• 한국CDE학회논문집
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• 제6권2호
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• pp.78-88
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• 2001

In order to adopt feature-based parametric modeling, CAD/CAM applications must have a geometric constraint solver that can handle a large set of geometric configurations efficiently and robustly. In this paper, we describe a graph constructive approach to solving geometric constraint problems. Usually, a graph constructive approach is efficient, however it has its limitation in scope; it cannot handle ruler-and-compass non-constructible configurations and under-constrained problems. To overcome these limitations. we propose an algorithm that isolates ruler-and-compass non-constructible configurations from ruler-and-compass constructible configurations and applies numerical calculation methods to solve them separately. This separation can maximize the efficiency and robustness of a geometric constraint solver. Moreover, the solver can handle under-constrained problems by classifying under-constrained subgraphs to simplified cases by applying classification rules. Then, it decides the calculating sequence of geometric entities in each classified case and calculates geometric entities by adding appropriate assumptions or constraints. By extending the clustering types and defining several rules, the proposed approach can overcome limitations of previous graph constructive approaches which makes it possible to develop an efficient and robust geometric constraint solver.

• 조명전기설비학회논문지
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• 제14권5호
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• pp.56-61
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• 2000

산업자동화의 고l정밀도에 따라 강연한 재어가 요구되고 있다. 하지만 PID 제어지를 갖는 전동기 시스템이 부하 외란을 받게 되먼 제어시스템의 강인 제어는 어렵게 된다. 이에 대해 보완적인 한 방법로 본 논문에서는 전동기 제어 시스템을 위한 PID-전문가 복합형 제어 기법을 제시하였다. 만약 PID 제어 시스템이 안정한 상태에 있다면 전문가 제어기는 시용되지 않는다. 그러나 오차가 일단 발생하게 되면, 전문가 제어기는 오차를 구속 영역 내로 들어가도록 제어한다. 이에 따라 외란의 영향은 현저히 감소하게 된다. PID 전문가 복합형 제어거를 이용한 직류 서보 전용기의 강인성을 시뮬레이션에 의해 확인하였다.

• Journal of Communications and Networks
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• 제18권2호
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• pp.173-181
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• 2016

In this paper, we address a new robust optimization problem in a multiuser multiple-input single-output broadcasting system with simultaneous wireless information and power transmission, where a multi-antenna base station (BS) sends energy and information simultaneously to multiple users equipped with a single antenna. Assuming that perfect channel-state information (CSI) for all channels is not available at the BS, the uncertainty of the CSI is modeled by an Euclidean ball-shaped uncertainty set. To optimally design transmit beamforming weights and receive power splitting, an average total transmit power minimization problem is investigated subject to the individual harvested power constraint and the received signal-to-interference-plus-noise ratio constraint at each user. Due to the channel uncertainty, the original problem becomes a homogeneous quadratically constrained quadratic problem, which is NP-hard. The original design problem is reformulated to a relaxed semidefinite program, and then two different approaches based on convex programming are proposed, which can be solved efficiently by the interior point algorithm. Numerical results are provided to validate the robustness of the proposed algorithms.

• 한국정보전자통신기술학회논문지
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• 제2권3호
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• pp.103-108
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• 2009

산업자동화의 고정밀도에 따라 강인한 제어가 요구되고 있다. 하지만 PID 제어기를 갖는 전동기 시스템이 부하 외란을 받게 되면 제어시스템의 강인 제어는 어렵게 된다. 이에 대해 보완적인 한 방법으로 본 논문에서는 전동기 제어 시스템을 위한 PID-전문가 복합형 제어기법을 제시하였다. 만약 PID 제어 시스템이 안정한 상태에 있다면 전문가 제어기는 사용되지 않는다. 그러나 오차가 일단 발생하게 되면, 전문가 제어기는 오차를 구속 영역 내로 들어가도록 제어한다. 이에 따라 외란의 영향은 현저히 감소하게 된다. PID-전문가 복합형 제어기를 이용한 직류 서보 전동기의 강인성을 시뮬레이션에 의해 확인하였다.

• 대한전자공학회논문지SP
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• 제48권5호
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• pp.115-122
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• 2011

조향벡터(steering vector)에 에러가 있으면 적응 어레이(adaptive array)는 심한 성능저하를 겪게 된다. 이러한 에러로 인한 성능저하를 개선하기위해 DCRCB(doubly constrained robust Capon beamformer)에서는 벡터 norm 제한아래 구체 불확실 집합(spherical uncertainty set) 내의 벡터 중 출력전력을 최대로 하는 벡터를 조향벡터(steering vector)로 사용한다. 좋은 성능 개선을 위해서 불확실 집합의 반경, 즉 불확실 한계를 적절히 설정해야 하는 문제가 있다. 본 논문에서는 이를 해결하기 위해 반복탐색을 통해 조향벡터를 구하는 방식을 제안한다. 기존의 알려진 반복탐색 방식에서는 반복 종료를 위해 어떤 기준값을 결정해야 하는데, 이에 따른 어려움이 있다. 제안방식에서는 추정된 벡터와 신호부공간 거리가 더 이상 작아 지지 않으면 반복을 종료하며, 값 설정과 관련된 어떤 어려움도 없다. 시뮬레이션 결과에 따르면, 제안방식은 기존반복방식 그리고 최적의 불확실 한계로 설정된 표준 DCRCB 보다도 우수한 성능을 보여준다.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제52권8호
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• pp.363-367
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• 2003

