• Proceedings of the KIEE Conference
• /
• 2001.07d
• /
• pp.2252-2254
• /
• 2001

This paper proposes a algebraic parameter determination of MRAC (Model Reference Adaptive Control) controller using block Pulse functions and block Pulse function's differential operation. Generally, adaption is performed by solving differential equations which describe adaptive low for updating controller parameter. The proposes algorithm transforms differential equations into algebraic equation, which can be solved much more easily in a recursive manner. We believe that proposes methods are very attractive and proper for parameter estimation of MRAC controller on account of its simplicity and computational convergence.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.20 no.4
• /
• pp.520-527
• /
• 2017

In this study, the experimental methods are compared for obtaining the parameters of the Johnson-Cook constitutive model. The parameters used for numerical simulation are very important in making an accurate estimation of numerical simulation. So, the testing method of obtaining the parameters is also very important. We compared the difference of conventional method, compression method and tensile method of AISI-4340 steel at various strain rate by using MTS, SHPB and SHTB. Taylor impact test and M&S were carried out to compare differences among these three types of JC constitutive parameter.

• Communications for Statistical Applications and Methods
• /
• v.27 no.6
• /
• pp.625-639
• /
• 2020

The gamma distribution is a flexible right-skewed distribution widely used in many areas, and it is of great interest to estimate the probability of a random variable exceeding a specified value in survival and reliability analysis. Therefore, the study develops a fixed-accuracy confidence interval for P(X > c) when X follows a gamma distribution, Γ(α, β), and c is a preassigned positive constant through: 1) a purely sequential procedure with known shape parameter α and unknown rate parameter β; and 2) a nonparametric purely sequential procedure with both shape and rate parameters unknown. Both procedures enjoy appealing asymptotic first-order efficiency and asymptotic consistency properties. Extensive simulations validate the theoretical findings. Three real-life data examples from health studies and steel manufacturing study are discussed to illustrate the practical applicability of both procedures.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.14 no.6
• /
• pp.1679-1688
• /
• 1990

The method of nonlinear parameter estimation(NPE), which is a statistical and an inverse method, is used to estimate the thermal diffusivity of the porous insulation material. In order to apply the NPE method for measuring the thermal diffusivity, and algorithm for programing suitable to IBM personal computer is established, and is studied the statistical treatment of experimental data and theory of estimation. The experimental data obtained by discrete measurement using a constant heat flux technique are used to find the boundary conditions, initial conditions, and the thermal diffusivity, and then the final values are compared with the values obtained by some different methods. The results are presented as follows:(1) NPE method is used to establish the estimation of the thermal diffusivity and compared results with experimental output shows, that this method can be applicable to define the thermal diffusivity without considering hear flux types. (2) Because of all of the temperatures obtained by the discrete measurement on each steps of time are used to estimate the thermal diffusivity. Although some error in the temperature measurements of temperature are included in estimating process, its influences on the final value are minimzed in NPE method. (3) NPE method can reduce the experimental time including the time of data collecting in a few minutes and can take smaller specimen compared with steady state method. If the tube-type furnace is used, also the adjusting time of surrounding temperature can be reduced.

• Journal of Institute of Control, Robotics and Systems
• /
• v.5 no.7
• /
• pp.794-799
• /
• 1999

This study deals with robustness bounds estimation for uncertain linear systems with structured perturbations where the eigenvalues of the perturbed systems are guaranteed to stay in a prescribed region. Based upon the Lyapunov approach, new theorems to estimate allowable perturbation parameter bounds are derived. The theorems are referred to as the zero-order or first-order asymmetric robustness measure depending on the order of the P matrix in the sense of Taylor series expansion of perturbed Lyapunov equation. It is proven that Gao's theorem for the estimation of stability robustness bounds is a special case of proposed zero-order asymmetric robustness measure for eigenvalue assignment. Robustness bounds of perturbed parameters measured by the proposed techniques are asymmetric around the origin and less conservative than those of conventional methods. Numerical examples are given to illustrate proposed methods.

• Communications for Statistical Applications and Methods
• /
• v.21 no.6
• /
• pp.521-528
• /
• 2014

A stochastic Gompertz diffusion model for tumor growth is a topic of active interest as cancer is a leading cause of death in Korea. The direct maximum likelihood estimation of stochastic differential equations would be possible based on the continuous path likelihood on condition that a continuous sample path of the process is recorded over the interval. This likelihood is useful in providing a basis for the so-called continuous record or infill likelihood function and infill asymptotic. In practice, we do not have fully continuous data except a few special cases. As a result, the exact ML method is not applicable. In this paper we proposed a method of parameter estimation of stochastic Gompertz differential equation via Markov chain Monte Carlo methods that is applicable for several data structures. We compared a Markov transition data structure with a data structure that have an initial point.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.20 no.3
• /
• pp.43-59
• /
• 1995

This paper presents a method for estimating the population variability distribution of the failure parameter (failure rate or failure probability) for each failure mode considered in PSA (Probabilistic Safety Assessment). We focus on the utilization of generic estimates from various industry compendia for the estimation. The estimates are complicated statistics of failure data from plants. When the failure data referred in two or more sources are overlapped, dependency occurs among the estimates provided by the sources. This type of problem is first addressed in this paper. We propose methods based on ML-II estimation in Bayesian framework and discuss the characteristics of the proposed estimators. The proposed methods are easy to apply in real field. Numerical examples are also provided.

• Computational Structural Engineering
• /
• v.7 no.4
• /
• pp.137-144
• /
• 1994

As for the safety evaluation of existing large-scale structures, methods for the estimation of structural and dynamic properties are studied. Sequential prediction error method in time domain and frequency response function estimators in frequency domain are examined. For this purpose, impact tests are performed on a steel frame structure with 2 bays and 3 floors. Results from both methods are found to be consistent to each others. However those from the finite-element analysis are slightly different from the experimental results. The discrepancies may be caused by the improper modeling of the complex behavior at the connection joints of the model structure.

• Proceedings of the KIEE Conference
• /
• 2001.07d
• /
• pp.2092-2095
• /
• 2001

In this paper, the performance of a new alternative form of three-axis attitude estimation algorithm for a rigid body is evaluated via simulation for the situation where the observed vectors are the estimated baselines of a GPS antenna array. This method is derived based on a simple iterative nonlinear least-squares with four elements of quaternion parameter. The representation of quaternion parameters for three-axis attitude of a rigid body is free from singularity problem. The performance of the proposed algorithm is compared with other eight existing methods, such as, Transformation Method (TM), Vector Observation Method (VOM), TRIAD algorithm, two versions of QUaternion ESTimator (QUEST), Singular Value Decomposition (SVD) method, Fast Optimal Attitude Matrix (FOAM), Slower Optimal Matrix Algorithm (SOMA).

• Communications for Statistical Applications and Methods
• /
• v.11 no.3
• /
• pp.643-655
• /
• 2004

L$_1$-estimator in the linear regression model is widely recognized to have superior robustness in the presence of vertical outliers. While the L$_1$-estimation procedures and algorithms have been developed quite well, less progress has been made with the hypothesis test in the multiple L$_1$-regression. This article suggests computer-intensive resampling approaches, jackknife and bootstrap methods, to estimating the variance of L$_1$-estimator and the scale parameter that are required to compute the test statistics. Monte Carlo simulation studies are performed to measure the power of tests in small samples. The simulation results indicate that bootstrap estimation method is the most powerful one when it is employed to the likelihood ratio test.