• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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• pp.117-122
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• 1998

A servo system requires faster and more accurate dynamic reponses. Generally a PD control is mainly used to obtain the precision, and in the other hand a fuzzy control to improve the transient response and to cope with the nonlinearity of systems. Recently hybrid control, which is attempted to combine the advantages of PD control and a Fuzzy control was proposed, but this technique requires complicate design procedures. Therefore in this paper, designed on the Fuzzy controller with a various series rules, width of membership functions. And also it was showed to have the excellent adaptive performances against disturbances and the usefulness of this controller from the results of simulations.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.436-440
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• 1992

As an approach to design the intelligent controller, this paper proposes a new FNN(Fuzzy Neural Network) control method using the hybrid combination of fuzzy logic control and neural network. The proposed FNN controller has two important capabilities, namely, adaptation and learning. These functions are performed by the following process. Firstly, identification of the parameters and estimation of the states for the unknown plant are achieved by the MNN(Model Neural Network) which is continuously trained on-line. And secondly, the learning is performed by FNN controller. The error back propagation algorithm is adopted as a learning technique. The effectiveness of the proposed method will be demonstrated by computer simulation of a two d.o.f. robot manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.369-369
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• 2000

Control system by means of fuzzy theory has demonstrated its robustness in applying to the high-order and nonlinear dynamic system in that it can utilizes the human expert knowledges in system design. In this paper, first, the design methodology of HFC combined PID controller with fuzzy controller by membership function of weighting coefficient is proposed. Second, Second, an auto-tuning algorithms utilizing the simplified reasoning method and genetic algorithms is presented to improve the performance of hybrid fuzzy controller. Especially, in order to obtain the optimal scaling factors and PID parameters of HFC using GA based on advanced initial individual, three kinds of estimation modes such as basic, contraction, and expansion mode are effectively utilized. The proposed HFC is evaluated and discussed in ITAE, overshoot and rising time to show applicability and superiority with simulation results.

• 한국지능시스템학회논문지
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• 제26권5호
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• pp.351-360
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• 2016

Rapid population growth with high living standards and high electronics use for personal comfort has raised the electricity demand exponentially. To fulfill this elevated demand, conventional energy sources are shifting towards low production cost and long term usable alternative energy sources. Hybrid renewable energy systems (HRES) are becoming popular as stand-alone power systems for providing electricity in remote areas due to advancement in renewable energy technologies and subsequent rise in prices of petroleum products. Wind and solar power are considered feasible replacement to fossil fuels as the prediction of the fuel shortage in the near future, forced all operators involved in energy production to explore this new and clean source of power. Presented paper proposes fuzzy logic based Energy Management System (EMS) for Wind Turbine (WT), Photo Voltaic (PV) and Diesel Generator (DG) hybrid micro-grid configuration. Battery backup system is introduced for worst environmental conditions or high load demands. Dump load along with dump load controller is implemented for over voltage and over speed protection. Fuzzy logic based supervisory control system performs the power flow control between different scenarios such as battery charging, battery backup, dump load activation and DG backup in most intellectual way.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권1호
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• pp.82-86
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• 2008

The article presents ARTMAP and Fuzzy BK-Product approach underwater obstacle avoidance for the Autonomous underwater Vehicles (AUV). The AUV moves an unstructured area of underwater and could be met with obstacles in its way. The AUVs are equipped with complex sensorial systems like camera, aquatic sonar system, and transducers. A Neural integrated Fuzzy BK-Product controller, which integrates Fuzzy logic representation of the human thinking procedure with the learning capabilities of neural-networks (ARTMAP), is developed for obstacle avoidance in the case of unstructured areas. In this paper, ARTMAP-Fuzzy BK-Product controller architecture comprises of two distinct elements, are 1) Fuzzy Logic Membership Function and 2) Feed-Forward ART component. Feed-Forward ART component is used to understanding the unstructured underwater environment and Fuzzy BK-Product interpolates the Fuzzy rule set and after the defuzzyfication, the output is used to take the decision for safety direction to go for avoiding the obstacle collision with the AUV. An on-line reinforcement learning method is introduced which adapts the performance of the fuzzy units continuously to any changes in the environment and make decision for the optimal path from source to destination.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 제40회 하계학술대회
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• pp.780_781
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• 2009

