• 한국항공우주학회지
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• 제36권1호
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• pp.22-30
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• 2008

본 논문은 헬리콥터 기동비행문제를 비선형 최적제어기법으로 정식화 하고 이를 indirect method를 적용하여 해석하는 기법에 대해 연구하였다. 주어진 기동비행 경로에 대한 오차를 벌칙함수 형태의 가격(비용, 목적)함수로 채택하고 이를 최소화하도록 정식화하면 기동비행은 구속조건이 없는 최적제어문제로 정식화 된다. 정식화 결과로 얻어지는 이점 경계값 문제는 Multiple Shooting Method (MSM)을 적용하여 해석하였다. 본 논문은 shooting node의 수와 상태변수의 초기화 방법 등이 수치해법에 주는 영향을 분석하여 수렴성 확보에 필요한 조건을 식별하고 수렴반경을 증가시킬 수 있는 방안에 초점을 두었다. 연구결과는 헬리콥터와 같이 불안정한 시스템의 최적제어 문제에 indirect method를 적용하는 경우 수치해법의 안정성과 수렴성을 확보할 수 있는 방법을 제시한다.

• Journal of Mechanical Science and Technology
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• 제18권9호
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• pp.1512-1518
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• 2004

Rescaled Simulated Annealing (RSA) has been adapted to solve combinatorial optimization problems in which the available computational resources are limited. Simulated Annealing (SA) is one of the most popular combinatorial optimization algorithms because of its convenience of use and because of the good asymptotic results of convergence to optimal solutions. However, SA is too slow to converge in many problems. RSA was introduced by extending the Metropolis procedure in SA. The extension rescales the state's energy candidate for a transition before applying the Metropolis criterion. The rescaling process accelerates convergence to the optimal solutions by reducing transitions from high energy local minima. In this paper, structural optimization examples using RSA are provided. Truss structures of which design variables are discrete or continuous are optimized with stress and displacement constraints. The optimization results by RSA are compared with the results from classical SA. The comparison shows that the numbers of optimization iterations can be effectively reduced using RSA.

• 조명전기설비학회논문지
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• 제29권5호
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• pp.34-40
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• 2015

This paper presents an application of Differential Search (DS) meta-heuristic optimization algorithm for optimal operation of micro grid system. DS algorithm has the benefit of high convergence rate and precision compared to other optimization methods. The micro grid system consists of a wind turbine, a diesel generator, and a fuel cell. The simulation is applied to micro grid system only. The wind turbine generator is modeled by considering the characteristics of variable output. One day load data which is divided every 20 minute and wind resource for wind turbine generator are used for the study. The method using the proposed DS algorithm is easy to implement, and the results of the convergence performance are better than other optimization algorithms.

• 대한기계학회논문집A
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• 제29권1호
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• pp.22-29
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• 2005

A material cloud method, which is a new topology optimization method, is presented. In MCM, an optimal structure can be found out by manipulating sizes and positions of material clouds, which are lumps of material with specified properties. A numerical analysis for a specific distribution of material clouds is carried out using fixed background finite element mesh. Optimal material distribution can be element-wisely extracted from material clouds' distribution. In MCM, an expansion-reduction procedure of design domain for finding out better optimal solution can be naturally realized. Also the convergence of material distribution is faster and well-defined material distribution with fewer intermediate densities can be obtained. In addition, the control of minimum-member sizes in the material distribution can be realized to some extent. In this paper, basic concept of MCM is introduced, and formulation and optimization results of MCM are compared with those of the traditional density distribution method(DDM).

