• 대한기계학회:학술대회논문집
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• 대한기계학회 2007년도 춘계학술대회A
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• pp.831-836
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• 2007

This paper proposes an optimal galloping trajectory which costs low energy and guarantees the stability of the quadruped robot. In the realization of the fast galloping, the trajectory design is important. As a galloping trajectory, we propose an elliptic leg trajectory, which provides simplified locomotion to complex galloping motions of animals. However, the elliptic trajectory, as an imitation of animal galloping motion, does not guarantee stability and minimal energy consumption. We propose optimization based on the energy and stability using a genetic algorithm, which provides the robust and global solution to a multi-body, highly nonlinear dynamic system. To evaluate and verify the effectiveness of the proposed trajectory, computer simulations were carried out.

• Journal of information and communication convergence engineering
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• 제6권2호
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• pp.222-227
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• 2008

The important problem in designing a Fuzzy Logic Controller(FLC) is generation of fuzzy control rules and it is usually the case that they are given by human experts of the problem domain. However, it is difficult to find an well-trained expert to any given problem. In this paper, I describes an application of genetic algorithm, a well-known global search algorithm to automatic generation of fuzzy control rules for FLC design. Fuzzy rules are automatically generated by evolving initially given fuzzy rules and membership functions associated fuzzy linguistic terms. Using genetic algorithm efficient fuzzy rules can be generated without any prior knowledge about the domain problem. In addition expert knowledge can be easily incorporated into rule generation for performance enhancement. We experimented genetic algorithm with a non-trivial vehicle controling problem. Our experimental results showed that genetic algorithm is efficient for designing any complex control system and the resulting system is robust.

• Journal of Electrical Engineering and Technology
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• 제4권3호
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• pp.323-329
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• 2009

This paper presents a new approach for thermal unit commitment (UC) using a differential evolution (DE) algorithm. DE is an effective, robust, and simple global optimization algorithm which only has a few control parameters and has been successfully applied to a wide range of optimization problems. However, the standard DE cannot be applied to binary optimization problems such as UC problems since it is restricted to continuous-valued spaces. This paper proposes binary differential evolution (BDE), which enables the DE to operate in binary spaces and applies the proposed BDE to UC problems. Furthermore, this paper includes heuristic-based constraint treatment techniques to deal with the minimum up/down time and spinning reserve constraints in UC problems. Since excessive spinning reserves can incur high operation costs, the unit de-commitment strategy is also introduced to improve the solution quality. To demonstrate the performance of the proposed BDE, it is applied to largescale power systems of up to 100-units with a 24-hour demand horizon.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 추계학술대회
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• pp.1322-1327
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• 2003

It is important to determine supporting locations for structural stability of a structure under non-uniform load in space interfered by other parts. In this case, There are many local optima with discontinuous design space. Therefore, The traditional optimization methods based on derivative are not suitable. Whereas, Genetic algorithm(GA) based on stochastic search technique is a very robust and general method. This paper has been presented to determine supporting locations of the vertical supports for reducing stress of the KSTAR(Korea super Superconducting Tokamak Advanced Research) IVCC(In-vessel control coil) under non-uniform electromagnetic load and space interfered by other parts using genetic algorithm. For this study, we develop a program combining finite element analysis with a genetic algorithm to perform structural analysis of IVCC. In addition, this paper presents a technique to perform optimization with FEM when design variables are trapped in an incongruent design space.

• 한국항공우주학회지
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• 제43권7호
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• pp.601-608
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• 2015

유연날개의 공력 및 구조 설계값을 설계 변수로 하여 정적 상태에서의 정적 공탄성해석 및 최적화를 수행하였다. 정적 공탄성해석과 최적화를 위해 상용 해석소프트웨어들이 연계된 강건한 다분야 최적설계 시스템을 개발하였다. 최적화 설계변수로는 가로세로비, 테이퍼비, 후퇴각과 날개 위아래 스킨 두께를 설정하였다. 전역적 다목적 최적화를 위해 실수기반 적응영역 다목적 유전자 알고리즘을 적용하였으며 계산시간을 줄이기 위해 메타모델로 서포트벡터회귀 기법을 적용하였다. 유연날개에 대한 파레토 결과 분석을 통해 최대 항속시간과 최소 중량에 대한 최적 결과를 확인하였다.

