• Journal of Construction Engineering and Project Management
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• 제7권2호
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• pp.1-10
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• 2017

The Clonal Selection Algorithm (CSA) is an algorithm inspired by the human immune system mechanism. In CSA, several parameters needs to be optimized by large amount of sensitivity analysis for the optimal results. They limit the accuracy of the results due to the uncertainty and subjectivity. Adaptive Clonal Selection (ACS), a modified version of CSA, is developed as an algorithm without controls by pre-defined parameters in terms of selection process and mutation strength. In this paper, we discuss the ACS in detail and present its implementation in construction site utilization planning (CSUP). When applied to a developed model published in research literature, it proves that the ACS are capable of searching the optimal layout of temporary facilities on construction site based on the result of objective function, especially when the parameterization process is considered. Although the ACS still needs some improvements, obtaining a promising result when working on a same case study computed by Genetic Algorithm and Electimze algorithm prove its potential in solving more complex construction optimization problems in the future.

• KIEE International Transactions on Power Engineering
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• 제4A권2호
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• pp.73-78
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• 2004

This paper proposes a framework for determining the minimum load shedding for restoring solvability. The framework includes a continuation power flow (CPF) and an optimal power flow (OPF). The CPF parameterizes a specified outage from a set of multiple contingencies causing unsolvable cases, and it traces the path of solutions with respect to the parameter variation. At the nose point of the path, sensitivity analysis is performed in order to achieve the most effective control location for load shedding. Using the control location information, the OPF for locating the minimum load shedding is executed in order to restore power flow solvability. It is highlighted that the framework systematically determines control locations and the proper amount of load shedding. In a numerical simulation, an illustrative example of the proposed framework is shown by applying it to the New England 39 bus system.

• 한국전산구조공학회논문집
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• 제30권4호
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• pp.313-318
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• 2017

본 연구는 진동에너지를 흡수하기 위한 진동 금속 댐퍼의 구조 해석과 최적 설계를 수행한다. 고무 베어링, 마찰 또는 점성 댐퍼와 같은 다른 댐퍼와는 달리 이 금속제진장는 금속의 소성 변형과 그에 따른 히스테리시스 현상을 이용하여 구조물의 진동을 감소시킨다. 이 금속제진장치를 최적화 하려면 댐퍼를 통해 소성 변형을 얻는 것이 중요하다. 금속제진장치의 최적화된 형상을 찾기 위해 형상 최적화 방법을 적용하였다. 또한 매개 변수화 체계에 따라 일부 최적의 모양을 찾을 수 있다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 추계학술대회 논문집 학회본부
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• pp.146-148
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• 1997

An LMI-based parameterization of all $\gamma$-suboptimal reduced-order unbiased $H_{\infty}$ filters is provided in terms of a free matrix, using the unbiasedness condition, bounded real lemma and the general solution of the basic LMI. Also, by sequentially solving the generalized eigenvalue minimization and basic LMI problem, the optimal filter coefficient matrix can be obtained with the best achievable performance.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제53권8호
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• pp.469-476
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• 2004

In this paper, a 3D shape optimization algorithm which guarantees a smooth optimal shape is presented using parameterized sensitivity analysis. The design surface is parameterized using Bezier spline and B-spline, and the control points of the spline are taken as the design variables. The parameterized sensitivity for the control points are found from that for nodal points. The design sensitivity and adjoint variable formulae are also derived for the 3D non-linear problems. Through an application to the shape optimization of 3D electromagnet to get a uniform magnetic field, the effectiveness of the proposed algorithm is shown.

• 한국전산구조공학회논문집
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• 제35권6호
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• pp.351-356
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• 2022

