• Title/Summary/Keyword: Defuzzifier

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Speed Control for Low Speed Diesel Engine by Hybrid F-NFC (Hybrid F-NFC에 의한 저속 디젤 기관의 속도 제어)

  • Choi, G.H.;Yang, J.H.
    • Journal of Power System Engineering
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    • v.10 no.4
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    • pp.159-164
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    • 2006
  • In recent, the marine engine of a large size is being realized a lower speed, longer stroke and a small number of cylinders for the energy saving. Consequently the variation of rotational torque became larger than former days because of the longer delay-time in fuel oil injection process and an increased output per cylinder. It was necessary that algorithms have enough robustness to suppress the variation of the delay-time and the parameter perturbation. This paper shows the structure of hybrid F-NFC against the delay-time and the perturbation of engine parameter as modeling uncertainties, and the design of the robust speed controller by hybrid F-NFC for the engine. And, The Parameter values of linear equation are determined by RC-GA for F-NFS. The hybrid F-NFC is combined the F-NFC and PID controller for filling up each.

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A Study on the Improvement of Control Characteristic and Performance of the Marine Mechanical-Hydraulic Governor using Fuzzy Control Scheme (퍼지 제어기법에 따른 선박용 유압조속기의 제어특성 및 성능개선에 관한 연구)

  • 강창남
    • Journal of Advanced Marine Engineering and Technology
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    • v.20 no.3
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    • pp.137-143
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    • 1996
  • The propulsion marine diesel engine has been widely applied with a mechanical-hydraulic governor to control the ship speed for long time. But it was recently very difficult for the mechanical-hydraullic governor to control the speed of engine under the condition of low speed and low load because of jiggling and hunting by rough fluctuation of rotating torque. To solve these problems of control systems, the performance improvement of mechanical-hydraulic governor is required. In this paper, in order to analyze the speed stability of control systems, the influence of parameters of the engine dead time, gain, damping ratio was discussed on the view of control engineering. The performance improvement of a conventional mechanical hydraulic governor is confirmed to be possible by fuzzy control scheme.

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Development of an Educational Java Applet for Understanding Fuzzy Logic Controller (퍼지 논리 제어기의 이해를 위한 교육용 자바 애플릿의 개발)

  • Kim Dong-Sik;Seo Sam-Jun;Kim Yoon-Bae
    • Journal of Engineering Education Research
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    • v.3 no.1
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    • pp.21-26
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    • 2000
  • The World Wide Web provides new opportunities for cyber education over the Internet. The web, when combined with other network tools, can be used to provide useful educational information to learners. Thus, the objective of this paper is to develop Java applet for understanding the concept of Fuzzy Logic Controller (FLC) on the Internet. The developed Java Applet is composed of four frames: fuzzifier, rulebase, inference engine and defuzzifier. Since data transmission can be achieved from one frame to other frames, users can easily observe and understand the process of FLC. The results of this paper can be used to improve the efficiency of lectures in the cyber university.

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A Study on Learning Evaluation Method by Using Fuzzy Theory (퍼지이론을 이용한 학습 평가 방법에 관한 연구)

  • 정창욱;남재현;김광백
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.7 no.5
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    • pp.853-862
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    • 2003
  • With the data base subject of first grade paper test of information handling technician, We proposed special method of evaluating learning ability directivity to judge that student can understand the contents of each chapter exactly or not, using assigned function and fuzzy deduction in this thesis. Using fuzzy logic, the proposed method of evaluating learning ability is dividing the presenting frequency of setting questions for examination about the subject of database into three rank and we can define this as the important. We applied the fuzzy assigned rate about the number of times of studying through the important of studying and the fuzzy assigned rate about formative evaluation to each of nine fuzzy deduction theories and than evaluated comprehension rate of learning. With the fuzzy grade about learning comprehension of each chapter and assigned rate about the score of generalized evaluation; We applied these two thing to the deduction rule of fuzzy and made it as defuzzifier and finally evaluated learning. We made that the result of eventual evaluating learning is very useful for learners to diagnosis learned contents by themselves and also it can be great material to judge that learners can get the goal of learning or not synthetically.

A Study on the Design of Classifier for Urine Analysis System (요분석 시스템의 분류기 설계에 관한 연구)

  • 전계록;김기련;예수영;김철한;정도운;조진호
    • Journal of Biomedical Engineering Research
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    • v.24 no.3
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    • pp.193-201
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    • 2003
  • In this paper, a classifier of urine analysis system was designed using preprocessing and fuzzy algorithm. Preprocessing were processed by normalizing data of strip using calibration curve composed of achromatic colors value and by calculating three stimulus. FUZZY classifier capable of analyzing a qualitative concentration of test items was composed of fuzzifier by gaussian shaped membership function, inference of MIN method, and defuzzifier of centroid method through verification by measuring standard solution and by classifying concentration classes. After tuning membership function according to relating standard solution with urinalysis sample, the possibility to adapt classifier designed for urine analysis system near a bed was verified as classifying measured urinalysis samples and observing classified result. Of all test items, experimental results showed a satisfactory agreement with test results of reference system.

An Optimal Design of Neuro-Fuzzy Logic Controller Using Lamarckian Co-adaptation of Learning and Evolution (학습과 진화의 Lamarckian 상호 적응에 의한 뉴로-퍼지 제어기의 최적 설계)

  • 김대진;이한별;강대성
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.35C no.12
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    • pp.85-98
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    • 1998
  • This paper proposes a new design method of neuro-FLC by the Lamarckian co-adaptation scheme that incorporates the backpropagation learning into the GA evolution in an attempt to find optimal design parameters (fuzzy rule base and membership functions) of application-specific FLC. The design parameters are determined by evolution and learning in a way that the evolution performs the global search and makes inter-FLC parameter adjustments in order to obtain both the optimal rule base having high covering value and small number of useful fuzzy rules and the optimal membership functions having small approximation error and good control performance while the learning performs the local search and makes intra-FLC parameter adjustments by interacting each FLC with its environment. The proposed co-adaptive design method produces better approximation ability because it includes the backpropagation learning in every generation of GA evolution, shows better control performance because the used COG defuzzifier computes the crisp value accurately, and requires small workspace because the optimization procedure of fuzzy rule base and membership functions is performed concurrently by an integrated fitness function on the same fuzzy partition. Simulation results show that the Lamarckian co-adapted FLC produces the most superior one among the differently generated FLCs in all aspects such as the number of fuzzy rules, the approximation ability, and the control performance.

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