predicted output, and the mean and variance of permeability will have significant impacts on the modeling output. The proposed method offers an effective tool for evaluating uncertainty in multiphase flow simulation system.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1000-1003
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• 1996

Nonlinear unified predictive control(UPC) algorithm was applied to the temperature control of a batch polymerization reactor for polymethylmethacrylate(PMMA). Before the polymerization reaction is initiated, the parameters of the process model are determined by the recursive least squares(RLS) method. During the reaction, nonlinearities due to generation of heat of reaction and variation of heat transfer coefficients are predicted through the nonlinear model developed. These nonlinearities are added to the process output from the linear process model. And then, the predicted process output is used to calculate the control output sequence. The performance of nonlinear control algorithm was verified by simulation and compared with that of the linear unified predictive control algorithm. In the experiment of a batch PMMA polymerization, nonlinear unified predictive control was implemented to regulate the temperature of the reactor, and the validity of the nonlinear model was verified through the experimental results. The performance of the nonlinear controller turned out to be superior to that of the linear controller for tracking abrupt changes in setpoint.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.5
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• pp.52-61
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• 1993

This paper deals with adaptive control method of a robot manipulator with one-flexible link. ARMA model is used as a prediction and estimation model, and adaptive control scheme consists of parameter estimation part and adaptive controller. Parameter estimation part estimates ARMA model's coefficients by using recursive least-squares(RLS) algorithm and generates the predicted output. Variable forgetting factor (VFF) is introduced to achieve an efficient estimation, and adaptive controller consists of reference model, error dynamics model and minimum prediction error controller. An optimal input is obtained by minimizing input torque, it's successive input change and the error between the predicted output and the reference output.

• Tribology and Lubricants
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• v.32 no.4
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• pp.107-112
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• 2016

This paper presents a rotordynamic analysis of the reduction gear system applied to the 250 kW super critical CO₂ cycle. The reduction gear system consists of an input shaft, intermediate shaft, and output shaft. Because of the high rotating speed of the input shaft, we install tilting pad bearings, rolloer bearings support the intermediate and output shafts. To predict the tilting pad bearing performance, we calculate the applied loads to the tilting pad bearings by considering the reaction forces from the gear. In the rotordynamic analysis, gear mesh stiffness results in a coupling effect between the lateral and torsional vibrations. The predicted Campbell diagram shows that there is not a critical speed lower than the rated speed of 30,000 rpm of the input shaft. The predicted modes on the critical speeds are the combined bending modes of the intermediate and output shaft, and the lateral vibrations dominate when compared to the torsional vibrations. The damped natural frequency does not strongly depend on the rotating speeds, owing to the relatively low rotating speed of the intermediate and output shaft and constant stiffness of the roller bearing. In addition, the logarithmic decrements of all the modes are positive; therefore all modes are stable.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.934-938
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• 1989

This paper considers the model predictive control (MPC) problems in nonlinear processes or systems. The MPC method determines the control law such that the predicted output based on the identified process model is equal to the reference output which consists of both the process output at current time and the setting value called as the command generator. In this paper, the nonlinear MPC software for a chemical reactor is developed and analized from the point of view of practical applications.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.218-223
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• 1993

In this paper, we modify a multiple target angle tracking algorithm presented by Sword et al.. The predicted estimates, instead of the existing estimates, of the target angles are updated by the most recent output of the sensor array to improve the tracking performance of the algorithm for crossing targets. Also, the least square solution is modified to avoid abnormally large angle innovations when the target angles are very close. The improved performance of the proposed algorithm is demonstrated by computer simulations.