• Title/Summary/Keyword: Fuzzy Reasoning Method

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Estimation of Optimal Control Parameters and Design of Hybrid Fuzzy Controller by Means of Genetic Algorithms (유전자 알고리즘에 의한 HFC의 최적 제어파라미터 추정 및 설계)

  • Lee, Dae-Keun;Oh, Sung-Kwun;Jang, Sung-Whan;Kim, Yong-Soo
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.49 no.11
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    • pp.599-609
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    • 2000
  • The new design methodology of a hybrid fuzzy controller by means of the genetic algorithms is presented. First, a hybrid fuzzy controller(HFC) related to the optimal estimation of control parameters is proposed. The control input for the system in the HFC combined PID controller with fuzzy controller is a convex combination of the FLC's output and PID's output by a fuzzy variable, namely, membership function of weighting coefficient. Second, an auto-tuning algorithms utilizing the simplified reasoning method and genetic algorithms is presented to automatically improve the performance of hybrid fuzzy controller. Especially, in order to auto-tune scaling factors and PID parameters of HFC using GA, three kinds of estimation modes such as basic, contraction, and expansion mode are effectively utilized. The proposed HFC is evaluated and discussed to show applicability and superiority with the and of three representative processes.

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Implemented Logic Circuits of Fuzzy Inference Engine for DC Servo Control Using decomposition of $\alpha$-level fuzzy set ($\alpha$-레벨 퍼지집합 분해에 의한 직류 서보제어용 퍼지추론 연산회로 구현)

  • 이요섭;손의식;홍순일
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.8 no.5
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    • pp.1050-1057
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    • 2004
  • The purpose of study is development of a fuzzy controller which independent of a computer and its software for fuzzy control of servo system. This paper describes a method of approximate reasoning for fuzzy control of servo system, based on decomposition of $\alpha$-level fuzzy sets, It is propose that fuzzy logic algorithm is a body from fuzzy inference to defuzzificaion in cases where the output variable u directly is generated PWM. The effectiveness of quantified $\alpha$-levels on input/output characteristics of fuzzy controller and output response of DC servo system is investigated. It is concluded that $\alpha$-cut 4 levels give a sufficient result for fuzzy control performance of DC servo system. The experimental results shows that the proposed hardware method is effective for practical applications of DC servo system.

A Study on Fault Diagnosis of Power System Using Fuzzy Petri Nets (퍼지 페트리네트를 이용한 전력계통 고장진단에 관한 연구)

  • Roh, Myong-Gyun;Hong, Sang-Eun
    • Proceedings of the KIEE Conference
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    • 2000.07a
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    • pp.122-124
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    • 2000
  • As the complexity of power systems increases, especially in the case of multiple faults or incorrect operation of protective devices, fault diagnosis requires new and systematic methods to the reasoning process, which improves both its accuracy and its efficiency. Therefore this paper proposes a method of the modeling of protection systems and fault diagnosis in power systems using Fuzzy Petri Nets (FPN). The proposed method can reduce processing time and increase accuracy when compared with the traditional methods. And also this method can cover online processing of real-time data from SCADA (Supervisory Control and Data Acquisition).

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An Interval Valued Bidirectional Approximate Reasoning Method Based on Similarity Measure

  • Chun, Myung-Geun
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.579-584
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    • 1998
  • In this work, we present a method to deal with the interval valued decision making systems. First, we propose a new type of equality measure based on the Ordered Weighted Averaging (OWA) operator. The proposed equality measure has a structure to render the extreme values of the measure by choosing a suitable weighting vector of the OWA operator. From this property, we derive a bidirectional fuzzy inference network which can be applied for the decisionmaking systems requiring the inverval valued decisions.

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A Fuzzy-based Network Intrusion Detection System Through sessionization (세션화 방식을 통한 퍼지기반 네트워크 침입탐지시스템)

  • Park, Ju-Gi;Choi, Eun-Bok
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.1 s.45
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    • pp.127-135
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    • 2007
  • As the Internet is used widely, criminal offense that use computer is increasing, and an information security technology to remove this crime is becoming competitive power of the country. In this paper, we suggest network-based intrusion detection system that use fuzzy expert system. This system can decide quick intrusion decision from attack pattern applying fuzzy rule through the packet classification method that is done similarity of protocol and fixed time interval. Proposed system uses fuzzy logic to detect attack from network traffic, and gets analysis result that is automated through fuzzy reasoning. In present network environment that must handle mass traffic, this system can reduce time and expense of security

