• 제목/요약/키워드: Fuzzy Rules

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퍼지추론 방법에 의한 퍼지동정과 하수처리공정시스템 응용 (Fuzzy Identification by means of Fuzzy Inference Method and Its Application to Wate Water Treatment System)

  • 오성권;주영훈;남위석;우광방
    • 전자공학회논문지B
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    • 제31B권6호
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    • pp.43-52
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    • 1994
  • A design method of rule-based fuzzy modeling is presented for the model identification of complex and nonlinear systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of ``IF....,THEN...', using the theories of optimization theory , linguistic fuzzy implication rules and fuzzy c-means clustering. Three kinds of method for fuzzy modeling presented in this paper include simplified inference (type I), linear inference (type 2), and modified linear inference (type 3). In order to identify premise structure and parameter of fuzzy implication rules, fuzzy c- means clustering and modified complex method are used respectively and the least sequare method is utilized for the identification of optimum consequence parameters. Time series data for gas furance and those for sewage treatment process are used to evaluate the performance of the proposed rule-based fuzzy modeling. Comparison shows that the proposed method can produce the fuzzy model with higher accuracy than previous other studies.

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퍼지생성규칙을 위한 퍼지페트리네트표현에서 후진추론 (Backward Reasoning in Fuzzy Petri - net Representation for Fuzzy Production Rules)

  • 조상엽
    • 한국정보처리학회논문지
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    • 제5권4호
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    • pp.951-958
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    • 1998
  • 본 논문에서는 퍼지생성규칙을 표현한 퍼지페트리네트에서 사용할 수 있는 후진추론 알고리즘을 제안한다. 퍼지페트리 네트워크표현은 근사추론 시스템을 모형화하거나 퍼지추론엔진을 구현하는데 사용할 수 있다. 본 논문이 제안한 알고리즘은 단순히 min과 max 게산만을 하는 기존의 알고리즘과는 달리 퍼지생성규칙의 전제부와 결론부에 퍼지개념의 유무에 따라 적절한 믿음값평가함수을 사용하여 보다 더 인간적인 추론을 한다. 후진추론 알고리즘은 목표노드에서 시작노드까지의 후진추론 통로를 구한 후에 믿음값평가함수를 이용하여 목표노드의 믿음값을 구한다.

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Co-Evolution of Fuzzy Rules and Membership Functions

  • Jun, Hyo-Byung;Joung, Chi-Sun;Sim, Kwee-Bo
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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    • pp.601-606
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    • 1998
  • In this paper, we propose a new design method of an optimal fuzzy logic controller using co-evolutionary concept. In general, it is very difficult to find optimal fuzzy rules by experience when the input and/or output variables are going to increase. Futhermore proper fuzzy partitioning is not deterministic ad there is no unique solution. So we propose a co-evolutionary method finding optimal fuzzy rules and proper fuzzy membership functions at the same time. Predator-Prey co-evolution and symbiotic co-evolution algorithms, typical approaching methods to co-evolution, are reviewed, and dynamic fitness landscape associated with co-evolution is explained. Our algorithm is that after constructing two population groups made up of rule base and membership function, by co-evolving these two populations, we find optimal fuzzy logic controller. By applying the propose method to a path planning problem of autonomous mobile robots when moving objects applying the proposed method to a pa h planning problem of autonomous mobile robots when moving objects exist, we show the validity of the proposed method.

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RVEGA 최적 퍼지 제어기를 이용한 비선형 시스템의 안정화 제어에 관한 연구 (Stabilization Control of the Nonlinear System using A RVEGA ~. based Optimal Fuzzy Controller)

  • 이준탁;정동일
    • Journal of Advanced Marine Engineering and Technology
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    • 제21권4호
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    • pp.393-403
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    • 1997
  • In this paper, we proposed an optimal identification method of identifying the membership func¬tions and the fuzzy rules for the stabilization controller of the nonlinear system by RVEGA( Real Variable Elitist Genetic Algo rithm l. Although fuzzy logic controllers have been successfully applied to industrial plants, most of them have been relied heavily on expert's empirical knowl¬edge. So it is very difficult to determine the linguistic state space partitions and parameters of the membership functions and to extract the control rules. Most of conventional approaches have the drastic defects of trapping to a local minima. However, the proposed RVEGA which is similiar to the processes of natural evolution can optimize simulta¬neously the fuzzy rules and the parameters of membership functions. The validity of the RVEGA - based fuzzy controller was proved through applications to the stabi¬lization problems of an inverted pendulum system with highly nonlinear dynamics. The proposed RVEGA - based fuzzy controller has a swing -. up control mode(swing - up controller) and a stabi¬lization one(stabilization controller), moves a pendulum in an initial stable equilibrium point and a cart in an arbitrary position, to an unstable equilibrium point and a center of the rail. The stabi¬lization controller is composed of a hierarchical fuzzy inference structure; that is, the lower level inference for the virtual equilibrium point and the higher level one for position control of the cart according to the firstly inferred virtual equilibrium point. The experimental apparatus was imple¬mented by a DT -- 2801 board with AID, D/A converters and a PC - 586 microprocessor.

