• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.11a
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• pp.587-592
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• 2000

The optimization method based on an enhanced genetic algorithms is proposed for multimodal function optimization in this paper. This method is consisted of two main steps. The first step is global search step using the genetic algorithm(GA) and function assurance criterion(FAC). The belonging of an population to initial solution group is decided according to the FAC. The second step is to decide the similarity between individuals, and to research the optimum solutions by simplex method in reconstructive search space. Two numerical examples are also presented in this paper to comparing with conventional methods.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.1
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• pp.53-61
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• 2014

In this paper, we present the design, fabrication and measurement of high efficiency GaN HEMT power amplifier using harmonic matching technique. In order to achieve high efficiency, harmonic load-pull simulation is performed, that is, the optimum load impedances are determined at $2^{nd}$ and $3^{rd}$ harmonic frequencies as well as at the fundamental. Then, the output matching circuit is designed based on harmonic load-pull simulation. The measurement of the fabricated power amplifier shows the linear gain of 20 dB and $P_{1dB}$(1 dB gain compression point) of 33.7 dBm at 1.85 GHz. The maximum power added efficiency(PAE) of 80.9 % is achieved at the output power of 38.6 dBm, which belongs to best efficiency performance among the reported high efficiency power amplifiers. For W-CDMA input signal, the power amplifier shows a PAE of 27.8 % at the average output power of 28.4 dBm, where an ACLR (Adjacent Channel Leakage Ratio) is measured to be -38.8 dBc. Digital predistortion using polynomial fitting was implemented to linearize the power amplifiers, which allowed about 6.2 dB improvement of an ACLR performance.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.11
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• pp.99-107
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• 2009

Since a long work piece influences the natural frequency of the entire system with a miniature high speed spindle, a bar-feeder is used for a long work piece to improve the vibration characteristics of a spindle system. Therefore, it is very important to design optimally support positions between a bar-feeder and a long work piece for a miniature high speed spindle system. The goal of the current paper is to present an optimization method for the design of support positions between a bar-feeder and a long work piece. This optimization method is effectively composed of the method of design of experiment (DOE), the artificial neural network (ANN) and the genetic algorithm (GA). First, finite element models which include a high speed spindle, a long work piece and the support conditions of a bar-feeder were generated from the orthogonal array of the DOE method, and then the results of natural vibration analysis using FEM were provided for the learning inputs of the neural network. Finally, the design of bar-feeder support positions was optimized by the genetic algorithm method using the neural network approximations.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.1
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• pp.52-64
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• 1995

Robot manipulator is a highly nonlinear-time varying system. Therefore, a lot of control theory has been applied to the system. Robot manipulator has two types of control; one is path planning, another is path tracking. In this paper, we select the path tracking, and for this purpose, propose the intelligent control¬ler which is combined with fuzzy logic and neural network. The fuzzy logic provides an inference morphorlogy that enables approximate human reasoning to apply to knowledge-based systems, and also provides a mathematical strength to capture the uncertainties associated with human cognitive processes like thinking and reasoning. Based on this fuzzy logic, the fuzzy logic controller(FLC) provides a means of converhng a linguistic control strategy based on expert knowledge into automahc control strategy. But the construction of rule-base for a nonlinear hme-varying system such as robot, becomes much more com¬plicated because of model uncertainty and parameter variations. To cope with these problems, a auto-tuning method of the fuzzy rule-base is required. In this paper, the GA-based Fuzzy-Neural control system combining Fuzzy-Neural control theory with the genetic algorithm(GA), that is known to be very effective in the optimization problem, will be proposed. The effectiveness of the proposed control system will be demonstrated by computer simulations using a two degree of freedom robot manipulator.

