• The Journal of Korea Robotics Society
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• v.17 no.1
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• pp.40-47
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• 2022

A reward function suitable for a task is required to manipulate objects through reinforcement learning. However, it is difficult to design the reward function if the ample information of the objects cannot be obtained. In this study, a demonstration-based object manipulation algorithm called stochastic exploration guided by demonstration (SEGD) is proposed to solve the design problem of the reward function. SEGD is a reinforcement learning algorithm in which a sparse reward explorer (SRE) and an interpolated policy using demonstration (IPD) are added to soft actor-critic (SAC). SRE ensures the training of the critic of SAC by collecting prior data and IPD limits the exploration space by making SEGD's action similar to the expert's action. Through these two algorithms, the SEGD can learn only with the sparse reward of the task without designing the reward function. In order to verify the SEGD, experiments were conducted for three tasks. SEGD showed its effectiveness by showing success rates of more than 96.5% in these experiments.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.10
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• pp.130-138
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• 1996

In general, the scattler is observed in fatigue test data due to the nonhomogeneity of a material. Consequently. It is necessary to use the statistical method to describe the fatigue crack growth process precisely. Bogdanoff and Kozin suggested and developed the B-model which is the probabilistic models of cumulative damage using the Markov process in order to describe the damage process. But the B-model uses only constant probability ratior(r), so it is not consistent with the actual damage process. In this study, the r-decreasing model using a monotonic decreasing function is introduced to improve the B-model. To verify the model, thest data of fatigue crack growth of A12024-T351 and A17075-T651 are used. Compared with the empirical distribution of test data, the distribution from the r-decreasing model is satisfactory and damage process is well described from the probabilistic and physical viewpoint.

• Communications for Statistical Applications and Methods
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• v.29 no.6
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• pp.679-694
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• 2022

Mortality risk is a significant threat to individual life, and quantifying the risk is necessary for making a national population plan and is a traditionally fundamental task in the insurance and annuity businesses. Like other advanced countries, the sustainability of life pensions and the management of longevity risks are becoming important in Asian countries entering the era of aging society. In this study, mortality and pension value sustainability trends are compared and analyzed based on national population and mortality data, focusing on four Asian countries from 1990 to 2017. The result of analyzing the robustness and accuracy of generalized linear/nonlinear models reveals that the Cairns-Blake-Dowd model, the nonparametric Renshaw-Haberman model, and the Plat model show low stability. The Currie, CBD M5, M7, and M8 models have high stability against data periods. The M7 and M8 models demonstrate high accuracy. The longevity risk is found to be high in the order of Taiwan, Hong Kong, Korea, and Japan, which is in general inversely related to the population size.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.4
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• pp.120-131
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• 2004

In this paper, we propose the method of a motion planning generation in which the movement of the 3-link leg subsystem is constrained to a slider-link and a singular posture can be easily avoided. The proposed method is the jumping control moving in vertical direction which mimics a cat's behavior. That is, it is jumping toward wall and kicking it to get a higher-place. Considering the movement from the point of constraint mechanical system, the robotic system which realizes the motion changes its configuration according to the position and it has several phases such as; ⅰ) an one-leg phase, ⅱ) in an air-phase. In other words, the system is under nonholonomic constraint due to the reservation of its momentum. Especially, in an air-phase, we will use a control method using state transformation and linearization in order to control the landing posture. Also, an iterative learning control algorithm is applied in order to improve the robustness of the control. The simulation results for jumping control will illustrate the effectiveness of the proposed control method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.8
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• pp.1132-1137
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• 2013

This paper considers the $H_{\infty}$ control problem for networked control systems(NCSs). In order to solve the problem which comes from discontinuous control signal in NCSs, an approach that discontinuous control signals treat time-varying delayed continuous signals is applied to achieve $H_{\infty}$ stability of NCSs. In addition, randomly occurring packet losses and disturbances are considered by introducing stochastic variables with Bernoulli distribution. Based on Lyapunov stability theory, a new stability condition is obtained via linear matrix inequality formulation to find the $H_{\infty}$ controller which achieves the mean square stability of NCSs. Finally, the proposed method is applied to a numerical example in order to show the effectiveness of our results.

