• Transactions of the Korean Society of Mechanical Engineers B
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• v.31 no.7 s.262
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• pp.635-643
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• 2007

An inverse radiation analysis is presented for the estimation of the radiation properties for an absorbing, emitting, and scattering media with diffusely emitting and reflecting opaque boundaries. In this study, a repulsive particle swarm optimization(RPSO) algorithm which is a relatively recent heuristic search method is proposed as an effective method for improving the search efficiency for unknown parameters. To verify the performance of the proposed RPSO algorithm, it is compared with a basic particle swarm optimization(PSO) algorithm and a hybrid genetic algorithm(HGA) for the inverse radiation problem with estimating the various radiation properties in a two-dimensional irregular medium when the measured temperatures are given at only four data positions. A finite-volume method is applied to solve the radiative transfer equation of a direct problem to obtain measured temperatures.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.8
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• pp.1534-1544
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• 2002

The TDCSA(Time Delay Control with Switching Action) method, which consists of Time Delay Control(TDC) and a switching action of sliding mode control(SMC), has been proposed as a promising technique in the robust control area, where the plant has unknown dynamics with parameter variations and substantial disturbances are preset. When TDCSA is applied to the plant with saturation nonlinearity, however, the so-called windup phenomena are observed to arise, causing excessive overshoot and instability. The integral element of TDCSA and the saturation element of a plant cause the windup phenomena. There are two integral effects in TDCSA. One is the integral effect occurred by time delay estimation of TDC. Other is the integral term of an integral sliding surface. In order to solve this problem, we have proposed an anti-windup scheme method for TDCSA. The stability of the overall system has been proved for a class of nonlinear system. Experiment results show that the proposed method overcomes the windup problem of the TDCSA.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.12
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• pp.176-184
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• 2000

TDC(Time Delay Control) deals with the time-varying system parameters, unknown dynamics and unexpected disturbances using time delay. TDC can be divided into two separate parts: an auxiliary controller and a servo controller. The two controllers can be designed independently. The auxiliary controller is used to reduce sensitivity to parameter variations, nonlinear effects, and other disturbances. The servo controller is to reduce the error between the desired command and output. We propose the model-following time delay controller with modified error feedback controller. This was applied to follow the desired reference model for the uncertain time-varying overhead crane. The model generates the damped-out swinging motion trajectory to suppress the swinging motion caused by the acceleration and the deceleration of crane transportation. The control performance was evaluated through simulations. The theoretical results indicate that this control method shows excellent performance to an overhead crane with the uncertain time-varying parameters.

• Journal of the Korean Statistical Society
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• v.30 no.2
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• pp.179-192
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• 2001

When a statistical model has a hierarchical structure such as multilayer perceptrons in neural networks or Gaussian mixture density representation, the model includes distribution with unidentifiable parameters when the structure becomes redundant. Since the exact structure is unknown, we need to carry out statistical estimation or learning of parameters in such a model. From the geometrical point of view, distributions specified by unidentifiable parameters become a singular point in the parameter space. The problem has been remarked in many statistical models, and strange behaviors of the likelihood ratio statistics, when the null hypothesis is at a singular point, have been analyzed so far. The present paper studies asymptotic behaviors of the maximum likelihood estimator and the Bayesian predictive estimator, by using a simple cone model, and show that they are completely different from regular statistical models where the Cramer-Rao paradigm holds. At singularities, the Fisher information metric degenerates, implying that the cramer-Rao paradigm does no more hold, and that he classical model selection theory such as AIC and MDL cannot be applied. This paper is a first step to establish a new theory for analyzing the accuracy of estimation or learning at around singularities.

• Journal of Environmental Science International
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• v.17 no.11
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• pp.1295-1305
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• 2008

This study aims at the analyze of unsteady downstream flow due to dam failure along dam failure scenario and applied to Yeoncheon Dam which was collapsed August 1st 1999, using HEC-RAS simulation model. The boundary conditions of this unsteady flow simulation are that dam failure arrival time could be at 02:45 a.m. August 1st 1999 and failure duration time could be also 30 minutes. Downstream 19.5 km from dam site was simulated for unsteady flow analysis in terms of dam failure and non-failure cases. For the parameter calibration, observed data of Jeonkok station were used and roughness coefficient was applied to simulation model. The result of the peak discharge difference was 2,696 to $1,745\;m^3/sec$ along the downstream between dam failure and non-failure and also peak elevation of water level showed meanly 0.6m difference. Those results of these studies show that dam failure scenarios for the unknown failure time and duration were rational because most results were coincident with observed records. And also those results and procedure could suggest how and when dam failure occurs and downstream unsteady flow analyzes.

