• Journal of Advanced Marine Engineering and Technology
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• v.20 no.3
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• pp.154-161
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• 1996

A neural predictive tracking system for the control of structure-unknown dynamic system is presented. The control system comprises a neural network modelling mechanism for the the forward and inverse dynamics of a plant to be controlled, a feedforward controller, feedback controller, and an error prediction mechanism. The feedforward controller, a neural network model of the inverse dynamics, generates feedforward control signal to the plant. The feedback control signal is produced by the error prediction mechanism. The error predictor adopts the neural network models of the forward and inverse dynamics. Simulation results are presented to demonstrate the applicability of the proposed scheme to predictive tracking control problems.

• Smart Structures and Systems
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• v.23 no.2
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• pp.123-139
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• 2019

Impact forces induced by external object collisions can cause serious damages to civil engineering structures. While accurate and prompt identification of such impact forces is a critical task in structural health monitoring, it is not readily feasible for civil structures because the force measurement is extremely challenging and the force location is unpredictable for full-scale field structures. This study proposes a novel approach for identification of impact force including its location and time history using a small number of multi-metric observations. The method combines an augmented Kalman filter (AKF) and Genetic algorithm for accurate identification of impact force. The location of impact force is statistically determined in the way to minimize the AKF response estimate error at measured locations and then time history of the impact force is accurately constructed by optimizing the error co-variances of AKF using Genetic algorithm. The efficacy of proposed approach is numerically demonstrated using a truss and a plate model considering the presence of modelling error and measurement noises.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.83-86
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• 2005

This paper presents a method for point-based 3D building reconstruction using LiDAR data and digital map. The proposed method consists of three processes: extraction of building roof points, identification of roof types, and 3D building reconstruction. After extracting points inside the polygon of building, the ground surface, wall and tree points among the extracted points are removed through the filtering process. The filtered points are then fitted into the flat plane using ODR(Orthogonal Distance Regression). If the fitting error is within the predefined threshold, the surface is classified as a flat roof. Otherwise, the surface is fitted and classified into a gable or arch roof through RMSE analysis. Based on the roof types identified in automated fashion, the 3D building reconstruction is performed. Experimental results showed that the proposed method classified successfully three different types of roof and that the fusion of LiDAR data and digital map could be a feasible method of modelling 3D building reconstruction.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.7
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• pp.950-955
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• 2014

In this paper, we propose a drug treatment protocol for the three state HIV infection model that explicitly includes the concentration of healthy T cells, infected T cells, and HIV. While most of the previous methods are not able to achieve the treatment goal in the presence of modelling errors, the proposed method is designed so as to compensate for the model uncertainties. Based on the Jacobain linearization of nonlinear HIV infection model, disturbance observer(DOB) based control is employed to design the drug treatment for the HIV patients. Computer simulation is carried out for nonlinear model in order to compare the performance of the proposed method with that of the conventional technique. The simulation results show that, in the presence of parameter uncertainties, the substantial improvement in the performance can be achieved by the proposed DOB controller.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1998.04a
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• pp.419-425
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• 1998

This paper presents a method of enhancing the accuracy of hybrid modelling that predicts dynamic characteristics of the coupled structure by synthesizing after FE analysis and vibration experimental analysis of the relevant individual substructure. Since most FE models in engineering problems are very large, dynamic analysis with the full FE model is costly. Frequency response function(FRF) synthesis after reducing the FE model can reduce this computational cost but introduce mode truncation error similarly in the case of considering only low-frequency mode after eigensolutions of the complete structure. This paper introduces a FRF of FE model for hybrid FRF synthesis, which is reduced by using IIRS methods and compensated through eigensolutions of the reduced model, and shows the effectiveness of the presented method.

• Proceedings of the KSME Conference
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• 2001.11b
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• pp.83-88
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• 2001

This paper presents modelling and analyzing method of centrifugal chiller which has a rated capacity of 200 RT(703 kW) through on-site performance test. Field data of chiller installed in the clean-room building of KIST have been collected, Simple models were developed for predicting the heat exchangers and system performances by regression of chiller operation data during 5 days in August. The models proposed here account for the effect of variations of cooling capacity, temperatures and flow rates of secondary fluids. The models are consistent with real performance data from June to September within ${\pm}5%$ error. The COP of centrifugal chiller are estimated under the standard rating conditions and reduced mass flow rate of chilled and cooling water.