• Smart Structures and Systems
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• 제26권3호
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• pp.345-360
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• 2020

Modern swarm intelligence heuristic search methods are widely applied in the field of structural health monitoring due to their advantages of excellent global search capacity, loose requirement of initial guess and ease of computational implementation etc. To this end, a hybrid strategy is proposed based on butterfly optimization algorithm (BOA) and differential evolution (DE) with purpose of effective combination of their merits. In the proposed identification strategy, two improvements including mutation and crossover operations of DE, and dynamic adaptive operators are introduced into original BOA to reduce the risk to be trapped in local optimum and increase global search capability. The performance of the proposed algorithm, hybrid butterfly optimization and differential evolution algorithm (HBODEA) is evaluated by two numerical examples of a simply supported beam and a 37-bar truss structure, as well as an experimental test of 8-story shear-type steel frame structure in the laboratory. Compared with BOA and DE, the numerical and experimental results show that the proposed HBODEA is more robust to detect the reduction of stiffness with limited sensors and contaminated measurements. In addition, the effect of search space, two dynamic operators, population size on identification accuracy and efficiency of the proposed identification strategy are further investigated.

• 대한기계학회논문집A
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• 제27권5호
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• pp.798-806
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• 2003

Structural optimization has been carried out in continuous or discrete design space. Methods for continuous design have been well developed though they are finding the local optima. On the contrary, the existing methods for discrete design are extremely expensive in computational cost or not robust. In this research, an algorithm using tabu search is developed fur the discrete structural designs. The tabu list and the neighbor function of the Tabu concepts are introduced to the algorithm. It defines the number of steps, the maximum number for random searches and the stop criteria. A tabu search is known as the heuristic approach while genetic algorithm and simulated annealing algorithm are attributed to the stochastic approach. It is shown that an algorithm using the tabu search with random moves has an advantage of discrete design. Furthermore, the suggested method finds the reliable optimum for the discrete design problems. The existing tabu search methods are reviewed. Subsequently, the suggested method is explained. The mathematical problems and structural design problems are investigated to show the validity of the proposed method. The results of the structural designs are compared with those from a genetic algorithm and an orthogonal array design.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권4호
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• pp.165-174
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• 2000

This paper presents the application of H$\infty$ control synthesis using LMI optimization method to power system stabilizer(PSS) design. Since power system is usually operated under circumstance of unmeasurable uncertainties and external disturbances, the improvement of small signal stability becomes one of the most important issue for securing system stability and preventing low frequency oscillation phenomena. The LMI optimized H$\infty$ PSS provides robust performance and guarantees the internal stability under these operating conditions. The global optimal H$\infty$ norm is found using LMI convex optimization method which is more systematic than standard two Riccati solution method. The design results are simulated for a case study. We verified that the LMI method shows the best performance characteristic smong standard Riccati method and conventional lead/lag method.

• 한국음향학회지
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• 제22권7호
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• pp.562-572
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• 2003

수동 소나를 이용하여 기동 표적의 위치를 추정하는 정합-표적모델 역산 기법을 개발하였다. 본 기법은 수중음향학 분야에서 널리 사용되는 정합장 역산 방법을 이용하여 관측으로부터 얻어지는 방위와 주파수를 표적모델에 의해 계산되는 값과 정합 시킴으로써 표적의 위치를 파악한다. 효율성과 정확성을 향상시키기 위하여 변수의 탐색 방식은 혼성 최적화 기법을 이용하였는데 일차적으로 광역 최적화 기법으로 알려진 유전자 기법이나 모사 담금질 기법을 적용한 후 단순 비탈 국부최적화 기법을 순차적으로 적용하였다. 제안 기법의 성능 검증을 위하여 3가지의 기동 시나리오에 대하여 시뮬레이션을 실시하였다. 검증 결과 가우시안 확률분포를 갖는 측정오차가 5σ를 가지는 경우에도 견실한 수렴을 보여주었으며 계산 시간면에서도 실용적 인 것으로 밝혀졌다.

• IEIE Transactions on Smart Processing and Computing
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• 제4권4호
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• pp.237-250
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• 2015

This paper describes a hardware-oriented algorithm and its conceptual implementation in a real-time speed limit traffic sign detection system on an automotive-oriented field-programmable gate array (FPGA). It solves the training and color dependence problems found in other research, which saw reduced recognition accuracy under unlearned conditions when color has changed. The algorithm is applicable to various platforms, such as color or grayscale cameras, high-resolution (4K) or low-resolution (VGA) cameras, and high-end or low-end FPGAs. It is also robust under various conditions, such as daytime, night time, and on rainy nights, and is adaptable to various countries' speed limit traffic sign systems. The speed limit traffic sign candidates on each grayscale video frame are detected through two simple computational stages using global luminosity and local pixel direction. Pipeline implementation using results-sharing on overlap, application of a RAM-based shift register, and optimization of scan window sizes results in a small but high-performance implementation. The proposed system matches the processing speed requirement for a 60 fps system. The speed limit traffic sign recognition system achieves better than 98% accuracy in detection and recognition, even under difficult conditions such as rainy nights, and is implementable on the low-end, low-cost Xilinx Zynq automotive Z7020 FPGA.