• Journal of Mechanical Science and Technology
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• 제19권5호
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• pp.1072-1079
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• 2005

Conceptual design is the first step in the overall process of product design. Its intrinsic uncertainty, imprecision, and lack of information lead to the fact that current conceptual design activities in engineering have not been computerized and very few CAD systems are available to support conceptual design. In most of the current intelligent design systems, approach of principle synthesis, such as morphology matrix, bond graphic, or design catalogues, is usually adopted to deal with the concept generation, in which optional concepts are generally combined and enumerated through function analysis. However, as a large number of concepts are generated, it is difficult to evaluate and optimize these design candidates using regular algorithm. It is necessary to develop a new approach or a tool to solve the concept generation. Generally speaking, concept generation is a problem of concept synthesis. In substance, this process of developing design candidate is a combinatorial optimization process, viz., the process of concept generation can be regarded as a solution for a state-place composed of multi-concepts. In this paper, genetic algorithm is utilized as a feasible tool to solve the problem of combinatorial optimization in concept generation, in which the encoding method of morphology matrix based on function analysis is applied, and a sequence of optimal concepts are generated through the search and iterative process which is controlled by genetic operators, including selection, crossover, mutation, and reproduction in GA. Several crucial problems on GA are discussed in this paper, such as the calculation of fitness value and the criteria for heredity termination, which have a heavy effect on selection of better concepts. The feasibility and intellectualization of the proposed approach are demonstrated with an engineering case. In this work concept generation is implemented using GA, which can facilitate not only generating several better concepts, but also selecting the best concept. Thus optimal concepts can be conveniently developed and design efficiency can be greatly improved.

• 전자공학회논문지SC
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• 제42권6호
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• pp.9-14
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• 2005

본 논문은 특이시스템과 곱셈형 섭동을 가지는 제어기에 대한 비약성 $H_{\infty}$ 제어기 설계 알고리듬을 제안한다. 제어기가 존재할 조건과 비약성 $H_{\infty}$ 제어기 설계 방법 및 제어기에서의 비약성 척도를 선형행렬부등식 접근방법으로 제안한다. 또한, 특이치 분해와 변수치환 및 슈어 여수정리를 이용하여 구한 충분조건은 구하고자 하는 모든 변수의 견지에서 볼록최적화(convex optimization)가 가능한 하나의 선형행렬부등식으로 변형된다. 따라서, 제안한 비약성 $H_{\infty}$ 제어기는 점근적 안정성과 폐루프 특이시스템의 $H_{\infty}$ 노옴 유계 및 제어기의 곱셈형 섭동에 대한 안정성을 보장한다. 또한, 제안한 알고리듬을 이용하면 변수 불확실성을 가지는 특이시스템에 대한 강인 비약성 $H_{\infty}$ 제어기 설계 문제에도 쉽게 확장됨을 보인다. 마지막으로, 수치예제를 통하여 제안한 알고리듬의 타당성을 검증한다.

• 한국지능시스템학회논문지
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• 제13권5호
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• pp.582-589
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• 2003

본 논문에서는 퍼지 피드백 선형화 제어 시스템에 대한 강인 안정성 해석과 제어기 설계에 대해서 말하고 있다. 제어 대상인 비선형 시스템을 모델링 하는데 있어서 Takagi-Sugeno (TS) 퍼지 모델 기법을 이용하였고, 이때 발생할 수 있는 모델 불화실성과 외란에 대해 그것의 최대 최소 범위를 안다고 가정하였다. 모델링을 통해서 얻어진 폐구간 시스템에 대한 안정성 판별은 Diagonal Norm based Linear Differential Inclusions (DNLDI) 구조를 이용하여 $L_2$ 강인 안정성 해석을 하였다. 또한, 퍼지 피드백 선형화 제어 시스템을 안정화 시키는 최대 이득을 얻기 위하여 LMI 최적화 계산법을 기반으로한 수치 해석법을 제시하였다. 제안된 방법의 효과를 확인하기 위해서 강인 안정성 해석 및 제어 설계에 대한 간단한 모의실험을 하였다.