• Proceedings of the Korean Statistical Society Conference
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• 2005.11a
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• pp.159-165
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• 2005

Recently, as a result of the growing interest in modelling stationary processes with discrete marginal distributions, several models for integer valued time series have been proposed in the literature. One of theses models is the integer-valued autoregressive(INAR) models. However, when modelling with integer-valued autoregressive processes, there is not yet distributional properties of forecasts, since INAR process contain an accrued level of complexity in using the Steutal and Van Harn(1979) thinning operator 'o'. In this study, a manageable expression for the asymptotic mean square error of predicting more than one-step ahead from an estimated poisson INAR(1) model is derived. And, we present a bootstrap methods developed for the calculation of forecast interval limits of INAR(p) model. Extensive finite sample Monte Carlo experiments are carried out to compare the performance of the several bootstrap procedures.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.10
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• pp.1454-1459
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• 2015

In this paper, a drug treatment protocol is proposed for an HIV infection model that explicitly includes the concentration of healthy T cells, infected T cells, and HIV. Since real parameters of HIV infection model differ from patient to patient, most drug treatment protocols are not able to achieve the treatment goal in the presence of modelling errors. Recently, based on the nonlinear robust control theory, a robust treatment protocol has been proposed that deals with parameter uncertainties. Although the developed scheme is inherently complex, it cannot be applied to the case where all parameters are unknown. In this paper, we propose a new drug treatment protocol that is much simpler than the previous one but can achieve the treatment goal even when all model parameters are unknown. The simulation results verify that the substantial improvement in the performance can be achieved by the proposed scheme.

• Nuclear Engineering and Technology
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• v.55 no.1
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• pp.373-377
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• 2023

The Monte Carlo (MC) method has become an indispensable part of the nuclear radiation research field. Several widely used and well-known MC packages were developed for simulation of radiation transport and interaction with matter. All these MC packages require users to prepare an input script. The input script can become lengthy for complex models. The process of preparing these input scripts is time-consuming and error-prone. In the present work, we have developed an open-source GUI computer program for modelling radiation transport and interaction in multi-segmented slab phantoms using grid-based system for the widely used PHITS MC package. The developed tools would be useful for future users of PHITS MC package and particularly inexperienced users. The present program is distributed under GPL license and all users can freely download, modify and redistribute the program without any restrictions.

• Journal of Power System Engineering
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• v.12 no.6
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• pp.42-49
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• 2008

The most important job in the container terminal area is to handle the cargo effectively in the limited time. To achieve this object, many strategies have been introduced and applied to. If we consider the automated container terminal, it is necessary that the cargo handling equipments are equipped with more intelligent control systems. From the middle of the 1990's, an automated rail-mounted gantry crane(RMGC) and rubber-tired gantry crane(RTG) have been developed and widely used to handle containers in the yards. Recently, in these cranes, the many equipments like CCD cameras and sensors are mounted to cope with the automated terminal environment. In this paper, we try to support the development of more intelligent automated cranes which make the cargo handling be performed effectively in the yards. For this plant, the modelling, tracking control, anti-sway system design, skew motion suppressing and complicated motion control and suppressing problems must be considered. Especially, in this paper, the system modelling and tracking control approach are discussed. And, we design the tracking control system incorporating an observer based on the 2DOF servo system design approach to obtain the desired state informations. In the case of observer design, a weighted $H_{\infty}$ error bound approach for a state estimator is considered. Based on an algebraic Riccati equation(inequality) approach, a necessary and sufficient condition for the existence of a full-order estimator which satisfies the weighted $H_{\infty}$ error bound is introduced. Where, the condition for existence of the estimator is denoted by a Linear Matrix Inequality(LMI) which gives an optimized solution and observer gain. Based on this result, we apply it to the tracking control system design for the transfer crane.