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Decision Method of Fuzzy Membership Function based on FCM for CBR (CBR을 위한 FCM 기반 퍼지 소속 함수 결정 방법)

  • 연지현;김은주;이일병
    • Proceedings of the Korean Information Science Society Conference
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    • 1999.10b
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    • pp.15-17
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    • 1999
  • 사례 기반 추론(Case-Based Reasoning)은 새로운 문제를 해결하기 위해 유사한 기존 문제를 추출하여 그 해결과정을 사용한다. 그러므로, 기존의 문제와의 유사성을 얼마만큼 잘 판별하는가가 매우 중요한 관건이다. 연구된 유사성 판단 방법으로는 퍼지 소속 함수(Fuzzy membership function)를 이용하여 사례마다 각 클래스에 대한 소속 함수 값을 주는 방법이 있다. 이 방법은 퍼지 소속 함수를 어떻게 주는가에 따라 성능이 달라진다. 본 논문에서는 적당한 퍼지 소속 함수를 주기 위하여 Fuzzy C-Means를 사용하는 방법을 제안하였다. 이 방법은 각 클래스에 대한 소속 함수 값을 결정하는데 있어서 좀 더 전체적인 데이터 분포 정보를 이용할 수 있다.

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SENSITIVITY ANALYSIS IN FUZZY RELIABILITY ANALYSISA

  • Onisawa, Takehisa
    • 제어로봇시스템학회:학술대회논문집
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    • 1988.10b
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    • pp.764-769
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    • 1988
  • In this paper the failure possibility and the error possibility are used to represent reliability of a technical component and that of a human operator, respectively. The failure possibility and the error possibility are fuzzy sets on the interval [0,1]. In a man-machine system, reliability of the technical component and that of the human operator are usually affected by many factors, e.g., the environment in which a machine is operated, psychological stress of the human operator, etc. The possibility is derived from not only the failure or the error rate but also estimates of these factors. The fuzzy reasoning plays an important role in the derivation. The reliability analysis is performed by the use of the possibility obtained by the present method. Moreover this paper discusses the sensitivity analysis which evaluates what extent the change of the estimation of each factor has an influence on reliability of a man-machine system. The important factors to be ameliorated are shown through the sensitivity analysis.

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Fuzzy Logic Control for a Redundant Manipulator -Resolved Motion Rate Control

  • Kim, Sung-Woo;Lee, Ju-Jang
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10b
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    • pp.479-484
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    • 1992
  • The resolved motion rate control (RMRC) is converting to Joint space trajectory from given Cartesian space trajectory. The RMRC requires the inverse of Jacobian matrix. Since the Jacobian matrix of the redundant robot is generally not square, the pseudo-inverse must be introduced. However the pseudo-inverse is not easy to be implemented on a digital computer in real time as well as mathematically complex. In this paper, a simple fuzzy resolved motion rate control (FRMRC) that can replace the RMRC using pseudo-inverse of Jacobian is proposed. The proposed FRMRC with appropriate fuzzy rules, membership functions and reasoning method can solve the mapping problem between the spaces without complexity. The mapped Joint space trajectory is sufficiently accurate so that it can be directly used to control redundant manipulators. Simulation results verify the efficiency of the proposed idea.

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The Optimal Design of HFC by means of GAs (유전자 알고리즘을 이용한 HFC의 최적설계)

  • 이대근;오성권;장성환
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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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.

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A Study on the Introduction of Fuzzy Theory to the Adjustment of Time Variant parameter

  • Lee, Jong-Kyu;Lee, Chang-Hae
    • Korean Journal of Hydrosciences
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    • v.8
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    • pp.69-83
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    • 1997
  • The Parameters of the storage function model (SFM) are taken as constants, while they have different values during every rainfall period and the duration of the runoff. Therefore, the results of the SFM generally show remarkably large errors. In this study, the modified storage function model (MSFM), in which the time variant parameters are introduced, is proposed to improve the SFM which is a conceptual rainfall-runoff model. The fuzzy reasoning method is applied as a real-time control one of the time variant parameters of the proposed model. The applicability of the MSFM was examined in the Bochung river, at a tributary of the Geum River, Korea. The pattern of the predicted runoff hydrograph and the peak discharge by the MSFM with fuzzy control are very similar to the measured values, compared with the results produced by the SFM.

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