• Earthquakes and Structures
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• v.11 no.3
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• pp.505-516
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• 2016

This paper evaluates the scaling of ground motions recorded from nine intermediate-depth earthquakes produced in the Vrancea seismic zone in Romania. The considered ground motion database consists of 363 horizontal recordings obtained on soil classes B and C (according to Eurocode 8). An analysis of the inter- and intra-event spectral accelerations is performed in order to gain information regarding the magnitude and distance scaling of the Vrancea ground motions. The analyses reveal a significant influence of the earthquake magnitude and focal depth on the distance scaling and different magnitude and distance scaling for the two soil classes. A linear magnitude and distance scaling is inferred from the results for the range of magnitudes $5.2{\leq}M_W{\leq}7.1$. The results obtained are checked through stochastic simulations and the influence of the stress drop and kappa values on the ground motion levels is assessed. In addition, five ground motion models which were tested in other studies using recordings from Vrancea earthquakes are analyzed in order to evaluate their corresponding host stress drop and kappa. The results show generally a direct connection between the host kappa values and the host stress drop values. Moreover, all the ground motion models depict magnitude dependent host kappa and stress drop levels.

• Water for future
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• v.14 no.1
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• pp.51-58
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• 1981

This study attempts to examine and estabilish a simulation model from the stochastic analysis of daily streamflow. Daily streamflow records obstained at the main gauging stations along the Han, Nakdong and Geum River were used in the analysis. The following results were abtained. From the analysis of time series of streamflow by the correlogram and spectraal density, The serial component of one-year periodicity, serial correlation and irregular or random component were found. The coefficient of determination R2 of multilag model remaine a plateau at log-two, so that second order mu.ltilag model was Known to fit in the simulation of daily streamflow, Consequently, multilag and recised Markov model of the sewnd order give the best results in simulatin of daily streamflow. But the former generally gives better results than the latter. And theoretical markev model is unfit in the simulation of daily series without modification.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.3 s.174
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• pp.661-666
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• 2000

Optimization of the elastic joint of train is performed according to the minimization of ten responses which represent driving safety and ride comfort of train and analyzed by using the each response se surface model from stochastic design of experiments. After the each response surface model is constructed, the main effect and sensitivity analyses are successfully performed by 2nd order approximated regression model as described in this paper. We can get the optimal solutions using by nonlinear programming method such as simplex or interval optimization algorithms. The response surface models and the optimization algorithms are used together to obtain the optimal design of the elastic joint of train. the ten 2nd order polynomial response surface models of the three translational stiffness of the elastic joint (design factors) are constructed by using CCD(Central Composite Design) and the multi-objective optimization is also performed by applying min-max and distance minimization techniques of relative target deviation.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.11
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• pp.22-33
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• 1999

This paper presents the method for the automatic tuning of a design weighting polynomial parameters of a generalized minimum-variance stochastic ultivariable self-tuning controller which adapts to changes in the higher order nonminimum phase system parameters with time delays and noises. The self-tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optimizing the design weighting polynomial parameters of the controller. The proposed multivariable self-tuning method is simple and effective compared with pole restriction method. The computer simulation results are presented to adapt the higher order multivariable system with nonminimum phase and with changeable system parameters.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.6 no.2
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• pp.57-65
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• 1986

The need of forecasting river flows arised whenever a river authority must make controls to protect the life and property from the flood and maintain the adequate flows for water use. This study is on the real time flood forecasting from the gauged and ungauged rainfall input and identification of second-order autoregressive(AR(2)) which is used as system model. A Kalman filter is used to obtain the values of the system parameters needed for the optimal control strategy. This system model was applied to the data at the Naiu gauging station in Young san river basin to check the accuracy and efficiency of prediction. One step ahead prediction is checked by stochastic analysis and the order of autoregressive model is proved to be satisfied, Discussions on interesting features of the model are presented.