• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.299-302
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• 2003

In fuzzy control systems having large volumes of fuzzy data. one of the important problems is the improvement of execution speed in the fuzzy inference and defuzzification stages. In this paper, to improve the speedup of fuzzy controllers, we use an integer line mapping algorithm to convert [0, 1] real values in the fuzzy membership functions to integer pixels. U sing this, we propose a real-time high-speed fuzzy control system and implement a fast fuzzy processor and control system using FPGAs.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.102-109
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• 2014

In this paper, an algorithm to design fuzzy PID controllers is proposed. The proposed controllers are composed of fuzzy rules of which consequences are linear PID controllers and are designed with help of TSK fuzzy controllers. TSK fuzzy controllers are designed from TSK fuzzy model using pole assignment and have outstanding ability making the output response of nonlinear systems similar to the desired one. However, because of its structure complexity the TSK fuzzy controller is difficult to be used in industry. The proposed controllers have PID controller structure which can be easily realized, and are designed by using the data obtained from control simulations with TSK fuzzy controllers. To verify the proposed algorithm, two example simulations are performed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.11a
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• pp.888-892
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• 2002

In this paper, parallel type fuzzy controller is designed by using a hybrid connected type fuzzy-PID controller and a model reference fuzzy controller. The first controller that consists a fuzzy-PI and a fuzzy-PD making a hybrid type fuzzy-PID controller plays a role as firstly reaching stable responses and secondly overcoming disturbance in plants. The second controller, model reference fuzzy controller, plays a role as reaching faster responses than other controllers. We have confirmed that we get rapid and stable responses and the controller overcomes disturbance in a short time when there happens disturbance by using parallel type fuzzy controller applying to DC motor in this paper.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.788-791
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• 2006

Fuzzy theory has been used effectively to control the nonlinear system since Mamdani successively adopted fuzzy theory in the steam-engine control problem in 1973. Truckbacker-upper control problem originally proposed by Nguyen and Widrow become a standard highly nonlinear control problem. In this paper, we designed adaptive fuzzy membership functions for speed control as well as steering control. In other words, an adaptive fuzzy control system for truck backer-upper problem useful for practical adaptation is proposed. Experimental results by simulations prove the effectiveness of the proposed system.

• The Journal of Korean Association of Computer Education
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• v.7 no.1
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• pp.67-77
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• 2004

In this paper, a new approach to the automation of the cultivation in a green house is suggested and a practical automatic control cultivation system is implemented. To automatically control and optimize the very nonlinear and time-varying growth of farm products, a hybrid strategy(FECA, Fuzzy Expertized Control Algorithm) is proposed which serially combines a fuzzy expert system with the fuzzy logic control. The fuzzy expert system(FMES, Fuzzy Model-based Expert System is intended to overcome the non-linearity of the growth of farm products. The part of fuzzy controller(FLC, Fuzzy Logic Controller) is incorporated to solve the time-variance of the growth of farm products. Finally, the efficiency and the effectiveness of the implemented agricultural automation system is presented through the cultivation results.

• Journal of Advanced Navigation Technology
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• v.20 no.3
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• pp.226-231
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• 2016

Researching and developing mobile robot are quite important. Autonomous driving of mobile robot is important in various working environment. For its autonomous driving, mobile robot detects obstacles and avoids them. Purpose of this thesis is to analyze kinematics model of the mobile robot and show the efficiency of type-2 fuzzy self-tuning PID controller used for controling steering angle. Type-2 fuzzy is more flexible in verbal expression than type-1 fuzzy because it has multiple values unlike previous one. To compare these two controllers, this paper conduct a simulation by using MATLAB Simulink. The result shows the capability of type-2 fuzzy self-tuning PID is effective.

• Journal of the Korean Society of Hazard Mitigation
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• v.4 no.1 s.12
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• pp.33-40
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• 2004

The objective of this study is to develop single dam operation models for flood control using Fuzzy control technique, which can improve flood controllability. We set control rules by water level and inflow, and developed three models Fuzzy I, II, III according to rule to decide outflow. Fuzzy I model consists of six rules considering only flood control and Fuzzy II model considers the effect of water use by increasing water level at the end of flood control period as well as flood control during the same period. Finally, Fuzzy m is an adaptive model designed to perform multipurpose dam operation for both flood control and water use simultaneously based on a control rules.

• The Transactions of the Korean Institute of Power Electronics
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• v.16 no.5
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• pp.484-493
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• 2011

The MPPT algorithm using neuro-fuzzy controller is proposed to improve the performance of fuzzy controller in this paper. The width of membership function and fuzzy rule have an effect on the performance of fuzzy controller. The neuro-fuzzy controller has the response characteristic which is superior to the existing fuzzy controller, because of using the optimal width of the fuzzy membership function through the neural learning. The superior control characteristic of a proposed algorithm is confirmed through simulation and experiment results.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.609-611
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• 1999

산업현장의 제어기들은 센서들로부터 수집된 다양한 형태의 신호들을 처리한다. 이 신호들은 고정된 값을 가지지 않고 물리적으로 변화하는 특성을 가진다. 이와 같이 변화하는 값을 처리하는 방법으로 다양한 형태의 연구가 진행되고 있고, 그 한 분야로 퍼지(Fuzzy)이론을 바탕으로 한 퍼지 제어 시스템에 대한 연구가 활발하게 진행되고 있다. Fuzzy PLC 시스템은 현재 초기단계 형태로 개발되어 사용되고 있으며 그 응용 방법도 조금씩 보급되고 있는 실정이다. 본 논문은 변화하는 값들에 대해 간결하고 적절한 제어를 수행 할 수 있는 기 개발된 Fuzzy PLC 시스템을 이용한 플랜트 제어에 대한 연구이다. 크레인(Crane) 제어용으로 사용한 Fuzzy PLC 시스템은 Moeller사의 FT4-400-MM2 PLC 모듈이다. 본 시스템을 이용하여 대상 플랜트인 크레인을 제어하는 퍼지 함수 로직을 개발하고, 입 출력 제어 프로그램 기법에 대하여 연구한다. 또한 퍼지 제어 시스템을 이용한 퍼지 제어 기법을 개발하는 과정에 대하여 소개한다. 결론적으로 Fuzzy PLC System 개발 및 응용 모델로서 제안하고자 한다.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.3
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• pp.173-183
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• 1998

In this paper, an auto-tuning method for fuzzy controller's membership functions based on the neural network is presented. The neural network emulator offers the path which reforms the fuzzy controller's membership functions and fuzzy rule, and the reformed fuzzy controller uses for speed control of induction motor. Thus, in the case of motor parameter variation, the proposed method is superior to a conventional method in the respect of operation time and system performance. 32bit micro-processor DSP(TMS320C31) is used to achieve the high speed calculation of the space voltage vector PWM and to build the self-learning fuzzy control algorithm. Through computer simulation and experimental results, it is confirmed that the proposed method can provide more improved control performance than that PI controller and conventional fuzzy controller.