• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.6
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• pp.301-308
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• 2018

This paper presents an optimal design method of a hybrid structural control system considering multi-hazard. Unlike a typical structural control system in which one system is designed for one specific type of hazard, a simultaneous optimal design method for both active and passive control systems is proposed for the mitigation of seismic and wind induced vibration responses of structures. As a numerical example, an optimal design problem is illustrated for a hybrid mass damper(HMD) and 30 viscous dampers which are installed on a 30 story building structure. In order to solve the optimization problem, a self-adaptive Harmony Search(HS) algorithm is adopted. Harmony Search algorithm is one of the meta-heuristic evolutionary methods for the global optimization, which mimics the human player's tuning process of musical instruments. A self-adaptive, dynamic parameter adjustment algorithm is also utilized for the purpose of broad search and fast convergence. The optimization results shows that the performance and effectiveness of the proposed system is superior with respect to a reference hybrid system in which the active and passive systems are independently optimized.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.3
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• pp.248-254
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• 2009

The use of evolutionary algorithm is limited in the field of aerodynamics, mainly because the population-based search algorithm requires excessive CPU time. In this paper a coupling method with adaptive range genetic algorithm for floating point and back-propagation neural network is proposed to efficiently obtain a converged solution. As a result, it is shown that a reduction of 14% and 33% respectively in wave drag and its consumed time can be achieved by the new method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.5
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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.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.179-182
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• 2002

GA(Genetic Algorithm)는 자연계 진화를 모방한 계산 알고리즘으로서 단순하고 응용이 쉽기 때문에 여러 분야에 전역적 최적해 탐색에 많이 사용되고 있다. 최근에는 하드웨어를 구성하는 방법의 하나로서 사용되어 진화하드웨어라는 분야를 탄생시켰다. 이와 함께 GA의 연산자체를 하드웨어로 구현하는 GA processor(GAP)의 필요성도 증가하고 있다. 특히 진화하드웨어를 소프트웨어상에서 진화 시키는 것이 아닌 GAP에 의해 진화 시키는 것은 독립된 구조의 진정한 EHW 설계에 필수적이 될 것이다. 본 논문에서는 GAP 설계 방법을 제안하고 이를 이용하여 진화하드웨어로 State machine을 구현하고자 한다. State machine의 경우 구조상 피드백이 필요하기 때문에 가산기나 멀티플렉서보다는 훨씬 복잡하고 설계가 까다로운 구조이다. 제안된 방법을 통하여 명시적 설계가 어려운 하드웨어 설계에 GAP를 이용한 하드웨어의 진화에 적용함으로써 그 유용성을 보인다.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.870-875
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• 2004

Current trend of design technologies shows engineers to objectify or automate the given decision-making process. The numerical optimization is an example of such technologies. However, in numerical optimization, the uncertainties are uncontrollable to efficiently objectify or automate the process. To better manage these uncertainties, Taguchi method, reliability-based optimization and robust optimization are being used. To obtain the target performance with the maximum robustness is the main functional requirement of a mechanical system. In this research, the robust design strategy is developed based on the DACE and the global optimization approaches. The DACE modeling, known as the one of Kriging interpolation, is introduced to obtain the surrogate approximation model of the system. The robustness is determined by the DACE model to reduce the real function calculations. The simulated annealing algorithm of global optimization methods is adopted to determine the global robust design of a surrogated model. The mathematical problems and the MEMS design problem are investigated to show the validity of the proposed method.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.2
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• pp.305-313
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• 2002

The genetic algorithm(GA), an optimization technique based on the theory of natural selection, has proven to be relatively robust means to search for global optimum. It is converged near to the global optimum point without auxiliary information such as differentiation of function. When studying some optimization problems with continuous variables, it was found that premature saturation was reached that is no further improvement in the object function could be found over a set of iterations. Also, the general GA oscillates in the region of the new global optimum point so that the speed of convergence is decreased. This paper is to propose the concept of restarting and elitist preserving strategy as a measure to overcome this difficulty. Some benchmark examples are studied involving 3-bar truss and cantilever beam with plane stress elements. The modifications to GA improve the speed of convergence.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.894-896
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• 1999

