• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.647-649
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• 2004

When a controller is implemented by a one-chip processor with fixed-point operations, the finite alphabet problem usually occurs since parameters and signals should be taken in a finite set of values. This paper formulates PID finite alphabet PID control problem which combines the PID controller with the finite alphabet problem. We will propose a PID parameter tuning method based on an optimization algorithm under the finite alphabet condition. The PID parameters can be represented by a fixed-point representation, and then the problem is formulated as an optimization with constraints that parameters are taken in the finite set. Some simulation are to be performed to exemplify the performance of the PID parameter tuning method proposed in this paper.

• 분석과학
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• 제6권3호
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• pp.267-274
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• 1993

두 가지 파라미터를 이용한 반복 회귀 최적화법을 미셀 액체 크로마토그래피에서 아미노산과 팹티드류의 분리에 적용하였다. 실험에 사용한 파라미터들은 계면활성제(surfactant)인 SDS와 2-propanol의 농도이다. 이 최적화 방법은 작은 횟수의 초기 실험 수행으로 효과적인 최적화점을 얻을 수 있었다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2011년도 제42회 하계학술대회
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• pp.187-188
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• 2011

This paper proposes the hybrid Complex-PSO algorithm based on the complex search method and particle swarm optimization (PSO) for unconstrained optimization. This hybridization intends to produce faster and more accurate convergence to the optimum value. These hybrid will concentrate on determining the dynamic load model parameters, the ZIP model and induction motor model parameters. Measurement-based parameter estimation, which employs measurement data to derive load model parameters, is used. The theoretical foundation of the measurement-based approach is system identification. The main objective of this paper is to demonstrate how the standard particle swarm optimization and complex method can be improved through hybridization of the two methods and the results will be compared with that of their original forms.

• Journal of Mechanical Science and Technology
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• 제14권10호
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• pp.1122-1130
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• 2000

Based on the value of the Lagrange multiplier and the degree of constraint activeness, a new update rule is proposed for penalty parameters of the ALM method. The theoretical exposition of this suggested update rule is presented by using the algorithmic interpretation and the geometric interpretation of the augmented Lagrangian. This interpretation shows that the penalty parameters can effect the performance of the ALM method. Also, it offers a lower limit on the penalty parameters that makes the augmented Lagrangian to be bounded. This lower limit forms the backbone of the proposed update rule. To investigate the numerical performance of the update rule, it is embedded in our ALM based dynamic response optimizer, and the optimizer is applied to solve six typical dynamic response optimization problems. Our optimization results are compared with those obtained by employing three conventional update rules used in the literature, which shows that the suggested update rule is more efficient and more stable than the conventional ones.

• 한국통신학회논문지
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• 제38A권11호
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• pp.938-943
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• 2013

본 논문에서는 동적 스펙트럼 접근을 위한 유전자 알고리즘 기반 전송 매개변수 최적화 기법을 제안한다. 구체적으로는 전송 매개변수 최적화를 위해 다목적 적합도 함수를 단일 목적 적합도 함수들의 가중합으로 표현하고, 유전자 알고리즘을 이용하여 주어진 전송 시나리오에 최적화된 전송 매개변수 값을 얻는다. 모의실험을 통하여 제안한 다목적 적합도 함수를 이용하여 주어진 시나리오에 따라 전송 매개변수를 최적화한 결과를 보인다.

• 말소리와 음성과학
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• 제8권2호
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• pp.23-30
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• 2016

This paper describes some implementation schemes of CNN in view of mini-batch DNN training for efficient second order optimization. This uses same procedure updating parameters of DNN to train parameters of CNN by simply arranging an input image as a sequence of local patches, which is actually equivalent with mini-batch DNN training. Through this conversion, second order optimization providing higher performance can be simply conducted to train the parameters of CNN. In both results of image recognition on MNIST DB and syllable automatic speech recognition, our proposed scheme for CNN implementation shows better performance than one based on DNN.

• 한국자동차공학회논문집
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• 제13권2호
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• pp.101-107
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• 2005

In this paper, optimized operating parameters were found using multi-dimensional engine simulation software (KIVA-3V) and micro-genetic algorithm for heavy duty diesel engine. The engine operating condition considered was at 1,737 rev/min and 57 % load. Engine simulation model was validated using an engine equipped with a high pressure electronic unit injector (HEUI) system. Three important parameters were used for the optimization - boost pressure, EGR rate and start of injection timing. Numerical optimization identified HCCI-like combustion characteristics showing significant improvements for the soot and $NO_X$ emissions. The optimized soot and $NO_X$ emissions were reduced to 0.005 g/kW-hr and 1.33 g/kW-hr, respectively. Moreover, the optimum results met EPA 2007 mandates at the operating point considered.

• Structural Engineering and Mechanics
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• 제53권6호
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• pp.1127-1141
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• 2015

The optimum design of liquid column dampers in seismic vibration control considering system parameter uncertainty is usually performed by minimizing the unconditional response of a structure without any consideration to the variation of damper performance due to uncertainty. However, the system so designed may be sensitive to the variations of input system parameters due to uncertainty. The present study is concerned with robust design optimization (RDO) of liquid column vibration absorber (LCVA) considering random system parameters characterizing the primary structure and ground motion model. The RDO is obtained by minimizing the weighted sum of the mean value of the root mean square displacement of the primary structure as well as its standard deviation. A numerical study elucidates the importance of the RDO procedure for design of LCVA system by comparing the RDO results with the results obtained by the conventional stochastic structural optimization procedure and the unconditional response based optimization.

• Journal of Welding and Joining
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• 제10권2호
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• pp.32-42
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• 1992

A method of optimization of process parameters in Arc Welding has been discussed in this paper. The method of investigation is based on the numerical calculation of weld bead by a finite element method and non-linear optimization technique is applied to estimated the optimization process parameters from the numerical calculation. The common package program(ANSYS 4.4A) was used to obtain the process parameters for a thin plate arc welding (TIG, CO$_{2}$). The results on some test are satisfactory and the used method of this paper is a useful guide to the optimum welding condition.

• 전력전자학회논문지
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• 제25권3호
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• pp.227-234
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• 2020

This paper presents the methods for the modeling and parameter optimization of the electric vehicle battery. The state variables of the battery are defined, and the test methods for battery parameters are presented. The state-space equation, which consists of four state variables, and the output equation, which is a combination of to-be-determined parameters, are shown. The parameter optimization method is the key point of this study. The least square of the modeling error can be used as an initial value of the multivariable function. It is equivalent to find the minimum value of the error function to obtain optimal parameters from multivariable function. The SIMULINK model is presented, and the 10-hour full operational range test results are shown to verify the performance of the model. The modeling error for 25 degrees is approximately 1% for full operational ranges. The comments to enhance modeling accuracy are shown in the conclusion.