• Proceedings of the KIEE Conference
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• 1997.07f
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• pp.1974-1977
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• 1997

오늘날 철강 냉간압연의 응용분야에서는 고성능의 장력제어와 높은 신뢰도, 역률 개선, 공장의 생산성 향상 등을 요구하고 있다. 기존의 직류전동기를 대체하는 가변속 교류전동기 구동시스템과 고주파 PWM, 그리고 높은 역률을 보장하는 PWM 컨버터에 의해 이러한 요구사항들은 만족될 수 있다. 이 논문에서는 위에서 언급된 제어요건을 보장하는 철강 생산 설비용 1MVA급 압연시스템을 설명한다. 본 시스템은 하나의 ac/dc PWM 컨버터와 각각 700kw 유도전동기를 구동하는 두대의 PWM 인버터로 구성되어 있다. 제어 알고리듬은 TMS320C40 디지탈 신호처리 프로세서(이하 DSP) 시스템을 이용하여 구현하였다.

• IE interfaces
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• v.17 no.spc
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• pp.141-151
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• 2004

As today's business environment has become more and more competitive, forward as well as backward flows of products among members belonging to a supply chain have been increased. The backward flows of products, which are common in most industries, result from increasing amount of products that are returned, recalled, or need to be repaired. Effective management for the backward flows of products has become an important issue for businesses because of opportunities for simultaneously enhancing profitability and customer satisfaction from returned products. Since third party logistics service providers (3PLs) are playing an important role in reverse logistics operations, they should perform two simultaneous logistics operations for a number of different clients who want to improve their logistics operations for both forward and reverse flows. In this case, distribution networks have been independently designed with respect to either forward or backward flows so far. This paper proposes a mixed integer programming model for the design of network integrating both forward and reverse logistics. Since the network design problem belongs to a class of NP-hard problems, we present an efficient heuristic algorithm based on genetic algorithm (GA), of which the performance is compared to the lower bound by Lagrangian relaxation. Finally, the validity of proposed algorithm is tested using numerical examples.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.2
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• pp.1-8
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• 2006

In this paper, an optimum design technology is developed to find an optimal position of the shock absorber using ADAMS and VisualDOC. A vehicle with a torsion-beam rear suspension is modeled by using ADAMS. Design variables for the optimal positioning of the shock absorber are defined considering the hard points of the chassis structure and design positioning are specified through the sensitivity analysis using a bump-crossing simulation. The objective function is defined as the joint reaction forces of the shock absorber connecting joints of the chassis structure. Sequential Quadratic Programming and Genetic Algorithms are used for this study. To validate the optimized design variables, pothole simulations are performed. GA showed better results than SQP algorithms for this design purpose.

• Proceedings of the KSME Conference
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• 2008.11b
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• pp.2444-2447
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• 2008

A new 3D-PTV algorithm (a Volume PTV) based upon a hybrid fitness function has been constructed. A coherency fitness function is introduced using the information of space and time to sort out the correct particle pairs between the two camera images. The measurement system consists of two-high-definition-cameras($1k{\times}1k$), a Nd-Yag laser and a host computer. The developed algorithm has been employed to investigate the flow features of the cylinder wake. The Reynolds numbers with the cylinder diameter (d=10mm) are 360, 720, 900 and 1260. Two-dimensional displacements of the particles of each camera's image and neighbouring constraints were introduced to reduce the calculation loads. More than 10,000 instantaneous 3D vectors have been obtained by the constructed algorithm. The constructed algorithm could recover more than $80{\sim}90%$ of the particle numbers in the image.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.6
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• pp.720-729
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• 2005

In this paper, we design the indirect adaptive controller using Wavelet Neural Network(WNN) for unknown nonlinear systems. The proposed indirect adaptive controller using WNN consists of identification model and controller. Here, the WNN is used in both Identification model and controller The WNN has advantage of indicating the location in both time and frequency simultaneously, and has faster convergence than MLPN and RBFN. There are several training methods for WNN, such as GD, GA, DNA, etc. In this paper, we present the Extended Kalman Filter(EKF) based training method. Although it is computationally complex, this algorithm updates parameters consistent with previous data and usually converges in a few iterations. Finally, ore illustrate the effectiveness of our method through computer simulations for the Buffing system and the one-link rigid robot manipulator. From the simulation results, we show that the indirect adaptive controller using the EKF method has better performance than the GD method.