• Journal of Institute of Control, Robotics and Systems
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• v.6 no.11
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• pp.995-1002
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• 2000

In this paper, fuzzy logic controllers(FLC) are designed for control of flight. For tuning FLC, we used adaptive evolutionary algorithms(AEA) which uses a genetic algorithm(GA) and an evolution strategy (ES) in an adaptive manner in order to take merits of two different evolutionary computations. We used AEA to search for optimal settings of the membership functions shape and gains of the inputs and outputs of FLC. Finally, the proposed controller is applied to the high-angle-of-attack flight system for a supermaneuverable version of the f-18 aircraft and compares with other methods.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1177-1179
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• 1999

This paper presents a design of artificial neural network power system stabilizer(ANNPSS) using adaptive evolutionary algorithm(AEA). We have proposed an adaptive evolutionary algorithm which uses both a genetic algorithm(GA) and an evolution strategy(ES), useing the merits of two different evolutionary computations. ANNPSS shows better control performances than conventional power system stabilizer(CPSS) in three-phase fault with heavy load which is used when tuning ANNPSS. To show the robustness of the proposed ANNPSS, it is applied to damp the low frequency oscillation caused by disturbances such as three-phase fault with normal and light load. the proposed ANNPSS shows better robustness than CPSS.

• Proceedings of the KIEE Conference
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• 1999.11b
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• pp.160-162
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• 1999

This paper presents an optimal design method for fuzzy controllers of HVDC system using adaptive evolutionary algorithm(AEA). We have proposed an adaptive evolutionary algorithm which uses a genetic algorithm and an evolution strategy in an adaptive manner in order to take merits of two different evolutionary computations. AEA is used for tuning fuzzy membership functions, scaling constants and PD gains. The simulation results show that the disturbances are well damped by both controllers and the dynamic performances of fuzzy controllers have better responses than those of PD controllers when mechanical torque changes suddenly.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.490-492
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• 1998

In this paper, fuzzy-PD control system is designed to control angle and position of the inverted pendulum. To optimize parameters of fuzzy-PD controller, we used adaptive evolutionary computation(AEC). AEC uses a Genetic A1gorithm(GA) and an Evolution Strategy(ES) in an adaptive manner in order to take merits of two different evolutionary computations.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.5
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• pp.234-240
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• 2001

Audible noise (AN) produced by corona discharges from high voltage transmission lines is one of the more important considerations in line design. Therefore, line designers must pre-determine the AN using prediction formulas. This paper presents the results of applying evolutionary computation techniques using AN data from lines throughout the world to develop new, highly accurate formulas for predicting a A-weighted AN during heavy rain and stable rain from overhead ac lines. Calculated ANs using these new formulas and existing formulas are compared with measured data.

• Proceedings of the KIPE Conference
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• 2004.07a
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• pp.54-57
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• 2004

In this paper, an optimal design method to have a good performance is researched. The parameters which are senstive to the performance are examined and determined by using evolutionary computations and commercial CAD program to have a good performance. Design method simulated is compared with conventional procedure.

• Proceedings of the KIPE Conference
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• 2004.11a
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• pp.14-17
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• 2004

In this paper, an optimal design method to have a good performance is researched. The parameters which are senstive to the performance are examined and determined by using evolutionary computations and commercial CAD program to have good performance. Design method simulated is compared with conventional procedure.

• Proceedings of the KIEE Conference
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• summer
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• pp.1031-1033
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• 2004

In this paper, an optimal design method to have a good performance is researched. The parameters which are senstive to the performance are examined and determined by using evolutionary computations and commercial CAD program to have good performance. Design method simulated is compared with conventional procedure.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.311-313
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• 2000

본 논문에서는 시간이 흐름에 따라 관측되는 시계열 데이터에 대한 예측을 위한 순차적 베이지안 진화 연산기법을 제안한다. 이 방법에서는 이전 세대의 모델을 바탕으로 예측을 수행하고 새로운 데이터가 주어지면 현재의 예측 모델을 평가하여 더 좋은 모델을 생성하도록 한다. 제안된 방법을 시계열 데이터에 적용한 결과 기조의 방법보다 데이터에 적합한 모델을 학습하고 성공적인 예측을 수행함을 확인하였다.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.54 no.7
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• pp.317-322
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• 2005

Advantages of switched reluctance motor(SRM) include a simple structure, the ability of operation in hash environments and under partial hardware failures, and a wide speed range. However design of SRM for industrial applications is very difficult because motor's inherent none-linearity and sensitivity of design parameter. In this paper, an optimal method for determining design parameters of a switched reluctance motor is researched. The dominant design parameters are stator and rotor pole arc and switching on and off angle. The parameters affecting performance are examined and selected using evolutionary computations and commercial CAD Program. The proposed design process is very fast. reliable and easy to access. The simulated design method proposed is compared with conventional procedure.