• Bulletin of the Korean Mathematical Society
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• v.33 no.3
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• pp.377-383
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• 1996

We consider in this paper the following nonlinear regression model $$ (1.1) y_t = f(x_t, \theta_o) + \in_t, t = 1, \ldots, n, $$ where $y_t$ is the tth response, $x_t$ is m-vector imput variable, $\theta_o$ is a p-vector of unknown parameter belong to a parameter space $\Theta, f:R^m \times \Theta \ to R^1$ is a nonlinear known function, and $\in_t$ are independent unobservable random errors with finite second moment.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.231-235
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• 1995

In this paper, the frozen time approach is used to analyze the nonlinear system with time varying parameter. Using the extended linearization, we propose two analytical methods that compute an upper bound of the Euclidean norm of the difference between state variable and equilibrium point of the given system. The propertise of the two methods are discussed with simple examples.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.817-826
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• 1987

An offset-free self-tuning control with pole placement (STCPP) and a recursive parameter estimation with multiple and variable forgetting factors (REWF), together with their application to a real plant, are described. There are two different types of offset-free STCPP; their features are analysed and discussed. REMVF employs as many forgetting factors as parameter estimates. It is suitable when parameters to be estimated are changing at different rates. The offset-free STCPP and REMVF have been successfully applied to a real plant, giving excellent results.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1987-1992
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• 2004

A Variable Structure Model Reference Adaptive Controller (VS-MRAC) using state Variables is proposed for single input multi output systems. . The structure of the switching functions is designed based on stability requirements, and global exponential stability is proved. Transient behavior is analyzed using sliding mode control and shows perfect model following at a finite time. The effect of input disturbances on stability and transients is investigated and shows preference to the conventional MRAC schemes with integral adaptation law. Sliding surfaces are independent of system parameters and therefore VS-MRAC is insensitive to system parameter variations. Simulation is presented to clear the theoretical results.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1227-1233
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• 1993

In this paper we present the differential geometric approach for the analysis and design of sliding modes in nonlinear variable structure feedback systems. We also design the robust controller for the nonlinear system using variable structure control theory on the basis of differential geometric methods and feedback linearization applying Min-Max control based on the Lyapunov second method. The robustness against parameter uncertainties for robot manipulators with flexible joint is considered. Simulation results are presented and show the advantage of the proposed nonlinear control method.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.852-855
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• 1996

A variable structure controller is developed for an AC servo motor used in CNC milling machines. The designed controller is implemented as an outer loop controller to a factory designed motor-servopack system. The robustness parameter is tuned for a fast response when the speed tracking error is large, while it is tuned for small oscillations when the speed tracking error is small. The designed controller is installed on a CNC machine using a PC. Cutting experiments show improved performance over the factory-designed controller.

• Communications for Statistical Applications and Methods
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• v.20 no.5
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• pp.357-366
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• 2013

This paper defines an improvement for estimating the population mean of a study variable using auxiliary information and known values of certain population parameter(s), when there is a non-response in a study as well as on auxiliary variables. Under a simple random sampling without a replacement (SRSWOR) scheme, the mean square error (MSE) of all proposed estimators are obtained and compared with each other. Numerical illustration is also given.

• Proceedings of the KIEE Conference
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• 2005.10a
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• pp.161-164
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• 2005

In this paper, a new estimation algorithm for the rotor speed for SRM drives is described. The algorithm is implemented by the binary observer. The stability and robustness of the binary observer for the parameter variations of the SRM are proved by variable structure control theory. Variable speed control of the SRM is accomplished by the estimated speed. Experiment results verify that the binary observer is able to estimate the speed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.10
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• pp.1299-1306
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• 2011

In this study, crack-growth model parameters subjected to variable amplitude loading are estimated in the form of a probability distribution using the method of Bayesian parameter estimation. Huang's model is employed to describe the retardation and acceleration of the crack growth during the loadings. The Markov Chain Monte Carlo (MCMC) method is used to obtain samples of the parameters following the probability distribution. As the conventional MCMC method often fails to converge to the equilibrium distribution because of the increased complexity of the model under variable amplitude loading, an improved MCMC method is introduced to overcome this shortcoming, in which a marginal (PDF) is employed as a proposal density function. The model parameters are estimated on the basis of the data from several test specimens subjected to constant amplitude loading. The prediction is then made under variable amplitude loading for the same specimen, and validated by the ground-truth data using the estimated parameters.

• Communications of the Korean Mathematical Society
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• v.33 no.4
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• pp.1367-1376
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• 2018

In practice, the density function of a random variable X is always unknown. Even its smoothness parameter is unknown to us. In this paper, we will consider a density smoothness parameter estimation problem via wavelet theory. The smoothness parameter is defined in the sense of equivalent Besov norms. It is well-known that it is almost impossible to estimate this kind of parameter in general case. But it becomes possible when we add some conditions (to our proof, we can not remove them) to the density function. Besides, the density function contains impurities. It is covered by some additive noises, which is the key point we want to show in this paper.