• Title/Summary/Keyword: parametric coordinate transformation

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On Feedback Linearization of Nonlinear Time-Delay Systems

  • Shin, Hee-Sub;Lim, Jong-Tae
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1906-1908
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    • 2004
  • We propose a result on the stabilization of nonlinear time-delay systems via the feedback linearization method. Using the predictor based control and the parametric coordinate transformation, we introduce a stabilizing controller to compensate time delay. Specifically, we present the delay-dependent stability analysis to makes the considered system stable. Also, an illustrative example is provided

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NUMERICAL EVALUATION OF CAUCHY PRINCIPAL VALUE INTEGRALS USING A PARAMETRIC RATIONAL TRANSFORMATION

  • Beong In Yun
    • The Pure and Applied Mathematics
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    • v.30 no.4
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    • pp.347-355
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    • 2023
  • For numerical evaluation of Cauchy principal value integrals, we present a simple rational function with a parameter satisfying some reasonable conditions. The proposed rational function is employed in coordinate transformation for accelerating the accuracy of the Gauss quadrature rule. The efficiency of the proposed rational transformation method is demonstrated by the numerical result of a selected test example.

Automatic Ship Collision Avoidance in Narrow Channels through Curvilinear Coordinate Transformation (곡선좌표계 변환에 기반한 협수로에서 선박 자율 충돌회피)

  • Cho, Yonghoon;Kim, Jonghwi;Kim, Jinwhan
    • Journal of the Society of Naval Architects of Korea
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    • v.58 no.3
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    • pp.191-197
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    • 2021
  • This study addresses autonomous ship collision avoidance in narrow channels using curvilinear coordinates. Navigation in narrow channels or fairways is known to be much more difficult and challenging compared with navigation in the open sea. It is not straightforward to apply the existing collision avoidance framework designed for use in the open sea to collision avoidance in narrow channels due to the complexity of the problem. In this study, to generalize the autonomous navigation procedure for collision avoidance in narrow channels, we introduce a curvilinear coordinate system for collision-free path planning using a parametric curve, B-spline. To demonstrate the feasibility of the proposed algorithm, ship traffic simulations were performed and the results are presented.

Nonlinear Adaptive Control of EMS Systems with Mass Uncertainty (무게 변화를 고려한 자기부사열차의 비선형 적응제어기법)

  • Jo, Nam-Hoon;Joo, Sung-Jun;Seo, Jin-Heon
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.49 no.10
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    • pp.563-571
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    • 2000
  • In this paper, a nonlinear adaptive control method for an EMS(Electro-Magnetic Suspension) system with mass uncertainty is proposed. Using the coordinate transformation and feedback linearizing control, EMS system has been transformed into the form of parametric strict-feedback system with unknown virtual control coefficients. With this transformed system, tuning functions approach, which is an advanced from of adaptive backstepping, has been applied in order to stabilize the system against mass uncertainty. Computer simulation is also carried out in order to compare the performance of the proposed controller with that of feedback linerizing controller.

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The Precise Positioning with the 3D Coordinate Transformation of GPS Surveying (GPS 측량의 3차원 좌표변환에 의한 정밀위치결정)

  • Park, Woon-Yong;Yeu, Bock-Mo;Lee, Kee-Boo
    • Journal of Korean Society for Geospatial Information Science
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    • v.8 no.2 s.16
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    • pp.47-60
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    • 2000
  • On this study, Among the classification methods of land cover using satellite imagery, we compared the classification accuracy of Neural Network Classifier and that of Maximum Likelihood Classifier which has the characteristics of parametric and non-parametric classification method. In the assessment of classification accuracy, we analyzed the classification accuracy about testing area as well as training area that many analysts use generally when assess the classification accuracy. As a result, Neural Network Classifier is superior to Maximum Likelihood Classifier as much as 3% in the classification of training data. When ground reference data is used, we could get poor result from both of classification methods, but we could reach conclusion that the classification result of Neural Network Classifier is superior to the classification result of Maximum Likelihood Classifier as much as 10%.

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Posterior Inference in Single-Index Models

  • Park, Chun-Gun;Yang, Wan-Yeon;Kim, Yeong-Hwa
    • Communications for Statistical Applications and Methods
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    • v.11 no.1
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    • pp.161-168
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    • 2004
  • A single-index model is useful in fields which employ multidimensional regression models. Many methods have been developed in parametric and nonparametric approaches. In this paper, posterior inference is considered and a wavelet series is thought of as a function approximated to a true function in the single-index model. The posterior inference needs a prior distribution for each parameter estimated. A prior distribution of each coefficient of the wavelet series is proposed as a hierarchical distribution. A direction $\beta$ is assumed with a unit vector and affects estimate of the true function. Because of the constraint of the direction, a transformation, a spherical polar coordinate $\theta$, of the direction is required. Since the posterior distribution of the direction is unknown, we apply a Metropolis-Hastings algorithm to generate random samples of the direction. Through a Monte Carlo simulation we investigate estimates of the true function and the direction.

Thermal Conductivity Model of Twisted Yarn Composites (꼰 섬유 복합재료의 열전도도 예측모델)

  • 변준형;이상관;김병선;박종규;이재열
    • Proceedings of the Korean Society For Composite Materials Conference
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    • 2003.10a
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    • pp.95-98
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    • 2003
  • In woven or knitted preforms for composites, the yams are often twisted for avoiding damage due to the contact with the textile machine elements. When the preforms of twisted yams are used in carbon/carbon composites, the thermal conductivity of the composites varies depending upon the degree of the yarn twist. This paper presents a thermal conductivity model of spun yarn composites. The thermal-electrical analogy and the averaging technique have been adopted in this analysis. The model prediction has been correlated with experimental results in order to confirm the model predictability. Parametric study has also been conducted to examine the effect of the yam twist on the thermal conductivity of spun yarn composites.

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Robust Stabilization of Differentially Flat Uncertain Nonlinear Systems (미분적으로 평활한 불확정 비선형 시스템의 강인 안정화)

  • Joo, Jin-Man;Park, Jin-Bae;Choi, Yoon-Ho;Yoon, Tae-Sung
    • Proceedings of the KIEE Conference
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    • 1998.07b
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    • pp.647-649
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    • 1998
  • This paper describes a robust stabilization of single input nonlinear systems with parametric uncertainty. We first investigate differential flatness of the nominal nonlinear systems. If a single input system is differentially flat, it possesses a flat output. And we define coordinate transformation functions via successively differentiating the flat output, and we also consider the robust fictitious controls at every differentiation of the flat output. In the new coordinates the nonlinear system is transformed into the Brunovsky normal form with matched uncertainty. With a robust control based on the Lyapunov method, the robust stabilization is achieved.

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