• 로봇학회논문지
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• 제8권2호
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• pp.92-103
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• 2013

Humanoid robot is the most intimate robot platform suitable for human interaction and services. Biped walking is its basic locomotion method, which is performed with combination of joint actuator's rotations in the lower extremity. The present work employs humanoid robot simulator and numerical optimization method to generate optimal joint trajectories for biped walking. The simulator is developed with Matlab based on the robot structure constructed with the Denavit-Hartenberg (DH) convention. Particle swarm optimization method minimizes the cost function for biped walking associated with performance index such as altitude trajectory of clearance foot and stability index concerning zero moment point (ZMP) trajectory. In this paper, instead of checking whether ZMP's position is inside the stable region or not, reference ZMP trajectory is approximately configured with feature points by which piece-wise linear trajectory can be drawn, and difference of reference ZMP and actual one at each sampling time is added to the cost function. The optimized joint trajectories realize three phases of stable gait including initial, periodic, and final steps. For validation of the proposed approach, a small-sized humanoid robot named DARwIn-OP is commanded to walk with the optimized joint trajectories, and the walking result is successful.

• 설비공학논문집
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• 제18권5호
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• pp.426-433
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• 2006

The requirements for the optimal building system design is numerous. However, most system designers do not take care of various design strategies. They often argue that the proper simulation tools are not existed to solve the implicated design requirements and the time to consider many alternatives of building systems are insufficient. The aim of this study is to develop the optimization interface program that considers various system design variables and eventually find both the optimal values of annual energy use and cost. Therefore, Doe2Opt is developed to easily perform simulation-optimization process based on DOE2 and GenOpt, and minimizes energy cost of small-to-medium sized building for 6.7% and that of large sized building for 3% with optimizing several HVAC system variables.

• 한국지진공학회논문집
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• 제14권2호
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• pp.1-13
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• 2010

본 논문에서는 비선형 지진격리교량의 최적 설계 방법을 제시하였다. 최적설계를 위한 목적함수로는 교각과 지진격리장치의 파괴확률을 고려하였으며, 상충하는 두 목적함수를 동시에 최적화하는 다수의 해를 효율적으로 검색하고자 유전자 알고리즘에 기반한 다목적 최적화기법을 도입하였다. 또한, 최적화 과정에서 요구되는 다수의 비선형 시간이력해석을 수행하지 않고도 교량의 확률적 응답을 효율적으로 예측할 수 있는 추계학적 선형화 방법을 접목하였다. 제시하는 방법의 효율성을 검증하기 위한 수치 예로서 실제 교량인 남한강교를 고려하였고, 제안하는 방법과 기존 비선형 시간이력해석을 이용한 생애주기비용 기반 설계법을 각각 적용하여 내진성능을 비교하였다. 내진성능을 비교한 결과, 제시하는 방법이 기존의 비용에 기반한 최적설계보다 우수한 성능 및 경제성을 보임을 검증하였다. 또한, 다양한 지진하중에 대해서도 제안된 방법이 보다 개선된 성능을 보임을 확인하였다.

• 한국생산제조학회지
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• 제20권4호
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• pp.412-418
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• 2011

Reliability-based Topology optimization(RBTO) is to get an optimal design satisfying uncertainties of design variables. Although RBTO based on homogenization and density distribution method has been done, RBTO based on BESO has not been reported yet. This study presents a reliability-based topology optimization(RBTO) using bi-directional evolutionary structural optimization(BESO). Topology optimization is formulated as volume minimization problem with probabilistic displacement constraint. Young's modulus, external load and thickness are considered as uncertain variables. In order to compute reliability index, four methods, i.e., RIA, PMA, SLSV and ADL(adaptive-loop), are used. Reliability-based topology optimization design process is conducted to obtain optimal topology satisfying allowable displacement and target reliability index with the above four methods, and then each result is compared with respect to numerical stability and computing time. The results of this study show that the RBTO based on BESO using the four methods can effectively be applied for topology optimization. And it was confirmed that DLSV and ADL had better numerical efficiency than SLSV. ADL and SLSV had better time cost than DLSV. Consequently, ADL method showed the best time efficiency and good numerical stability.