Robust control for feedback control system is needed according to the highest precision of industrial automation. However, when a feedback control system has an effect of disturbance, it is very difficult to guarantee the robustness of control system. As a compensation method solving this problem, in this paper, Hybrid control method of feedback and Differential Supervisory controller is presented. A Feedback Controller is operated as a main controller, A Differential Supervisory Controller is a controller which operates only when some undesirable phenomena occur, e. g., when the error hits the boundary of constraint set. The robust control function of Differential Supervisory Controller, as a assistant controller is operated when state is unstable by disturbance. it demonstrated by speed control of motor.

• 한국멀티미디어학회:학술대회논문집
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• 한국멀티미디어학회 2003년도 춘계학술발표대회논문집
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• pp.423-426
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• 2003

Adaptive algorithm used in Acoustic Echo Canceller (AEC) needs fast convergence algorithm when reference signal is colored speech signal. Set-Membership Affine Projection (SMAP) algorithm is derived from the constraint, which is the minimum value adaptive filter coefficient error. In this paper, we test the characteristic about noise of the SMAP algorithm and proposed modified version of SMAP algorithm fur using at AEC. As the projection order increase, the convergence characteristic of the SMAP algorithm is improved where no noise space. But if the noise uncorrelated with input signal exists, the AEC shows bad performance. In this paper, we propose normalized version of adaptive constants using estimated error signal for robust to noise and show the good performance through AEC simulation.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2006년도 정기 학술대회 논문집
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• pp.299-306
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• 2006

Using a level set method and topological derivatives, a topological shape optimization method that is independent of an initial design is developed for linearly elastic structures. In the level set method, the initial domain is kept fixed and its boundary is represented by an implicit moving boundary embedded in the level set function, which facilitates to handle complicated topological shape changes. The 'Hamilton-Jacobi (H-J)' equation and computationally robust numerical technique of 'up-wind scheme' lead the initial implicit boundary to an optimal one according to the normal velocity field while minimizing the objective function of compliance and satisfying the constraint of allowable volume. Based on the asymptotic regularization concept, the topological derivative is considered as the limit of shape derivative as the radius of hole approaches to zero. The required velocity field to update the H -J equation is determined from the descent direction of Lagrangian derived from optimality conditions. It turns out that the initial holes is not required to get the optimal result since the developed method can create holes whenever and wherever necessary using indicators obtained from the topological derivatives. It is demonstrated that the proper choice of control parameters for nucleation is crucial for efficient optimization process.

• 조명전기설비학회논문지
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• 제18권1호
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• pp.85-89
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• 2004

산업자동화의 고정밀도에 따라 궤환 제어시스템은 강인한 제어가 요구되고 있다. 하지만 신경망 궤환 제어시스템이 외란의 영향을 받았을 때, 시스템의 강인한 제어는 어렵게 된다. 본 논문에서는 이러한 문제를 해결하기 위한 한 방법으로 신경회로망제어기와 PR제어기의 복합형 제어방법을 제시하였다. 신경회로망 제어기는 주 제어기로서 동작하고, PID제어기는 허용오차가 경계영역을 벗어날 때 동작하는 보조제어기로 사용된다. 신경회로망-PID복합형제어기의 강인성은 전동기의 속도제어에 의해서 확인하였다.

• 산업경영시스템학회지
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• 제38권4호
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• pp.117-131
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• 2015

Conventional data envelopment analysis (DEA) models require that inputs and outputs are given as crisp values. Very often, however, some of inputs and outputs are given as imprecise data where they are only known to lie within bounded intervals. While a typical approach to addressing this situation for optimization models such as DEA is to conduct sensitivity analysis, it provides only a limited ex-post measure against the data imprecision. Robust optimization provides a more effective ex-ante measure where the data imprecision is directly incorporated into the model. This study aims to apply robust optimization approach to DEA models with imprecise data. Based upon a recently developed robust optimization framework which allows a flexible adjustment of the level of conservatism, we propose two robust optimization DEA model formulations with imprecise data; multiplier and envelopment models. We demonstrate that the two models consider different risks regarding imprecise efficiency scores, and that the existing DEA models with imprecise data are special cases of the proposed models. We show that the robust optimization for the multiplier DEA model considers the risk that estimated efficiency scores exceed true values, while the one for the envelopment DEA model deals with the risk that estimated efficiency scores fall short of true values. We also show that efficiency scores stratified in terms of probabilistic bounds of constraint violations can be obtained from the proposed models. We finally illustrate the proposed approach using a sample data set and show how the results can be used for ranking DMUs.