• 한국수자원학회논문집
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• 제35권4호
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• pp.385-395
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• 2002

하천에서의 수질변동을 예측하기 위해 FOEA(First-Order Error-Analysis)와 Monte Carlo 모의를 적용한 추계학적 모형을 개발하였다. 영향메트릭스(Influential matrix)를 이용한 민감도 분석을 실시하여 주요 반응계수를 결정하였고, BFGS(Broyden-Fletcher-Goldfarb-Shanno) 최적화 기법을 사용하여 주요 반응계수 값을 산정하였다. 본 모형을 확정론적 수질해석과 동일한 실제 하도구간에 적용하여 추계학적 수질해석을 실시하였고, 그 결과는 확정론적 해석결과와 잘 일치하였다. 유량과 수질, 반응계수 등에 포함된 불확실도가 하류단의 불확실도에 끼치는 영향을 산정하기 위해 상류단과 지류의 유량 및 수질에 대한 불확실도, 그리고 반응계수의 불확실도에 대한 분석과정이 모형에 포함되었다. 모의수행 결과로부터 각 변수들이 가지고 있는 불확실도가 총 불확실도에 끼치는 영향에 대한 기여도를 산정 할 수 있었다.

• 한국지능시스템학회논문지
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• 제21권3호
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• pp.372-377
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• 2011

본 논문에서는 하이브리드 자기베어링 시스템의 효과적인 제어 방안 마련을 위한 기법 제안을 목표로 한다. 자기베어링 시스템에서의 제어 목적이란, 회전자(rotor)의 회전을 외부의 물리적 접촉 없이 자기장의 힘만으로 동작하도록 베어링의 위치를 최대한 센터에 위치케 하는 것이다. 기본적으로 자기베어링 시스템은 비선형적 동적방정식으로 구성되기 때문에, 제어 목적을 달성하기 위한 제어 입력 신호의 설계가 쉽지 않으며, 외부 환경의 영향에 따른 시스템 파라미터 변화율에도 많이 민감한 편이다. 본 논문에서는 자기베어링 시스템의 비선형성에 대한 해석 방안으로 퍼지 모델링을 통해 시스템을 재해석하게 되며, 제어 목적에 대한 설정은 선형행렬 부등식 기반 안정화 문제로 변환하여 제어 입력을 설계하고자 한다. 해당 퍼지 모델링 및 제어 알고리즘의 정당성은 시뮬레이션을 통해 검증된다.

• Composites Research
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• 제35권3호
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• pp.188-195
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• 2022

본 논문은 멀티스케일 공정-구조 해석의 방법론을 제안하고 단섬유층과 직물층으로 이루어진 배터리 하우징 파트에 적용한다. 특별히 마이크로스케일 대표체적요소(RVE: Representative Volume Element)안 기지의 불확정성을 고려하였다. 마이크로스케일의 RVE내 기지 물성의 랜덤한 공간내 분포는 KLE(Karhunen-Loeve Expansion)을 통해 구현하였다. 공간상 랜덤분포된 기지 물성을 갖는 RVE의 유효 물성을 전산균질화를 통해 얻어 매크로스케일 유한요소 모델에 매핑하였다. 또한 하이브리드 공정해석을 통해 압축 성형 해석으로부터 얻은 잔류응력과 섬유배향을 매핑한 유한요소 모델과 드레이핑 공정 해석결과로부터 얻어진 섬유배향을 매핑한 모델을 결합하였다. 본 연구에 제안된 방법은 배터리 하우징 뿐만 아니라 다양한 재료 구성을 갖는 복합재료의 공정-구조해석을 통해 설계요구도를 엄밀하게 평가할 수 있을 것이라 기대된다.

• Geomechanics and Engineering
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• 제31권2호
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• pp.129-147
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• 2022

The properties of soil are naturally highly variable and thus, to ensure proper safety and reliability, we need to test a large number of samples across the length and depth. In pile foundations, conducting field tests are highly expensive and the traditional empirical relations too have been proven to be poor in performance. The study proposes a state-of-art Particle Swarm Optimization (PSO) hybridized Artificial Neural Network (ANN), Extreme Learning Machine (ELM) and Adaptive Neuro Fuzzy Inference System (ANFIS); and comparative analysis of metaheuristic models (ANN-PSO, ELM-PSO, ANFIS-PSO) for prediction of bearing capacity of pile foundation trained and tested on dataset of nearly 300 dynamic pile tests from the literature. A novel ensemble model of three hybrid models is constructed to combine and enhance the predictions of the individual models effectively. The authenticity of the dataset is confirmed using descriptive statistics, correlation matrix and sensitivity analysis. Ram weight and diameter of pile are found to be most influential input parameter. The comparative analysis reveals that ANFIS-PSO is the best performing model in testing phase (R² = 0.85, RMSE = 0.01) while ELM-PSO performs best in training phase (R² = 0.88, RMSE = 0.08); while the ensemble provided overall best performance based on the rank score. The performance of ANN-PSO is least satisfactory compared to the other two models. The findings were confirmed using Taylor diagram, error matrix and uncertainty analysis. Based on the results ELM-PSO and ANFIS-PSO is proposed to be used for the prediction of bearing capacity of piles and ensemble learning method of joining the outputs of individual models should be encouraged. The study possesses the potential to assist geotechnical engineers in the design phase of civil engineering projects.