• 대한토목학회논문집
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• 제35권2호
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• pp.407-415
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• 2015

철도사업을 추진함에 있어, 지금까지 대부분의 사업은 노선과 선형계획은 엔지니어가 현장 사전조사 결과 및 지형도 등을 이용하여 한정된 수의 대안을 설정하여 분석하는 방식으로 수행되어 왔다. 본 연구에서는 유전자 알고리즘을 이용한 지능형 철도선형계획 프로그램(ei-Rail)을 개발하여, 가능한 모든 대안에 대하여 선형요소 및 공사비에 대한 평가를 가능하게 하였다. 그리고 기존에 계획된 노선에 대한 비교 평가를 통하여 기존 대안보다 사업비를 절감할 수 있을 뿐만 아니라, 이에 소요되는 비용과 시간도 단축할 수 있는 것으로 나타났다. 본 연구의 결과는 향후 국내외 철도사업 계획 수립에 소요되는 비용과 시간, 그리고 전체 사업비 절감을 가능케 함으로써 철도분야 발전에 도움이 될 수 있을 것으로 기대할 수 있다.

• 제어로봇시스템학회논문지
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• 제20권7호
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• pp.750-755
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• 2014

Product shortage which causes backordering and/or lost sales cost is very popular in chemical industries, especially in commodity polymer business. This study deals with backordering cost in the supply chain optimization model under the framework of process-inventory network. Classical economic order quantity model with backordering cost suggested optimal time delay and lot size of the final product delivery. Backordering can be compensated by advancing production/transportation of it or purchasing substitute product from third party as well as product delivery delay in supply chain network. Optimal solutions considering all means to recover shortage are more complicated than the classical one. We found three different solutions depending on parametric range and variable bounds. Optimal capacity of production/transportation processes associated with the product in backordering can be different from that when the product is not in backordering. The product shipping cycle time computed in this study was smaller than that optimized by the classical EOQ model.

• International Journal of Contents
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• 제7권2호
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• pp.1-5
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• 2011

Allocation of computing resources is a crucial issue when dealing with a huge number of tasks to be completed according to a given deadline and cost constraints. The task scheduling to several resources (e.g. grid, cloud or a supercomputer) with different characteristics is not trivial, especially if a trade-off in terms of time and cost is considered. We propose an allocation approach able to fulfill the given requirements about time and cost through the use of optimizing techniques and an adaptive behavior. Simulated productions of tasks have been run in order to evaluate the characteristics of the proposed approach.

• Communications for Statistical Applications and Methods
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• 제6권1호
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• pp.99-106
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• 1999

This paper considers an imperfect repair model for which the repairable system is maintained preventively at periodic times and is replaced by a new system when a predetermined number of preventive maintenance has been applied. our main objective of this is to determine the optimal number of preventive maintenances before the system is replaced and the optimal length of interval between two consecutive preventive maintenances under a new repair model which is referred to as an ineffective preventive maintenance. Such a model assumes a periodic preventive maintenance in which the system is effectively maintained with a certain probability. Otherwise the system is not improved at all after each maintenance and thus the failure rate remains the same as before. The criteria to determine the optimal number of preventive maintenances and length of period is the expected cost rate per unit time for an infinite time span. We give the explicit expressions for the expected cost rate per unit time. Some numerical examples are presented for illustrative purposes.

• 전기학회논문지
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• 제61권3호
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• pp.459-465
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• 2012

In this paper, we present a non-fragile guaranteed cost control design method for uncertain nonlinear systems with time varying delays in state and control input, even though the controller gain is perturbed. The uncertain nonlinear term in the systems is norm bounded and the linear matrix inequality(LMI) optimization method is employed as a stability analysis of the systems. We design a robust controller and show the asymptotical stability of uncertain time-varying systems based on Lyapunov method. Also, we guarantee a specific level of performance of the systems. The simulations are carried out to demonstrate the effectiveness of the proposed method.

• International Journal of Control, Automation, and Systems
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• 제5권6호
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• pp.691-700
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• 2007

This paper proposes a simple but effective design method of PID control using a numerical optimization method. In order to achieve both stability and performance, gain and phase margins and performance indices of step response directly compose of the cost function. Hence, the proposed approach is a multiobjective optimization problem. The main effectiveness of this approach results from the strong capability of the used optimization method. A one-dimensional example concerning gain margin illustrates the practical applicability of the optimization method. The present approach has many degrees of freedom in controller design by only adjusting related weight constants. The attained PID controller is compared with Wang#s and Ho#s methods, IAE, and ISE for a high-order process, and the simulation result for various design targets shows that the proposed approach achieves desired time-domain performance with a guarantee of frequency-domain stability.