• Journal of the Korean Statistical Society
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• 제20권1호
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• pp.29-43
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• 1991

Two data-based bandwidth selectors which are optimal in the sense that they achieve n$\^$-$\frac{1}{2}$/ rate of convergence in kernel density estimation are proposed. The proposed bandwidth selectors are constructed by modifying Park and Marron's plug-in method. The first modification is taking Taylor expansion of the mean integrated squared error to two more terms than in the case of plug-in method. The second is estimating more accurately the functionals of the unknown density appeared in the minimizer of the expansion by using higher order kernels. The proposed bandwidth selectors were proved to be optimal in terms of convergence rate. According to small-sample Monte Carlo studies, the proposed bandwidth selectors showed better performance than all the other bandwidth selectors considered in the simulation.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권4호
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• pp.270-275
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• 2016

We present an approach for acceleration actor-critic algorithm for reinforcement learning with continuous action space. Actor-critic algorithm has already proved its robustness to the infinitely large action spaces in various high dimensional environments. Despite that success, the main problem of the actor-critic algorithm remains the same-speed of convergence to the optimal policy. In high dimensional state and action space, a searching for the correct action in each state takes enormously long time. Therefore, in this paper we suggest a search accelerating function that allows to leverage speed of algorithm convergence and reach optimal policy faster. In our method, we assume that actions may have their own distribution of preference, that independent on the state. Since in the beginning of learning agent act randomly in the environment, it would be more efficient if actions were taken according to the some heuristic function. We demonstrate that heuristically-accelerated actor-critic algorithm learns optimal policy faster, using Educational Process Mining dataset with records of students' course learning process and their grades.

• 한국산업융합학회 논문집
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• 제26권6_1호
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• pp.985-991
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• 2023

This study proposes a solution to the voltage drop in electric vehicle chargers, due to the parasitic resistance and inductance of power cables when the chargers are separated by large distances. A method using multi-level electric vehicle chargers that can output power in stages, without installing an additional energy supply source such as a reactive power compensator or an energy storage system, is proposed. The voltage drop over the power cables, to optimize the charging scheduling, is derived. The obtained voltage drop equation is used to formulate the constraints of the optimization process. To validate the effectiveness of the obtained results, an optimal charging scheduling is performed for each period in a case study based on the assumed charging demands of three connected chargers. From the calculations, the proposed method was found to generate an annual profit of $20,800 for a $12,500 increase in installation costs.

• 융합신호처리학회 학술대회논문집
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• 한국신호처리시스템학회 2005년도 추계학술대회 논문집
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• pp.306-309
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• 2005

We consider the multi-objective optimization of a multi-service arrayed-waveguide grating-based single-hop metro WDM network with the two conflicting objectives of maximizing throughput while minimizing delay. We develop and evaluate a genetic algorithm based methodology for finding the optimal throughput-delay tradeoff curve, the so-called Pareto-optimal frontier. Our methodology provides the network architecture and the Medium Access Control protocol parameters that achieve the Pareto-optima in a computationally efficient manner. The numerical results obtained with our methodology provide the Pareto-optimal network planning and operation solution for a wide range of traffic scenarios. The presented methodology is applicable to other networks with a similar throughput-delay tradeoff.

• 한국산업융합학회 논문집
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• 제18권2호
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• pp.67-74
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• 2015

Two-wheeled driying mobild robots are precise controlled in terms of linear contol methods without considering the nonlinear dynamical characteristics. However, in the high maneuvering situations such as fast turn and abrupt start and stop, such neglected terms become dominant and heavy influence the overall driving performance. This study describes the nonlinear optimal control method to take advantage of the exact nonlinear dynamics of the balancing robot. Simulation results indicate that the optimal control outperforms in the respect of transient performance and required wheel torques. A design example is suggested for the state matrix that provides design flexibility in the control. It is shown that a well-planned state matrix by reflecting the physics of a balancing robot greatly conrtibutes to the driving performance and stability.

• 한국생산제조학회지
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• 제23권5호
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• pp.456-464
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• 2014

Commercial vehicle drivers typically feel more fatigued compared to general-public drivers. because they spend longer periods of time driving and experience more rough road conditions. This study showed that the application of a magnet, a linear spring, and a seat suspension with nonlinear characteristics was the optimal design to increase comfort while driving. The resonant frequency for the optimal design suspension was 2.8 Hz, and the stiffness was analyzed through displacement-load experiments. Vibration transmissibility was analyzed by suspension stiffness and the existing dynamic compression. The magnetic spring type was at 0.875. As a result, the X-type magnetic spring performed better than the existing spring at 0.729.