• International Journal of Aeronautical and Space Sciences
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• 제16권2호
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• pp.278-294
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• 2015

Considering the guidance and control problem of the near space interceptor (NSI) during the terminal course, this paper proposes a three-channel independent integrated guidance and control (IGC) scheme based on the backstepping sliding mode and finite time disturbance observer (FTDO). Initially, the three-channel independent IGC model is constructed based on the interceptor-target relative motion and nonlinear dynamic model of the interceptor, in which the channel coupling term and external disturbance are regarded as the total disturbances of the corresponding channel. Then, the FTDO is introduced to estimate the target acceleration and control system loop disturbances, and the feed-forward compensation term based on the estimated values is employed to effectively remove the effect of disturbances in finite time. Subsequently, the IGC algorithm based on the backstepping sliding mode is also given to obtain the virtual control moment. Furthermore, a robust least-squares weighted control allocation (RLSWCA) algorithm is employed to distribute the previous virtual control moment among the corresponding aerodynamic fins and reaction jets, which also takes into account the uncertainty in the control effectiveness matrix. Finally, simulation results show that the proposed IGC method can obtain the small miss distance and smooth interceptor trajectories.

• Smart Structures and Systems
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• 제22권5호
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• pp.547-560
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• 2018

This paper investigates the operation of the $H_{\infty}$ static output-feedback controller to reduce dynamic responses under seismic excitation on the five-story and benchmark 20 story building with parametric uncertainties. Linear matrix inequality (LMI) control theory is applied in this system and then to achieve the desired LMI formulations, some transformations of the LMI variables is used. Conversely uncertainties due to material properties, environmental loads such as earthquake and wind hazards make the uncertain system. This problem and its effects are studied in this research. Also to decrease the transition of large amount of data between sensors and controller, avoiding the disruption of whole control system and economy problems, the operation of the decentralized controllers is investigated in this paper. For this purpose the comparison between the performance of the centralized, fully decentralized and partial decentralized controllers in uncoupled and coupled cases is performed. Also, the effect of the changing the number of stories in substructures is considered. Based on the numerical results, the used control algorithm is very robust against the parametric uncertainties and structural responses are decreased considerably in all the control cases but partial decentralized controller in coupled form gets the closest results to the centralized case. The results indicate the high applicability of the used control algorithm in the tall shear buildings to reduce the structural responses and its robustness against the uncertainties.

• Neonatal Medicine
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• 제25권1호
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• pp.1-6
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• 2018

Extremely low birth weight infants remain at increased risk of intraventricular hemorrhage from the fragile vascular bed of the germinal matrix; the roles of hypotension (ischemia) and reperfusion (hyperemia) in the development of intraventricular hemorrhage are still debated. Cerebrovascular pressure autoregulation protects the brain by maintaining constant cerebral blood flow despite changes in blood pressure. The ontogeny of cerebrovascular pressure autoregulation has not been well established and uncertainty remains about the optimal arterial blood pressure required to support brain perfusion. Another important aspect of premature cerebral hemodynamics is the critical closing pressure--the arterial blood pressure at which cerebral blood flow ceases. Interestingly, in premature infants, the critical closing pressure approximates the mean arterial blood pressure. Often in this unique population, cerebral blood flow occurs only during systole when the diastolic arterial blood pressure is equal to the critical closing pressure. Moreover, the diastolic closing margin, a metric of cerebral perfusion that normalizes diastolic arterial blood pressure to the critical closing pressure, may be a better measure than arterial blood pressure for defining cerebral perfusion in premature infants. Elevated diastolic closing margin has been associated with intraventricular hemorrhage. This review summarizes the current state of understanding of cerebral hemodynamics in premature infants.