• The Korean Journal of Applied Statistics
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• v.27 no.4
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• pp.589-603
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• 2014

When consecutive data follows different distributions(depending on the time interval) change-point detection infers where the changes occur first and then finds further inferences for each sub-interval. In this paper, we investigate the Bayesian detection of multiple change points. Utilizing the reversible jump MCMC, we can explore parameter spaces with unknown dimensions. In particular, we consider a model where the signal is a piecewise linear function. For the Bayesian inference, we propose a new Bayesian structure and build our own MCMC algorithm. Through the simulation study and the real data analysis, we verified the performance of our method.

• Smart Structures and Systems
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• v.4 no.3
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• pp.319-342
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• 2008

Identification of the nonlinear hysteretic behavior of a reinforced concrete (RC) bridge pier subjected to earthquake loads is carried out based on acceleration measurements of the earthquake motion and bridge responses. The modified Takeda model is used to describe the hysteretic behavior of the RC pier with a small number of parameters, in which the nonlinear behavior is described in logical forms rather than analytical expressions. Hence, the modified extended Kalman filter is employed to construct the state transition matrix using a finite difference scheme. The sequential modified extended Kalman filter algorithm is proposed to identify the unknown parameters and the state vector separately in two steps, so that the size of the problem for each identification procedure may be reduced and possible numerical problems may be avoided. Mode superposition with a modal sorting technique is also proposed to reduce the size of the identification problem for the nonlinear dynamic system with multi-degrees of freedom. Example analysis is carried out for a continuous bridge with a RC pier subjected to earthquake loads in the longitudinal and transverse directions.

• Wind and Structures
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• v.26 no.6
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• pp.383-395
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• 2018

An accurate determination of wind speed distribution is the basis for an evaluation of the wind energy potential required to design a wind turbine, so it is important to estimate unknown parameters of wind speed distribution. In this paper, Gumbel distribution is used in modelling wind speed data, and alternative robust estimation methods to estimate its parameters are considered. The methodologies used to obtain the estimators of the parameters are least absolute deviation, weighted least absolute deviation, median/MAD and least median of squares. The performances of the estimators are compared with traditional estimation methods (i.e., maximum likelihood and least squares) according to bias, mean square deviation and total mean square deviation criteria using a Monte-Carlo simulation study for the data with and without outliers. The simulation results show that least median of squares and median/MAD estimators are more efficient than others for data with outliers in many cases. However, median/MAD estimator is not consistent for location parameter of Gumbel distribution in all cases. In real data application, it is firstly demonstrated that Gumbel distribution fits the daily mean wind speed data well and is also better one to model the data than Weibull distribution with respect to the root mean square error and coefficient of determination criteria. Next, the wind data modified by outliers is analysed to show the performance of the proposed estimators by using numerical and graphical methods.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.12
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• pp.54-60
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• 2005

In this paper, fault tolerant control for aircraft is being discussed. The authors propose a fault tolerant control algorithm based on time delay control. Time delay control is an effective method to deal with unknown dynamics. The proposed algorithm has no parameter to be updated and needs no prior information of faults. These are the primary advantages of the proposed method. The algorithm uses output feedback. The design and the stability condition are presented by following the existing proof. The proposed algorithms are verified by simulation examples.

• Earthquakes and Structures
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• v.3 no.1
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• pp.59-81
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• 2012

A ductility inverse-mapping method for SDOF systems including passive dampers is proposed which enables one to find the maximum acceleration of ground motion for the prescribed maximum response deformation. In the conventional capacity spectrum method, the maximum response deformation is computed through iterative procedures for the prescribed maximum acceleration of ground motion. This is because the equivalent linear model for response evaluation is described in terms of unknown maximum deformation. While successive calculations are needed, no numerically unstable iterative procedure is required in the proposed method. This ductility inverse-mapping method is applied to an SDOF model of bilinear hysteresis. The SDOF models without and with passive dampers (viscous, viscoelastic and hysteretic dampers) are taken into account to investigate the effectiveness of passive dampers for seismic retrofitting of building structures. Since the maximum response deformation is the principal parameter and specified sequentially, the proposed ductility inverse-mapping method is suitable for the implementation of the performance-based design.