• Korean Journal of Remote Sensing
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• v.29 no.6
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• pp.589-593
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• 2013

Sea Surface Temperature (SST) is the temperature close to the ocean's surface and affects the Earth's atmosphere as an important parameter for the climate circulation and change. The SST from satellite still has biases from the error in specifying retrieval coefficients from either forward modeling or instrumental biases. So in this paper, we performed sensitivity analysis using input parameter of the SST to notice that the SST is most affected among the input parameter. We used Infrared (IR) data from the Communication, Ocean, and Meteorological Satellite (COMS)/Meteorological Imager (MI) from April 2011 to March 2012. We also used the Global Space-based Inter-Calibration System (GSICS) correction to quality of the IR data from COMS. SST was calculated by substituting the input parameters; IR data with or without the GSICS correction. The results of this sensitivity analysis, the SST was sensitive from -0.0403 to 0.2743 K when the IR data were changed by the GSICS corrections.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2406-2412
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• 2015

Multi-user multi-input multi-output (MU-MIMO) system has attracted the 4^th generation wireless network as one of core technique for performance enrichment. In this system rate control is a challenging problem and another problem is optimization. Proper scheduling can resolve these problems by deciding which set of user and at which rate the users send their data. This paper proposes a new multi-parameter based scheduling (MPS) for downlink multi-user multiple-input multiple-output (MU-MIMO) system under space-time block coding (STBC) transmissions. Goal of this MPS scheme is to offer improved link level performance in terms of a low average bit error rate (BER), high packet delivery ratio (PDR) with improved resource utilization and service fairness among the user. This scheme allows the set of users to send data based on their channel quality and their demand rates. Simulation compares the MPS performance with other scheduling scheme such as fair scheduling (FS), normalized priority scheduling (NPS) and threshold based fair scheduling (TFS). The results obtained prove that MPS has significant improvement in average BER performance with improved resource utilization and fairness as compared to the other scheduling scheme.

• 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.

• Korean Management Science Review
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• v.29 no.3
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• pp.81-89
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• 2012

Since introduced by Vining and Myers in 1990, the concept of dual response approach based on response surface methodology has widely been investigated and adopted for the purpose of robust design. Separately estimating mean and variance responses, dual response approach may take advantages of optimization modeling for finding optimum settings of input factors. Explicitly assuming functional relationship between responses and input factors, however, it may not work well enough especially when the behavior of responses are poorly represented. A sufficient number of experimentations are required to improve the precision of estimations. This study proposes an alternative to dual response approach in which additional experiments are not required. An artificial neural network has been applied to model relationships between responses and input factors. Mean and variance responses correspond to output nodes while input factors are used for input nodes. Training, validating, and testing a neural network with empirical process data, an artificial data based on the neural network may be generated and used to estimate response functions without performing real experimentations. A drug formulation example from pharmaceutical industry has been investigated to demonstrate the procedures and applicability of the proposed approach.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2216-2218
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• 2002

A system identification is to measure the output in the presence of a adequate input for the controlled system and to estimate the mathematical model in the basic of input output data. 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. In recent the adjusted least squares method is suggested as a consistent estimation method in the system identification not with the observed noise input but with the observed noise output. In this paper we have developed the adjusted least squares method from the least squares method and have made certain of the efficiency in comparing the estimating results with the generating data by the computer simulations.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1189-1196
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• 2010

This paper provides an identification method for three-parameter models i.e. first order with dead time models and second order with dead time models. The proposed identification method is based on step response and can be easily implemented using digital microprocessors. The proposed method first identifies the order of the plant i.e. first order or second order from the behavior of the plant with constant input. After the order of the plant is determined, a test step input is applied to the system and the three parameters of the plant are obtained from the corresponding response of the plant. The output of the plant need not to be zero when the test signal is applied. The efficacy of proposed algorithms is verified through simulation and experiment.

• Journal of Advanced Marine Engineering and Technology
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• v.27 no.7
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• pp.852-861
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• 2003

In this paper, in order to improve the disadvantages of the fixed design-parameter fuzzy PID controller. a new fuzzy PID controller named a variable design-parameter fuzzy PID controller is suggested. The main characteristic of the suggested controller is to adjust design-parameters of the controller by comparing magnitudes between fuzzy controller inputs at each sampling time when controller inputs are measured. As a result. all fuzzy input partitioned spaces converge within a time-varying normalization scale. and the resultant PID control action can always be applied precisely regardless of operating input magnitudes. In order to verify the effectiveness of the suggested controller. several a computer simulations for a nonlinear system are executed and the control parameters of the variable design-parameter fuzzy PID controller are throughly analyzed.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.2 s.107
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• pp.207-213
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• 2006

In our previous research, we proposed a robust saturation controller which involves both control input saturation and structured real parameter uncertainties. This controller can analytically prescribed the upper and lower bounds of parameter uncertainties, and guarantee the closed-loop robust stability of the system in the presence of actuator's saturation. And the availability and the effectiveness of the proposed robust saturation controller were verified through numerical simulations. In this paper, we verify the robust stability of this controller through experimental tests. Expecially, we show unstable cases of other controllers in comparison with this controller. Experimental tests are carried out in the laboratory using a two-story test structure with a hydraulic-type active mass damper.

• The Transactions of the Korean Institute of Power Electronics
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• v.23 no.5
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• pp.321-327
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• 2018

DC microgrid system composed of multiple converters has a tendency to make the system unstable due to the interaction of converters. To solve this problem, in this paper, the interaction between cascaded converters with LC input filter is analyzed with impedance modeling using g-parameter. The input impedance and the output impedance of the system can be obtained through this technique. The stability of the system can be determined by applying Middlebrook's stability criterion to the impedance. Virtual impedance is added to the controller to enhance stability. The validity of the analysis is verified by the result of several simulations and experiments.

• Journal of the Korea Institute of Military Science and Technology
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• v.3 no.2
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• pp.71-80
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• 2000

In Underwater Flight Vehicle depth control system, the followings must be required. Firstly, It need robust depth control performance which can get over parameter variation, modeling error and disturbance. Secondly, It need no oveshoot phenomenon to avoid colliding with ground surface and obstables. Thirdly, It need continuous control input to reduce the acoustic noise and propulsion energy consumption. Finally, It need effective interpolation method which can reduce the dependency of control parameters on speed. To solve these problems, we propose the Fuzzy-PID depth controller with the control parameter interpolators. Simulation results show the proposed control scheme has robust and accurate performance with continuous control input.