본 논문에서는 3차원 엮임 재료의 유체투과율 향상을 목적으로 수치해석 데이터 기반의 물성치 회귀 분석 및 최적설계를 소개한다. 우선 3차원 엮임 재료를 구성하는 와이어 사이의 간격을 결정하는 배율 계수를 매개변수화 하여 다양한 배율 조합을 가지는 수치 모델을 생성하였고, 전산 수치해석을 통해 계산된 각 모델의 체적 탄성계수, 열전도 계수, 유체투과율 데이터를 이용하여 다항식 기반의 회귀 분석을 수행하였다. 이를 사용해서 체적 탄성계수와 유체투과율 사이의 다목적함수 최적설계를 통한 파레토 최적해를 도출하였으며, 두 물성치가 서로 상충 관계에 있음을 확인하였다. 한편 3차원 엮임 재료의 열전달 효율을 높이기 위해서 유체투과율을 최대화 시키는 것을 목적으로 경사도 기반 최적설계를 수행하였고, 제약조건인 체적 탄성계수의 크기별 유체투과율의 변화율을 분석하였다. 그 결과 설계자가 원하는 최소한의 강성을 가지는 최대 유체투과율 설계 모델을 얻어낼 수 있음을 확인하였으며, 회귀 방정식을 통해서 얻어진 설계가 높은 정확도를 가지고 있음을 추가적으로 검증하였다.

• 제어로봇시스템학회논문지
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• 제21권12호
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• pp.1193-1200
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• 2015

An effective swing trajectory of legged robots is different from the swing trajectories of humans or animals because of different dynamic characteristics. Therefore, it is important to find optimal parameters through experiments. This paper proposes a real-time nonlinear programming (RTNLP) method for optimization of the swing trajectory of the legged robot. For parameterization of the trajectory, the swing trajectory is approximated to parabolic and cubic spline curves. The robotic leg is position-controlled by a high-gain controller, and a cost function is selected such that the sum of the motor inputs and tracking errors at each joint is minimized. A simplified dynamic model is used to simulate the dynamics of a robotic leg. The purpose of the simulation is to find the feasibility of the optimization problem before an actual experiment occurs. Finally, an experiment is carried out on a real robotic leg with two degrees of freedom. For both the simulation and the experiment, the design variables converge to a feasible point, reducing the cost value.

• 한국지능시스템학회논문지
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• 제11권7호
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• pp.680-688
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• 2001

In this paper, we propose a reliable method for searching the optimally performing generalized brain-state-in-a-box (GBSB) neural associative memory using an evolution program (EP) given a set of prototype patterns to be stored as stable equilibrium points. First, we exploit some qualitative guidelines necessary to synthesize the GBSB model. Next, we parameterize the solution space utilizing the limited number of parameters to represent the solution space. Then, we recast the synthesis of GBSB neural associative memories as two constrained optimization problems, which are equivalent to finding a solution to the original synthesis problem. Finally, we employ an evolution program (EP), which enables us to find an optimal set of parameters related to the size of domains of attraction (DOA) for prototype patterns. The validity of this approach is illustrated by a design example and computer simulations.

• Advances in Automotive Engineering
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• 제1권1호
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• pp.105-121
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• 2018

The hybrid electric powertrain is a robust solution that allows for major improvements in both fuel economy and emission reduction. In the present study, a through-the-road hybrid vehicle model with an electric motor driving the rear axle and an Internal Combustion Engine (ICE) driving the front axle has been constructed. We then present a systematic method for the determination of a real time applicable optimal Energy Management Strategy (EMS) for a hybrid road vehicle. More precisely, we compare the performance of rule-based EMS strategies to an optimization-based strategy, namely ECMS (Equivalent Consumption Minimization Strategy). The comparison is conducted in parallel with a parameterization of the size of the internal combustion engine and the implementation of a Continuously Variable Transmission (CVT) that allows following the line of best fuel economy. For the FTP-75 driving cycle, the constrained engine On-off control algorithm is shown to offer a 28% improvement potential of fuel consumption compared to the conventional internal combustion engine while the ECMS strategy achieves an improved potential of nearly 33%.

• 대한기계학회논문집A
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• 제27권8호
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• pp.1353-1362
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• 2003

This paper considers a simultaneous optimization problem of structure and control systems. The problem is generally formulated as a non-convex optimization problem for the design parameters of mechanical structure and controller. Therefore, it is not easy to obtain the global solutions for practical problems. In this paper, we parameterize all design parameters of the mechanical structure such that the parameters work in the control system as decentralized static output feedback gains. Using this parameterization, we have formulated a simultaneous optimization problem in which the design specification is defined by the Η$_2$and Η$\_$$\infty$/ norms of the closed loop transfer function. So as to lead to a convex problem we approximate the nonlinear terms of design parameters to the linear terms. Then, we propose a convex optimization method that is based on linear matrix inequality (LMI). Using this method, we can surely obtain suboptimal solution for the design specification. A numerical example is given to illustrate the effectiveness of the proposed method.