• Title/Summary/Keyword: Fuzzy Reasoning

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Design of fuzzy controller for activated sludge process in sewage water treatment system (하수처리 시스템에서의 활성오니공정 제어를 위한 퍼지제어기 설계)

  • 황희수;오성권;김현기;우광방
    • 제어로봇시스템학회:학술대회논문집
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    • 1990.10a
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    • pp.209-212
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    • 1990
  • The activated sludge process is a commonly used method for treating sewage and waste waters. The process is characterized by a lack of measurement instrumentations and control goals that are neither well defined nor well understood. In the present study the concept of fuzzy control is employed for such process in which a design method for fuzzy controller based on a multivariable fuzzy reasoning algorithms is investigated and then simulation results are presented.

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Design of ECG Pattern Classification System Using Fuzzy-Neural Network (퍼지-뉴럴 네트워크를 이용한 심전도 패턴 분류시스템 설계)

  • 김민수;이승로;서희돈
    • Proceedings of the IEEK Conference
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    • 2002.06e
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    • pp.273-276
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    • 2002
  • This paper has design of ECG pattern classification system using decision of fuzzy IF-THEN rules and neural network. each fuzzy IF-THEN rule in our classification system has antecedent lingustic values and a single consequent class. we use a fuzzy reasoning method based on a single winner rule in the classification phase. this paper in, the MIT/BIH arrhythmia database for the source of input signal is used in order to evaluate the performance of the proposed system. From the simulation results, we can effectively pattern classification by application of learned from neural networks.

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Architecture for Complex Inference Method

  • Lim, M.H.;Leong, J.Y.
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.989-992
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    • 1993
  • In this paper, we describe hardware architecture of fuzzy processors for reasoning involving fuzzy control“Heuristics”. This we believe will lead to fuzzy systems that are closer to the way humans process domain knowledge for decision making. One noticeable beneficial effect based on our notion of fuzzy heuristics is the significantly reduced number of rules required.

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FUZZY PETRI NETS AND THEIR APPLICATIONS TO FUZZY REASONING SYSTEMS CONTROL

  • Matsumoto, Tadashi;Sakaguchi, Atsushi;Tsuji, Kohkichi
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.1330-1333
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    • 1993
  • In this paper, first, the fuzzy Petri net inference mechanism with learning function is proposed by using the extended fuzzy Petri nets. Secondly, a control system with this new inference engine is proposed. This system can do automatically and easily the knowledge acquisition from the operator's empirical data and can also be controller adaptively under the big parameter change.

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Psychological Jump in Vague Knowledge

  • Nakatsuyama, Mikio
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.343-346
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    • 1998
  • This paper deals with the decision in vague knowledge, One method is a classic theory. That is to say, constraints and goals in the vague knowledge. Another method is the fuzzy catastrophe. If there exist two fuzzy variables, there may be a discontinuity which plays an important role in decision.

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Characteristics of Fuzzy Inference Systems by Means of Partition of Input Spaces in Nonlinear Process (비선형 공정에서의 입력 공간 분할에 의한 퍼지 추론 시스템의 특성 분석)

  • Park, Keon-Jun;Lee, Dong-Yoon
    • The Journal of the Korea Contents Association
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    • v.11 no.3
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    • pp.48-55
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    • 2011
  • In this paper, we analyze the input-output characteristics of fuzzy inference systems according to the division of entire input spaces and the fuzzy reasoning methods to identify the fuzzy model for nonlinear process. And fuzzy model is expressed by identifying the structure and parameters of the system by means of input variables, fuzzy partition of input spaces, and consequence polynomial functions. In the premise part of the rules Min-Max method using the minimum and maximum values of input data set and C-Means clustering algorithm forming input data into the hard clusters are used for identification of fuzzy model and membership function is used as a series of triangular membership function. In the consequence part of the rules fuzzy reasoning is conducted by two types of inferences. The identification of the consequence parameters, namely polynomial coefficients, of the rules are carried out by the standard least square method. And lastly, we use gas furnace process which is widely used in nonlinear process and we evaluate the performance for this nonlinear process.

A Design of Fuzzy Control System for Moving Object Tracking (이동물체 추적을 위한 퍼지제어 시스템 설계)

  • 강석범;김재기;양태규
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.5 no.4
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    • pp.738-745
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    • 2001
  • In this paper, when the moving object move to the three-dimentional space, the tracking system track the moving object using the fuzzy reasoning. The joint angle el of the manipulator rotate from $0^{\circ}\; to\; 360^{\circ}$ , and the joint angle $\theta_2$rotate from$0^{\circ}\; to\; 360^{\circ}$. The fuzzy singleton is used for fuzzification and the control rule is twenty five and the fuzzy inference method is simplified Mamdani's reasoning and the defuzzification is the SCOG(Simplified Center Of Gravity) of the fuzzy controller To measure of the performance of the designed system, the fuzzy controller is compared with the CTM(Computed Torque Method) controller at the same condition. when the disturbance torque is ON, the both of CTM and fuzzy controller tracked object without error, However, the disturbance torque changed 0.4N, the CTM controller is 10 times greater than fuzzy controller at the sum of absolute error difference. The designed system is showed it's robustness against with disturbance.

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Fuzzy Control of DC Servo System and Implemented Logic Circuits of Fuzzy Inference Engine Using Decomposition of $\alpha$-level Fuzzy Set (직류 서보계의 퍼지제어와 $\alpha$-레벨 퍼지집합 분해에 의한 퍼지추론 연산회로 구현)

  • 홍정표;홍순일;이요섭
    • Journal of Advanced Marine Engineering and Technology
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    • v.28 no.5
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    • pp.793-800
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    • 2004
  • The purpose of this study is to develope a servo system with faster and more accurate response. This paper describes a method of approximate reasoning for fuzzy control of servo system based on the decomposition of $\alpha$-level fuzzy sets. We propose that fuzzy logic algorithm is a body from fuzzy inference to defuzzificaion cases where the output variable u directly is generated PWM The effectiveness for robust and faster response of the fuzzy control scheme are verified for a variable parameter by comparison with a PID control and fuzzy control A position control of DC servo system with a fuzzy logic controller is demonstrated successfully.

Enhanced Auto-focus algorithm detecting target object with multi-window and fuzzy reasoning for the mobile phone (목적물 인식 및 자동 선택이 가능한 모바일 폰 용 자동초점 알고리즘)

  • Lee, Sang-Yong;Oh, Seung-Hoon;Kim, Soo-Won
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.44 no.3 s.357
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    • pp.12-19
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    • 2007
  • This paper proposes the enhanced auto-focus algorithm detecting several objects and selecting the target object. Proposed algorithm first detects some objects distributed in the image using focus measure operator and multi-window and then selects the target object through fuzzy reasoning with three fuzzy membership functions. Implementation can be simple because it only needs image sensor instead of infrared or ultrasonic equipment. Experimental result shows that the proposed algorithm can improve the quality of image by focusing to the target object.