• Title/Summary/Keyword: adaptive method

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Characteristics Improvement of Hydraulic Servosystem by Using Generalized Minimum Variance Adaptive Control (일반화최소분산 적응제어를 이용한 유압 서보계의 특성개선에 관한 연구)

  • 박용호;김기홍;이진걸
    • Journal of Advanced Marine Engineering and Technology
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    • v.27 no.3
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    • pp.388-394
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    • 2003
  • Hydraulic system is difficult to obtain a suitable performance due to the nonlinearity load pressure change and system parameter variation. The requirement of control a1gorithm has been complex in order to satisfy the performance. The adaptive control is a control method which is suggested to achieve the control object under the plant characteristics change. In spite of the case that plant characteristics and the degree of variation are difficult to grasp. the adaptive control could keep the characteristics of closed-loop system generally. In this study. a method of combined generalized minimum variance adaptive control (GMVAC) and output error feedback is proposed, in order to solve the problem of non-minimum phase of plant and the vibration and overshoot in initial response. The control performance according to the variation of characteristics of plant is evaluated by changing the supply pressure. The experimental results show the effectiveness of the proposed scheme.

The Image Segmentation Method using Adaptive Watershed Algorithm for Region Boundary Preservation

  • Kwon, Dong-Jin
    • International Journal of Internet, Broadcasting and Communication
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    • v.11 no.1
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    • pp.39-46
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    • 2019
  • This paper proposes an adaptive threshold watershed algorithm, which is the method used for image segmentation and boundary detection, which extends the region on the basis of regional minimum point. First, apply adaptive thresholds to determine regional minimum points. Second, it extends the region by applying adaptive thresholds based on determined regional minimum points. Traditional watershed algorithms create over-segmentation, resulting in the disadvantages of breaking boundaries between regions. These segmentation results mainly from the boundary of the object, creating an inaccurate region. To solve these problems, this paper applies an improved watershed algorithm applied with adaptive threshold in regional minimum point search and region expansion in order to reduce over-segmentation and breaking the boundary of region. This resulted in over-segmentation suppression and the result of having the boundary of precisely divided regions. The experimental results show that the proposed algorithm can apply adaptive thresholds to reduce the number of segmented regions and see that the segmented boundary parts are correct.

Modification of Generalized Side-lobe Canceller with an Adaptive filter and Compensator

  • Jeon, Byung-Wook;Park, Keun-Soo;Park, Jang-Sik;Son, Kyung-Sik
    • Proceedings of the Korea Multimedia Society Conference
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    • 2003.05b
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    • pp.427-430
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    • 2003
  • This paper proposes a modified generalized side-lobe canceller with a summed adaptive filter and an adaptive compensator. A summed adaptive filter reduces computational loads and the adaptive compensator minimizes the misadjustment of the adaptive filter coefficients . Computer simulations explain the performance improvement of the proposed method and the conventional generalized side-lobe canceller.

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Improving the Performance of Adaptive Feedback Cancellation in Hearing Aids (보청기에서 적응궤환제거의 성능 향상)

  • Kim, Dae-Kyung;Hur, Jong;Park, Jang-Sik;Son, Kyung-Sik
    • The Journal of the Acoustical Society of Korea
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    • v.18 no.4
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    • pp.38-46
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    • 1999
  • In this paper, two methods were proposed to improve the performance of adaptive feedback cancellation in hearing aids. One is “Orthogonality principle acoustic feedback cancellation method(Orthogonality principle method)” to track optimal solution with monitoring the instantaneous gradient, the other is a method using the CLMS algorithm(CLMS method). In many simulation conditions, adaptive feedback cancellation method proposed in this paper was much better than Greenberg method by Sum-method LMS algorithm which is known the most excellent method by now in case of system mismatch, SNR and segmental SMR. Also. Orthogonality principle method is as good as CLMS method in terms of adaptive feedback cancellation in many simulation conditions.

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Adaptive Finite Element Analysis of 2-D Plane Problems Using the R-P version (R-P법에 의한 이차원 평면문제의 적응 유한요소 해석)

  • Chung, Sang-Wook;Lim, Jang-Keun
    • Proceedings of the KSME Conference
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    • 2000.04a
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    • pp.345-350
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    • 2000
  • Adaptive finite element analysis, which its solution error meets with the user defined allowable error, is recently used far improving reliability of finite element analysis results. This adaptive analysis is composed of two procedures; one is the error estimation of an analysis result and another is the reconstruction of finite elements. In the rp-method, an element size is controlled by relocating of nodal positions(r-method) and the order of an element shape function is determined by the hierarchical polynomial(p-method) corresponding to the element solution error. In order to show the effectiveness and accuracy of the suggested rp-method, various numerical examples were analyzed and these analysis results were examined by comparing with those obtained by the existed methods. As a result of this study, following conclusions are obtained. (1) rp-method is more accurate and effective than the r- and p-method. (2) The solution convergency of the rp-method is controlled by means of the iterative calculation numbers of the r- and p- method each other.

