• 전기전자학회논문지
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• 제13권3호
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• pp.24-31
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• 2009

The computation time of FEA(finite element analysis) for one model may range from a few seconds up to several hours according to the complexity of the simulated model. If these FEA is used to calculate the objective and the constraint functions during the optimal solution search, it causes very excessive execution time. To resolve this problem, the distributed computing technique using internet web service is proposed in this paper. And the dynamic load balancing mechanisms are established to advance the performance of distributed computing. To verify its validity, this method is applied to a traditional mathematical optimization problem. And the proposed FEA-based optimization using internet distributed computing is applied to the optimal design of the permanent magnet dc motor(PMDCM) for automotive application.

• 전자공학회논문지B
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• 제32B권12호
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• pp.1670-1679
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• 1995

In this paper, an optimal variable structure controller with a multilayer neural inverse identifier is proposed. A multilayer neural network with error back propagation learning algorithm is used for construction the neural inverse identifier which is an observer of the external disturbances and the parameter variations of the system. The variable structure controller with the multilayer neural inverse identifier not only needs a small part of a priori knowledge of the bounds of external disturbances and parameter variations but also alleviates the chattering magnitude of the control input. Also, an optimal sliding line is designed by the optimal linear regulator technique and an integrator is introduced for solving the reaching phase problem. Computer simulation results show that the proposed approach gives the effective control results by reducing the chattering magnitude of control input.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2002년도 제5회 압출 및 인발가공 심포지엄
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• pp.23-32
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• 2002

The torsional forward extrusion is the process that is executed by punch travel and die rotation. The advantages of having the die rotation on this process are that forming load can be reduced and optimal die angle can be increased. This provides a possibility to extrude cold-worded material where a large extrusion force and die angle are required. Also, this process can improve the material properties owing to the high deformation and uniform strain distribution. The forming load and optimal die angle of this process are determined by the upper bound analysis using stream function and the optimization technique. To verify the theoretical result, we have carried out experiments and FE simulations using DEFORM3D.

• 전기학회논문지
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• 제58권12호
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• pp.2385-2390
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• 2009

Based on the detailed analysis of output characteristics of PV array and residential load usage pattern, a design method to calculate optimal battery capacity for stand-alone PV generation systems is proposed. And also, according to power flow Actual irradiation and temperature data are analyzed to compose a PV array simulator and also six representative home appliances are electrically modeled for load simulator, along with 24hours usage pattern. The surplus and insufficient power can be calculated from the proposed simulation platform, so that selection of an optimal battery capacity can be possible. The theoretical analysis and design process will be explained, along with informative simulation results.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 D
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• pp.2096-2098
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• 2002

In this paper, the optimal evasive maneuver strategies for typical subsonic ASM(anti-ship missile) to reach its target ship with high survivability against CIWS(close in weapon system) are studied. The optimal evasive maneuver input is defined by the homing command optimizing the cost function which takes aiming errors of CIWS into account. The optimization problem for the effective evasive maneuver is formulated based on a simple missile dynamics model and a CIWS model. By means of solving the problem, a multiple hypotheses testing method is proposed. Since this method requires generation of too many hypotheses, the hypothesis-pruning technique is adopted. The solution shows that the optimal evasive maneuver is a bang-bane shaped command whose frequency is varied by the aimpoint determination strategy in CIWS.

• 대한전자공학회논문지
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• 제27권9호
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• pp.1364-1371
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• 1990

We propose a time-optimal path planning scheme for the robot manipulator using Hopfield neural network. The time-optimal path planning, which can allow the robot system to perform the demanded tasks with a minimum execution time, may be of consequence to improve the productivity. But most of the methods proposed till now suffers from a significant computational burden and thus limits the on-line application. One way to avoid such a difficulty is to apply the neural networke technique, which can allow the parallel computation, to the minimum time problem. This paper proposes an approach for solving the time-optimal path planning by using Hopfield neural network. The effectiveness of the proposed method is demonstrarted using a PUMA 560 manipulator.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2000년도 추계학술발표논문집
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• pp.251-254
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• 2000

The critical problem in dealing with multiple characteristics is how to compromise the conflict among the selected levels of the design parameters for each individual characteristic. In this study, First, Methodology using SN ratio optimized by univariate technique is proposed and a parameter design procedure to achieve the optimal compromise among several different response variables is developed. Second, to solve the issue on the optimal design for multiple quality characteristics, this study modelled the expected loss function with cross-product terms among the characteristics and derived range of the coefficients of the terms. The model will be used to determine the global optimal design parameters where there exists the conflict among the characteristics, which shows difference in optimal design parameters for the individual characteristics. Third, this paper propose a decision model to incorporates the values assigned by a group of experts on different factors in weighting decision of characteristic. Using this model, SN ratio of taguchi method for each of subjective factors as well as values of weights are used in this comprehensive method for weighting decision of characteristic.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1999년도 가을 학술발표회 논문집
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• pp.301-308
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• 1999

This paper describes the application of genetic algorithm(GA) in the discrete optimal design of truss structures. Stochastic processes generate an intial population of design and then apply principles of natural selection/survival of the fittest to improve the design. GA is applied to minimum weight of truss subject to stress and displacement constraints under multiple loading conditions. First, optimum solutions obtained from GA are compared to verify the reliability of GA with m well-known transmission tower structure which is referred to by other authors. Then, discrete optimal design is performed in satisfying service conditions of truss structure with commercially available fabricated sizes. From the results, it is found that GA search technique is very effective for discrete optimal design of truss structure and has high robustness.

• 한국경영과학회지
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• 제31권1호
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• pp.117-129
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• 2006

In this paper, we consider broadband satellite networks using MF-TDMA (Multi-Frequency Time Division Multiple Access) scheme. We analyze the number of expected lost packets in each terminal, and mathematically formulate optimal buffer and timeslot allocation model to minimize the weighted sum of the numbers of expected lost packets. We also suggest optimal buffer and timeslot allocation scheme based on Lagrangean relaxation technique to solve the proposed model in a fast time. Extensive experiments show that the proposed scheme provides encouraging results.

• International Journal of Control, Automation, and Systems
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• 제6권2호
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• pp.194-203
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• 2008

Iterative learning control (ILC) is a simple and effective method for the control of systems that perform the same task repetitively. ILC algorithm uses the repetitiveness of the task to track the desired trajectory. In this paper, we propose a PID (proportional plus integral and derivative) type ILC update law for control discrete-time single input single-output (SISO) linear time-invariant (LTI) systems, performing repetitive tasks. In this approach, the input of controlled system in current cycle is modified by applying the PID strategy on the error achieved between the system output and the desired trajectory in a last previous iteration. The convergence of the presented scheme is analyzed and its convergence condition is obtained in terms of the PID coefficients. An optimal design method is proposed to determine the PID coefficients. It is also shown that under some given conditions, this optimal iterative learning controller can guarantee the monotonic convergence. An illustrative example is given to demonstrate the effectiveness of the proposed technique.