• Journal of Electrical Engineering and Technology
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• v.2 no.2
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• pp.241-248
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• 2007

The accuracy of all the schemes that belong to vector controlled induction machine drives is strongly affected by parameter variations. The aim of this paper is to examine iron losses and magnetic saturation effect in sensorless vector control of induction machines. At first, an approach to induction machine modelling and vector control scheme, which account for both iron loss and saturation, is presented. Then, a model reference adaptive system (MRAS) based speed estimator is developed. The speed estimation is modified in such a way that iron losses and the variation in the saturation level are compensated. Thus by substituting an artificial neural network flux estimator into the MRAS speed estimator. Experimental results are presented to verify the effectiveness of the proposed approach.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.1952-1954
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• 2001

In this paper, we propose the neuro-fuzzy modeling method using VmGA (Virus messy Genetic Algorithm) for the complex nonlinear system. VmGA has more effective and adaptive structure than sGA. in this paper, we suggest a new coding method for applying the model's input and output data to the optimal number of rules in fuzzy models and the structure and parameter identification of membership functions simultaneously. The proposed method realizes the optimal fuzzy inference system using the learning ability of neural network. For fine-tune of parameters identified by VmGA, back- propagation algorithm is used for optimizing the parameter of fuzzy set. The proposed fuzzy modeling method is applied to a nonlinear system to prove the superiority of the proposed approach through comparing with ANFIS.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.95-97
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• 2004

This paper estimates Adaptive Resonance Theory 1(ART1) as a vigilance parameter of pattern clustering algorithm. Inherent characteristics of the model are analyzed. In particular the vigilance parameter ${\rho}$ and its role in classification of patterns is examined. Our estimates show that the vigilance parameter as designed originally does not necessarily increase the number of categories with its value but can decrease also. This is against the claim of solving the stability-plasticity dilemma. However, we have proposed a modified vigilance parameter estimate criterion which takes into account the problem of subset and superset patterns and stably categorizes arbitrarily many input patterns in one list presentation when the vigilance parameter is closer to one.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.22-25
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• 2004

In active noise control (ANC) system, the convergence behavior of the Filtered- X Least Mean Square (FXLMS) algorithm may be affected by nonlinear distortion in the secondary path as in the power amplifiers (e.g., saturation), loudspeakers and transducers. This distortion may yields degrading the error reduction performance of the ANC systems. In this paper, the authors of this paper propose a more improved and stable FXLMS algorithm to compensate for the undesirable nonlinearity of the secondary-path, whereby the third-order Volterra model was employed for the identification of the nonlinear secondary-path. In particular, the proposed approach was based on the modification of the conventional FXLMS algorithm. Finally, the simulation results showed that the proposed approach yields better convergence property and more stable performance in the ANC systems.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.1
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• pp.34-44
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• 2000

In this paper, a modified skyhook control for the semi-active Macpherson suspension system is investigated. A new model for the semi-active type suspension, which incorporates the rotational motion of the unsprung mass, is introduced and an output feedback control law using the skyhook control method is derived. The gains in the skyhook controller are adaptively adjusted by estimating the road conditions. Because two vertical acceleration sensors, one for the sprung mass and another for the unsprung mass, are used rather than using the angle sensor for the rotational motion of the control arm, the relative velocity of the rattle space is filtered using the acceleration signals. For testing the control performance, the actual damping force has been incorporated via the hardware-in-the-loop simulations. The performances of a passive damper and a semi-active damper are compared. Simulation results are provided.

• 한국IT서비스학회:학술대회논문집
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• 2006.11a
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• pp.483-490
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• 2006

