• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1694-1700
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• 2004

In this paper, we propose the AWLS/MFT (Adaptive Weighed Least Squares/ Modulation Function Technique) devised by A. E. Pearson et al. for the transfer function estimation of a modal system and investigate the performance of several algorithms, the Gram matrix method, a Luenberger Observer (LO), Least Squares (LS), and Recursive Least Squares (RLS), for the estimation of initial conditions. With the benefit of the Modulation Function Technique (MFT), we can separate the estimation problem into two phases: the transfer function parameters are estimated in the first phase, and the initial conditions are estimated in the second phase. The LO method produces excellent IC estimates in the noise free case, but the other three methods show better performance in the noisy case. Finally, we compared our result with the Prony based method. In the noisy case, the AWLS and one of the three methods - Gram matrix, LS, and RLS- show better performance in the output Signal to Error Ratio (SER) aspect than the Prony based method under the same simulation conditions.

• Journal of Ubiquitous Convergence Technology
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• v.2 no.2
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• pp.78-87
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• 2008

Received signal strength indicator (RSSI) is used as one of the ranging techniques to locate dynamic sensor nodes in wireless sensor network. Before it can be used for position estimation, RSSI values must be converted to distances using path loss model. These distances among sensor nodes are combined using trilateration method to find position. This paper presents an idea which attempts to integrate both path loss model and trilateration as one algorithm without going through RSSI-distance conversion. This means it is not simply formulas combination but a whole new model was developed. Several advantages were found after integration: it is able to reduce processing load, and ensure that all values do not exceed the maximum range of 16-bit signed or unsigned numbers due to antilog operation in path loss model. The results also show that this method is able to reduce estimation error while inaccurate environmental parameters are used for RSSI-distance conversion.

• Journal of the Korean Data and Information Science Society
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• v.27 no.2
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• pp.531-538
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• 2016

In this paper we deal with the small area estimation for the case that the response variables take binary values. The mixed effects models have been extensively studied for the small area estimation, which treats the spatial effects as random effects. However, when the spatial information of each area is given specifically as coordinates it is popular to use the geographically weighted logistic regression to incorporate the spatial information by assuming that the regression parameters vary spatially across areas. In this paper, relaxing the linearity assumption and propose a geographically weighted kernel logistic regression for estimating small area proportions by using basic principle of kernel machine. Numerical studies have been carried out to compare the performance of proposed method with other methods in estimating small area proportion.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.543-550
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• 2002

This work is concerned with the estimation of output derivatives and their use for the design of robust controller for linear systems with systems uncertainties due to modeling errors and disturbance. It is assumed that a nominal transfer function model and Quantitative bounds for system uncertainties are known. The developed control schemes are shown to achieve regulation of the system output and ensures boundedness of the system states without imposing any structural conditions on system uncertainties and disturbances. Output derivative estimation is first conducted trough restructuring of the plant in a specific parameterization. They are utilized for constructing robust nonlinear high-gain feedback controller of a SMC(Sliding Mode Controller) Type. The performances of the developed controller are evaluated and shown to be effective and useful through simulation study.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.325-327
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• 2003

Forest biomass is the basis of forest ecosystem. With the rapid development of remote sensing and computer technology, forest biomass estimation using remote sensing data is paid great attention and has acquired great achievements. This article focuses on discussion of methods of forest biomass estimation methods using Terra/MODIS data in Northeast China. The research include: combining the MODIS time series parameters with seasonal characteristics of forest species to identify major forest species; establishing a model to estimate forest biomass based on forest species; analyzing the effects of the existent forest biomass and increasing biomass on terrestrial carbon cycle. This research can help to make clear the mechanism of carbon cycle.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.227-237
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• 2011

This paper considers a generalized method of moments(GMM) estimation for seasonal cointegration as the extension of Kleibergen (1999). We propose two iterative methods for the estimation according to whether parameters in the model are simultaneously estimated or not. It is shown that the GMM estimator coincides in form to a maximum likelihood estimator or a feasible two-step estimator. In addition, we derive its asymptotic distribution that takes the same form as that in Ahn and Reinsel (1994).

• Journal of Power Electronics
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• v.11 no.2
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• pp.211-217
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• 2011

The dynamic response of a multi-MW wind turbine to a sudden change in wind speed is usually slow, because of the slow pitch control system. This could cause a large excursion of the rotor speed and an output power over the rated. A feedforward pitch control can be applied to minimize the fluctuations of these parameters. This paper introduces the complete design steps for a feedforward pitch controller, which consist of three stages, i.e. the aerodynamic torque estimation, the 3-dimensional lookup table for the wind seed estimation, and the calculation of the feedforward pitch amount. The effectiveness of the feedforward control is verified through numerical simulations of a multi-MW wind turbine.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.4
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• pp.330-336
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• 1996

An real-time active beacon localization system for mobile robots is developed and implemented. This system permits the estimation of robot positions when detecting light sources by PSD(Position Sensitive Detector) sensor which are placed sparsely over the robots work space as beacons(or landmarks). An LSE(Least Square Estimation) method is introduced to calibrate the internal parameters of a model for the beacon and robot position. The proposed system has two operational modes of position estimation. One is the initial position calculation by the detection of two or more light sources positions of which are known. The other is the continuous position compensation that calculates the position and heading of the robot using the IEKF(Iterated Extended Kalman Filter) applied to the beacon and dead-reckoning data. Practical experiments show that the estimated position obtained by this system is precise enough to be useful for the navigation of robots.

• Journal of The Korean Society of Agricultural Engineers
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• v.47 no.2
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• pp.87-96
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• 2005

In this research, an attempt is made to derive the practical estimation of the degree of consolidation in soft clay from field measurements under embankments. For the practical estimation of pore water pressure in soft clay, the elasto-viscous rheological model was proposed, with a transform of parameters and a field geotechnical measurements in southern Korea. By using the rheological properties of soft clays and the dissipation of excess pore water pressure behaviour during step loading, a degree of consolidation or pore water pressure estimation in the future can be performed, and are shown to be generally close to the field measurements of pore water pressure. Finally, a pore water pressure behaviour in soft clay can be explained through measured data in field and the excess pore water pressure data can also be used to estimate settlement.

• The Transactions of the Korean Institute of Power Electronics
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• v.17 no.3
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• pp.222-229
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• 2012

The SOC estimation method based on Kalman Filter(KF) requires the accurate battery model to express the electrical characteristics of the battery. However, the performance of KF SOC estimator can hardly be improved because of the nonlinear characteristic of the battery. This paper proposes the new KF SOC estimator of Lithium-Polymer Battery(LiPB), which considers the variation of parameters based on the hysteresis effect, the magnitude of SOC, the charging/discharging mode and the on/off load conditions. The proposed SOC estimation method is verified with the PSIM simulation combined the experimental data of the LiPB.