This paper proposes efficiency optimization control of IPMSM drive using hybrid intelligent controller(HIC). The design of the speed controller based on fuzzy-neural network that is implemented using fuzzy control and neural network. The design of the current based on adaptive fuzzy control using model reference and the estimation of the speed based on neural network using ANN controller. In order to maximize the efficiency in such applications, this paper proposes the optimal control method of the armature current. The optimal current can be decided according to the operating speed and the load conditions. This paper proposes speed control of IPMSM using ALM-FNN, current control of model reference adaptive fuzzy control(MTC) and estimation of speed using ANN controller. The proposed control algorithm is applied to IPMSM drive system controlled HIC, the operating characteristics controlled by efficiency optimization control are examined in detail.

• Journal of Power Electronics
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• 제18권2호
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• pp.573-587
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• 2018

Recently evolved power electronics' based domestic/residential appliances have begun to behave as single phase non-linear loads. Performing as voltage/current harmonic sources, those loads when connected to a three phase distribution network contaminate the line current with harmonics in addition to creating a neutral wire current increase. In this paper, an enhanced performance three phase four leg shunt active power filter (SAPF) controller is presented as a solution for this problem. The presented control strategy incorporates a hybrid predictive fuzzy-logic based technique. The predictive part is responsible for the SAPF compensating current generation while the DC-link voltage control is performed by a fuzzy logic technique. Simulations at various loading conditions are carried out to validate the effectiveness of the proposed technique. In addition, an experimental test rig is implemented for practical validation of the of the enhanced performance of the proposed technique.

• 한국지진공학회논문집
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• 제9권2호통권42호
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• pp.7-15
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• 2005

본 연구에서는 하이브리드 면진장치가 설치된 단자유도 구조물의 동적거동을 예측할 수 있는 수치해석모델을 제안한다. 하이브리드 면진장치는 MR 감쇠기와 마찰진자시스템(FPS)으로 구성된다. MR감쇠기의 동적거동을 모형화하기 위하여 뉴로-퍼지 모델을 사용한다. 다양한 변위, 속도, 전압의 조합을 사용하여 MR 감쇠기의 성능실험을 수행한 후 얻어진 데이터를 이용하여 MR 감쇠기 뉴로-퍼지 모델을 ANFIS로 학습시킨다. FPS의 모형화는 본 연구에서 유도한 비선형 모델식에 근거하여 뉴로-퍼지 모형화방법을 사용하여 이루어진다. 본 연구에서는 MR 감쇠기로 전달되는 제어전압을 조절하기 위하여 퍼지논리제어기를 사용한다. 다양한 지진하중을 사용한 진동대 실험을 통하여 얻은 실험체의 동적응답과와 뉴로-퍼지 모형화방법을 사용한 수치해석의 결과를 비교한다. 뉴로-퍼지 모델을 사용하여 MR 감쇠기와 FPS를 모형화해서 수치해석을 수행한 결과 하이브리드 면진장치의 동적거동을 매우 정확하게 예측할 수 있었다.

• 컴퓨터교육학회논문지
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• 제7권1호
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• pp.67-77
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• 2004

본 논문에서는 시설내 작물재배 시스템의 완전자동화를 구현함에 동시에 자동 제어 방식 설계상에 존재하는 많은 문제들 때문에 실현하지 못했던 작물의 직접제어자동화를 구현하였다. 시설내 작물재배 자동제어 시스템은 제어대상에 따라서 세 가지로 구분될 수 있다. 시설외부로부터 기상 환경 등을 계측하여서 시설내 재배 제어에 응용하는 외부 환경 제어, 시설 내부 환경을 직접 계측하고 제어하는 내부 환경 제어, 작물의 성장에 직접 공급되는 배양액의 적절한 조성에 관련된 배양액 제어로 나눌 수 있다. 본 논문에서는 이 세 가지의 자동 제어시스템을 완전 실현하며, 배양액의 급액량을 제어함으로서 작물의 우량 성장을 자동적으로 조절할 수 있는 고난도 제어시스템을 설계하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 B
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• pp.1245-1247
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• 2004

This paper considers the design and implementation of novel technique of speed estimation and control for IPMSM using hybrid intelligent control. The hybrid combination of neural network and adaptive fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of IPMSM using adaptive neural network fuzzy(A-NNF) and estimation of speed using artificial neural network(ANN) controller. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new hybrid intelligent control.