본 연구에서는 조직 구성원의 협업을 위하여 도입되는 그룹지원시스템(group support system; GSS)를 대상으로 GSS의 사용에 미치는 영향과 GSS의 사용으로 인한 개인의 성과의 관계에 대한 연구를 실시하였다. 본 연구를 위해 개인의 기술수용 요인에 대한 연구에서 보편적으로 널리 사용되어 온 기술수용모델(technology acceptance model; TAM)과 사용자의 과업과의 연관성을 고려한 과학기술적합(task-technology fit; TTF) 개념, 그리고 적응구조화이론(adaptive structuration theory; AST)을 통합하여 그룹 구성원들이 GSS의 도입의도에 맞게 사용하는 것이 개인과 조직의 성과를 향상시키는지 검증하였다. 연구결과, 높은 TTF는 사용자들이 GSS에 대하여 지각하는 유용성과 용이성에 영향을 미친다는 것을 검증하였다. 또한, TTF가 사용자들의 적절한 사용을 이끌고 있음을 검증하여 TTF 중심의 연구와 AST의 적절한 사용(faithfulness on appropriation; FOA)을 중심으로 하는 두 연구에 대한 통합 모델을 제시하였다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.297-300
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• 2006

본 논문에서는 비선형 기동표적의 추적에 대한 새로운 접근 방식을 소개한다. 이 논문에서는 표적의 가속도를 시변 변수인 표적의 추가적인 잡음으로 두고 각각의 가속도 간격의 정도에 따라 얻어지는 모든 잡음에 대한 변수에 의해 각각의 하부 모델들을 특성화시켰다. 표적의 기동중에 나타나는 가속도를 효과적으로 다루기 위하여, 잡음의 크기가 급격히 증가할 경우 증가분을 가속도로 인식하여 기동표적 관계식에 이용하였다. 또한 모르는 가속도에 따른 시변 변수를 적응적으로 어립잡기는 어렵기 때문에 정밀한 계산을 위하여 퍼지 뉴럴 네트워크와 적응 상호작용 다중모델 기법을 이용하였다. 퍼지 뉴럴 네트워크의 동정을 위해서는 오차 역전파 학습법을 사용하였다. 그리고 제안된 알고리즘의 수행 가능성을 보여주기 위하여 몇 가지 예를 제시하였다.

• Structural Engineering and Mechanics
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• v.76 no.3
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• pp.379-393
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• 2020

In this paper, we propose an automatic procedure to improve the accuracy of finite element solutions using enriched 2D solid finite elements (4-node quadrilateral and 3-node triangular elements). The enriched elements can improve solution accuracy without mesh refinement by adding cover functions to the displacement interpolation of the standard elements. The enrichment scheme is more effective when used adaptively for areas with insufficient accuracy rather than the entire model. For given meshes, an error for each node is estimated, and then proper degrees of cover functions are applied to the selected nodes. A new error estimation method and cover function selection scheme are devised for the proposed adaptive enrichment scheme. Herein, we demonstrate the proposed enrichment scheme through several 2D problems.

• Journal of the Korean Physical Society
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• v.73 no.9
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• pp.1269-1278
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• 2018

Using the thawed Gaussian wave packets [E. J. Heller, J. Chem. Phys. 62, 1544 (1975)] and the adaptive reinitialization technique employing the frame operator [L. M. Andersson et al., J. Phys. A: Math. Gen. 35, 7787 (2002)], a trajectory-based Gaussian wave packet method is introduced that can be applied to scattering and time-dependent problems. This method does not require either the numerical multidimensional integrals for potential operators or the inversion of nearly-singular matrices representing the overlap of overcomplete Gaussian basis functions. We demonstrate a possibility that the method can be a promising candidate for the time-dependent $Schr{\ddot{o}}dinger$ equation solver by applying to tunneling, high-order harmonic generation, and above-threshold ionization problems in one-dimensional model systems. Although the efficiency of the method is confirmed in one-dimensional systems, it can be easily extended to higher dimensional systems.

• Steel and Composite Structures
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• v.17 no.5
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• pp.623-639
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• 2014

Due to recent advancements in the area of Artificial Intelligence (AI) and computational intelligence, the application of these technologies in the construction industry and structural analysis has been made feasible. With the use of the Adaptive-Network-based Fuzzy Inference System (ANFIS) as a modelling tool, this study aims at predicting the shear strength of channel shear connectors in steel concrete composite beam. A total of 1200 experimental data was collected, with the input data being achieved based on the results of the push-out test and the output data being the corresponding shear strength which were recorded at all loading stages. The results derived from the use of ANFIS and the classical linear regressions (LR) were then compared. The outcome shows that the use of ANFIS produces highly accurate, precise and satisfactory results as opposed to the LR.