• International Journal of Control, Automation, and Systems
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• v.1 no.3
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• pp.289-300
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• 2003

In this paper, we introduce an identification method in Fuzzy Relation-based Fuzzy Neural Networks (FRFNN) through a hybrid identification algorithm. The proposed FRFNN modeling implement system structure and parameter identification in the efficient form of "If...., then... " statements, and exploit the theory of system optimization and fuzzy rules. The FRFNN modeling and identification environment realizes parameter identification through a synergistic usage of genetic optimization and complex search method. The hybrid identification algorithm is carried out by combining both genetic optimization and the improved complex method in order to guarantee both global optimization and local convergence. An aggregate objective function with a weighting factor is introduced to achieve a sound balance between approximation and generalization of the model. The proposed model is experimented with using two nonlinear data. The obtained experimental results reveal that the proposed networks exhibit high accuracy and generalization capabilities in comparison to other models.er models.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.954-959
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• 2008

This paper is concerned with the reliable $H_{\infty}$ controller design problem for uncertain linear systems against actuator failures. In the design, the $H_{\infty}$ performance of the closed-loop system is optimized during normal operation(without failures) while the system satisfies a prescribed $H_{\infty}$ performance level in the case of actuator failures. Single and parameter-dependent Lyapunov function approaches are applied in designing suboptimal reliable $H_{\infty}$ controllers. Simulation studies are presented to demonstrate the effectiveness of the proposed design procedures.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.7
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• pp.1156-1165
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• 1997

Complex modal testing is employed for the in-situ parameter identification of a four-axis active magnetic bearing system while the system is in operation. In the test, magnetic bearings are used as exciters as well as actuators for feedback control. The experimental results show that the directional frequency response function, which is properly defined in the complex domain, is a powerful tool for identification of bearing as well as modal parameters. It is also shown that the position and current stiffnesses can be accurately estimated using the relations between the measured forces, displacements, and currents.

• Journal of the Korean Data and Information Science Society
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• v.4
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• pp.137-146
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• 1993

The Proposed goodness-of-fit test Statistic $\hat{\lambda}_{\alpha}$ derived from the test Statistc in Kim (1992) is itself a smoothing parameter which is selected to minimize an estimated MISE for a truncated series estimator, $d_{\hat{\lambda}{n}}$, of the comparison density function. Therefore, this test statistic leads immediately to a point estimate of the density function in the event that $H_{0}$ is ejected. The limiting distribution of $\hat{\lambda}_{\alpha}$ was obtained under the null hypothesis. It is also shown that this test is consistent against fixed alternatives.

• Communications for Statistical Applications and Methods
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• v.5 no.2
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• pp.539-557
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• 1998

This article is concerned with the problem of estimating the mean of a one-parameter exponential family through sequential sampling in three stages under quadratic error loss. This more general framework differs from those considered by Hall (1981) and others. The differences are : (i) the estimator and the final stage sample size are dependent; and (ii) second order approximation of a continuously differentiable function of the final stage sample size permits evaluation of the asymptotic regret through higher order moments. In particular, the asymptotic regret can be expressed as a function of both the skewness $\rho$ and the kurtosis $\beta$ of the underlying distribution. The conditions on $\rho$ and $\beta$ for which negative regret is expected are discussed. Further results concerning the stopping variable N are also presented. We also supplement our theoretical findings wish simulation results to provide a feel for the triple sampling procedure presented in this study.

• 한국데이터정보과학회:학술대회논문집
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• 2005.04a
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• pp.83-126
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• 2005

Single-index models have found applications in econometrics and biometrics, where multidimensional regression models are often encountered. Here we propose a nonparametric estimation approach that combines wavelet methods for non-equispaced designs with Bayesian models. We consider a wavelet series expansion of the unknown regression function and set prior distributions for the wavelet coefficients and the other model parameters. To ensure model identifiability, the direction parameter is represented via its polar coordinates. We employ ad hoc hierarchical mixture priors that perform shrinkage on wavelet coefficients and use Markov chain Monte Carlo methods for a posteriori inference. We investigate an independence-type Metropolis-Hastings algorithm to produce samples for the direction parameter. Our method leads to simultaneous estimates of the link function and of the index parameters. We present results on both simulated and real data, where we look at comparisons with other methods.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.5
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• pp.833-839
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• 2003

The effects of stiffeners on the modal characteristics of rectangular plates are investigated. A modeling method for the modal analysis of rectangular plates with stiffeners is presented. A mass density Dirac's delta function is used to idealize the stiffeners mathematically. The equations of motion for the plates are derived and transformed into a dimensionless form. To confirm the accuracy of the method presented in this study, numerical result are obtained and compared to those of a commercial program. The mode shape variations due to some parameter variations are also exhibited.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.863-869
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• 2007

An improved method based on a normal frequency response function (FRF) is proposed to identify structural parameters such as mass, stiffness and damping matrices directly from the FRFs of a linear mechanical system. The method for estimating structural parameters directly from the measured FRFs of a structure is presented. This paper demonstrates that the characteristic matrices are extracted more accurately by using a weighted equation and eliminating the matrix inverse operation. The method is verified for a four degree-of-freedom lumped parameter system and an eight degree-of-freedom finite element beam. Experimental verification is also performed for a free-free steel beam whose size and physical properties are the same as those of the finite element beam. The results show that the structural parameters, especially the damping matrix, can be estimated more accurately by the proposed method.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.241-242
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• 2008

본 논문에서는 fuzzy granular computing 방법 중의 하나인 context-based FCM을 이용하여 granular-based radial basis function neural network에 대한 기본적인 개면과 그들의 포괄적인 설계 구조에 대해서 자세히 기술한다. 제안된 모델에 기본이 되는 설계 도구는 context-based fuzzy c-means (C-FCM)로 알려진 fuzzy clustering에 초점이 맞춰져 있으며, 이는 주어진 데이터의 특징에 맞게 공간을 분할함으로써 효율적으로 모델을 구축할 수가 있다. 제안된 모델의 설계 공정은 1) Context fuzzy set에 대한 정의와 설계, 2) Context-based fuzzy clustering에 대한 모델의 적용과 이에 따른 모델 구축의 효율성, 3) 입력과 출력공간에서의 연결된 information granule에 대한 parameter(다항식의 계수들)에 대한 최적화와 같은 단계로 구성되어 있다. Information granule에 대한 parameter들은 성능지수를 최소화하기 위해 Least square method에 의해서 보정된다. 본 논문에서는 모델을 설계함에 있어서 체계적인 설계 알고리즘을 포괄적으로 설명하고 있으며 더 나아가 제안된 모델의 성능을 다른 표준적인 모델들과 대조함으로써 제안된 모델의 우수성을 나타내고자 한다.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.357-366
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• 2001

The present paper develops a method to check the propriety of link functions for binary data. In order to parameterize a certain type of goodness of the link, a family of link functions indexed by a shape parameter is proposed. I first investigate the maximum likelihood estimation of the shape parameter as well as regression parameters and then derive their large sample behaviors of the estimators. A score test is considered to evaluate the goodness of the current link function. For illustration, I employ two families of power transformations, the modulus transformation by John and Draper (1980) and the extended power transformation by Yeo and Johnson (2000), which are appropriate to detect symmetric and asymmetric inadequacy of the selected link function. respectively.