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새로운 계층 구조를 이용한 퍼지 시스템 모델링 (Fuzzy System Modeling Using New Hierarchical Structure)

  • 김도완;주영훈;박진배
    • 한국지능시스템학회논문지
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    • 제12권5호
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    • pp.405-410
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    • 2002
  • 본 논문은 수학적으로 모델링하기 어려운 비선형 시스템을 위한 새로운 계층적 규칙 기반 퍼지 시스템 모델링 기법을 제안한다. 제안된 기법은 퍼지 규칙 기반 구조를 상위 규칙 기반과 하위 규칙 기반으로 나누어 계층화시키는 새로운 모델링 방법이다. 본 논문에서 제안한 계층적 퍼지 규칙을 적용함으로써 퍼지 규칙을 효율적이고 논리적으로 이용할 수 있음은 물론, 퍼지 규칙의 효율적, 논리적 사용은 퍼지 시스템의 정확성을 높일 수 있고 구조를 명료화시킬 수 있음을 보인다. 유전알고리즘은 제안된 퍼지 규칙의 파라미터 최적화 과정에 이용된다. 마지막으로, 복잡한 비선형 시스템에 대한 퍼지 모델링 결과를 통해서 제안된 기법의 타당성 및 효용성을 검증하고 타 기법의 결과와 비교한다.

가중치 조정 알고리즘을 이용한 직류 전동기의 적응 퍼지제어 (Adaptive Fuzzy Control for a DC Mmotor Using Weight Tuning Algorithm)

  • 손재현;지성현;전병태;임종광;남문현
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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    • pp.360-363
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    • 1993
  • Fuzzy Logic Control immitating human decision making process is a novel control strategy based on expert's experience and knowledge and many process designers are developing its applications. But it is difficult to obtain a set of rules from human operator. And there is a limitation on adjusting to environmental changes. In this paper, we proposed adaptive fuzzy algorithm to overcome these difficulties using weights added to the rules. To verify the validity of this control strategy, we have implemented this algorithm for a DC servo motor with PD-type fuzzy controller.

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간략화된 트롤 시스템의 퍼지제어 (Fuzzy Logic Control for a Simplified Trawl System)

  • 이춘우
    • 수산해양기술연구
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    • 제30권3호
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    • pp.189-198
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    • 1994
  • This paper describes the model of a simplified trawl system and a control method by using fuzzy algorithm in controlling the depth of trawl gear. Fuzzy logic control rules are sets of linguistic expression that are used by an experienced performer in real operation. For real time processing of the control rules, the look-up tables are used. Computer simulation results indicate that the proposed fuzzy controller shows fast response with minimum steady-state error and robustness properties to the simulated disturbance.

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인간의 감성을 고려한 칼라 Fuzzy 영상처리 (Human Sensory of Perception Oriented Color Fuzzy Image Processing)

  • 박영현;김승우;우동민;박민용
    • 전자공학회논문지B
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    • 제29B권3호
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    • pp.47-54
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    • 1992
  • This paper presents an image processing method which emphasizes a certain perception feeling on a color image. A series of fuzzy image processing schemes are proposed, which transform an color image represented in the LCH coordinate system to the image with a certain perception feeling based on the rules and fuzzy inference. To obtain the rules, results of the sensory perception tests are applied to the quantification theory. The proposed schemes can be effectively utilized in the color copy system, since printed outputs possibly look better than originals.

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Two-Degree-of Freedom Fuzzy Neural Network Control System And Its Application To Vehicle Control

  • Sekine, Satoshi;Yamaguchi, Toru;Tamagawa, Kouichirou;Endo, Tunekazu
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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    • pp.1121-1124
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    • 1993
  • We propose two-degree-of-freedom fuzzy neural network control systems. It has a hierarchical structure of two sets of control knowledge, thus it is easy to extract and refine fuzzy rules before and after the operation has started, and the number of fuzzy rules is reduced. In addition an example application of automatic vehicle operation is reported and its usefulness is shown simulation.

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GA-Based Construction of Fuzzy Classifiers Using Information Granules

  • Kim Do-Wan;Lee Ho-Jae;Park Jin-Bae;Joo Young-Hoon
    • International Journal of Control, Automation, and Systems
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    • 제4권2호
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    • pp.187-196
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    • 2006
  • A new GA-based methodology using information granules is suggested for the construction of fuzzy classifiers. The proposed scheme consists of three steps: selection of information granules, construction of the associated fuzzy sets, and tuning of the fuzzy rules. First, the genetic algorithm (GA) is applied to the development of the adequate information granules. The fuzzy sets are then constructed from the analysis of the developed information granules. An interpretable fuzzy classifier is designed by using the constructed fuzzy sets. Finally, the GA is utilized for tuning of the fuzzy rules, which can enhance the classification performance on the misclassified data (e.g., data with the strange pattern or on the boundaries of the classes). To show the effectiveness of the proposed method, an example, the classification of the Iris data, is provided.