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On the use of weighted adaptive nearest neighbors for missing value imputation (가중 적응 최근접 이웃을 이용한 결측치 대치)

  • Yum, Yunjin;Kim, Dongjae
    • The Korean Journal of Applied Statistics
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    • v.31 no.4
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    • pp.507-516
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    • 2018
  • Widely used among the various single imputation methods is k-nearest neighbors (KNN) imputation due to its robustness even when a parametric model such as multivariate normality is not satisfied. We propose a weighted adaptive nearest neighbors imputation method that combines the adaptive nearest neighbors imputation method that accounts for the local features of the data in the KNN imputation method and weighted k-nearest neighbors method that are less sensitive to extreme value or outlier among k-nearest neighbors. We conducted a Monte Carlo simulation study to compare the performance of the proposed imputation method with previous imputation methods.

Dynamically Adaptive Finite Element Mesh Generation Schemes

  • Yoon, Chong-Yul;Park, Joon-Seok
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.23 no.6
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    • pp.659-665
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    • 2010
  • The finite element method(FEM) is proven to be an effective approximate method of structural analysis if proper element types and meshes are chosen, and recently, the method is often applied to solve complex dynamic and nonlinear problems. A properly chosen element type and mesh yields reliable results for dynamic finite element structural analysis. However, dynamic behavior of a structure may include unpredictably large strains in some parts of the structure, and using the initial mesh throughout the duration of a dynamic analysis may include some elements to go through strains beyond the elements' reliable limits. Thus, the finite element mesh for a dynamic analysis must be dynamically adaptive, and considering the rapid process of analysis in real time, the dynamically adaptive finite element mesh generating schemes must be computationally efficient. In this paper, a computationally efficient dynamically adaptive finite element mesh generation scheme for dynamic analyses of structures is described. The concept of representative strain value is used for error estimates and the refinements of meshes use combinations of the h-method(node movement) and the r-method(element division). The shape coefficient for element mesh is used to correct overly distorted elements. The validity of the scheme is shown through a cantilever beam example under a concentrated load with varying values. The example shows reasonable accuracy and efficient computing time. Furthermore, the study shows the potential for the scheme's effective use in complex structural dynamic problems such as those under seismic or erratic wind loads.

An Adaptive Reclosing Scheme Based on the Classification of Fault Patterns in Power distribution System (사고 패턴 분류에 기초한 배전계통의 적응 재폐로방식)

  • Oh, Jung-Hwan;Kim, Jae-Chul;Yun, Sang-Yun
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.50 no.3
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    • pp.112-119
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    • 2001
  • This paper proposes an adaptive reclosing scheme which is based on the classification of fault patterns. In case that the first reclosing is unsuccessful in distribution system employing with two-shot reclosing scheme, the proposed method can determine whether the second reclosing will be attempted of not. If the first reclosing is unsuccessful two fault currents can be measured before the second reclosing is attempted, where these two fault currents are utilized for an adaptive reclosing scheme. Total harmonic distortion and RMS are used for extracting the characteristics of two fault currents. And the pattern of two fault currents is respectively classified using a mountain clustering method a minimum-distance classifier. Mountain clustering method searches the cluster centers using the acquired past data. And minimum-distance classifier is used for classifying the measured two currents into one of the searched centers respectively. If two currents have the different pattern it is interpreted as temporary fault. But in case of the same pattern, the occurred fault is interpreted as permanent. The proposed method was tested for the fault data which had been measured in KEPCO's distribution system, and the test results can demonstrate the effectiveness of the adaptive reclosing scheme.

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Numerical Studies of Transient Opposed-Flow Flames using Adaptive Time Integration

  • Im, Hong-Geun
    • Journal of Mechanical Science and Technology
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    • v.14 no.1
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    • pp.103-112
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    • 2000
  • Numerical simulations of unsteady opposed-flow flames are performed using an adaptive time integration method designed for differential-algebraic systems. The compressibility effect is considered in deriving the system of equations, such that the numerical difficulties associated with a high-index system are alleviated. The numerical method is implemented for systems with detailed chemical mechanisms and transport properties by utilizing the Chemkin software. Two test simulations are performeds hydrogen/air diffusion flames with an oscillatory strain rate and transient ignition of methane against heated air. Both results show that the rapid transient behavior is successfully captured by the numerical method.

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Design of Nonlinear Adaptive Controller using Wavelet Neural Network (웨이브렛 신경회로망을 이용한 비선형 적응 제어기 설계)

  • 정경권;김주웅;엄기환;정성부;김한웅
    • Proceedings of the IEEK Conference
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    • 2001.06c
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    • pp.17-20
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    • 2001
  • In this paper, we design a nonlinear adaptive controller using wavelet neural network. The method proposed in this paper performs for a nonlinear system with unknown parameters, identification with using a wavelet neural network, and then a nonlinear adaptive controller is designed with those identified informations. The advantage of the proposed control method is simple to design a controller for unknown nonlinear systems, because we use the identified informations and design parameters are positioned within a negative real part of s-plane. The simulation results showed the effectiveness of proposed controller design method.

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