PID 제어는 50년의 역사를 갖기 때문에 현장의 사용자는 이 제어방식에 익숙해져 있으며, 제어장치의 구성이 간단하며 제어기의 최적동조가 가능하므로 많은 분야에서 사용되고 있다[1]. 그러나 PID 제어기에 의해서 얻은 결과에 대하여 만족하기 위해서는 많은 시행착오를 겪어야 한다. 또한 만족하는 결과를 얻었다고 할지라도 외란, 플랜트의 동특성이 바뀌는 경우 시스템을 추종하지 못하기 때문에 파라미터를 재조정하여야 한다. 유전 알고리즘은 자연세계의 진화 현상에 기초한 계산모델로서 John Holland에 의해서 1975년에 개발된 전역적인 최적화 알고리즘이며[1][2], 비선형 고차원, 불연속, 다중모드, 노이즈 함수 등에 대하여 강건함을 보여주고, 복잡한 탐색 공간에서 최적 값을 스스로 발견하는 학습 능력을 갖는다. 이 방법은 재생산, 교배, 돌연변이를 통하여 최적해를 찾은 방법으로 1989년에 D. E. Goldgerg에 의해서 체계적으로 정리된 후 여러 분야에서 응용되고 있다[3][4]. 그러나 유전 알고리즘은 목적함수만을 이용하여 해집단을 탐색하기 때문에 숙련운전자가 원하는 제어 특성 명세인 상승시간, 정착시간, 초과량(oveshoot) 둥을 구체적으로 명시하여 제어에 반영할 수 없다. 또한, 유전 알고리즘은 입력 값이 크게 바뀔 경우 다른 시스템으로 인식하여 새로운 탐색을 수행하는 단점을 가지고 있다. 본 논문은 첫째, 기준모델을 도입하여 플랜트의 성능을 기준모델로 표현하여 플랜트가 요구하는 성능지표를 정량적으로 규정하는 것이 가능하였다. 또한, 이것은 미지 플랜트 동특성을 식별하기 위한 신호로 사용되어, 플랜트의 정보를 얻는데 이용되었다. 즉, 기준모델과 플랜트 출력사이의 추종 오차 정보가 적응기구인 PID 유전제어기의 입력으로 사용되며, 구형파 입력의 경우에도 기준모델과 플랜트의 출력차는 크게 변하지 않는다. 따라서, 유전 알고리즘의 목적함수에 기준 모델을 제안 적용하여 안정적이고, 세밀한 제어를 수행하였다. 둘째, PID의 간단하면서 확실한 제어가 가능하다는 점과 전역적인 최적값을 찾을 수 있는 유전 알고리즘을 적용하여 고속제어를 요하는 직류 서보 모터(DC Servo Motor) 운전 시 실시간 파라미터 동조에 적용하였다.

• Journal of Korean Society of Steel Construction
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• v.12 no.6
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• pp.629-638
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• 2000

With the positive features of simulated annealing algorithms such as simplicity of the algorithm and the possibility of finding global optimum solution, SA algorithm has been widely applied to structural optimization problems. However, the algorithms are far from practical applications in structural design or optimization of building structures due to requirement of a large number of iterations and dependency on cooling schedule and stopping criteria. In this paper, with the modification of annealing process and stopping criteria, a MSA algorithm is presented in the form of two phase annealing process for optimal seismic design of braced structures. The performance of the proposed algorithm has been illustrated in detail.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.7
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• pp.620-628
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• 2016

The homotopy algorithm provides a robust method for determining optimal control, in some cases the global minimum solution, as a continuation parameter is varied gradually to regulate the contributions of the nonlinear terms. In this paper, the Successive Backward Sweep (SBS) method, which is insensitive to initial guess, augmented with a homotopy algorithm is suggested. This approach is effective for highly nonlinear problems such as low-thrust trajectory optimization. Often, these highly nonlinear problems have multiple local minima. In this case, the SBS-homotopy method enables one to steadily seek a global minimum.

• Journal of Korean Society of Steel Construction
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• v.14 no.6
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• pp.783-791
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• 2002

An improved formulation for multi-objective optimization was proposed. This formulation was applied to steel seismic loads. The multi-objective optimization problem was formulated with minimum structural weight, maximum strstability. The global criterion method was employed to find a rational solution closest to the ideal solution for the optimization problem using standard steel profile, To efficiently solve the optimization problem, the decomposition meth both system-level and element-level was used. In addition, various techniques including efficient reanalysis technique intermediate variables and sensitivity analysis using an automatic differentiation(AD) were incorporated. Moreover the reamong section properties fitted to the section profile used in order to link the system level and the element level. From numerical investigation, it could be stated that the proposed method will lead to the more rational design compared with one.