• Title, Summary, Keyword: Fuzzy Logic

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Gain Tuning of a Fuzzy Logic Controller Superior to PD Controllers in Motor Position Control

  • Kim, Young-Real
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.14 no.3
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    • pp.188-199
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    • 2014
  • Although the fuzzy logic controller is superior to the proportional integral derivative (PID) controller in motor control, the gain tuning of the fuzzy logic controller is more complicated than that of the PID controller. Using mathematical analysis of the proportional derivative (PD) and fuzzy logic controller, this study proposed a design method of a fuzzy logic controller that has the same characteristics as the PD controller in the beginning. Then a design method of a fuzzy logic controller was proposed that has superior performance to the PD controller. This fuzzy logic controller was designed by changing the envelope of the input of the of the fuzzy logic controller to nonlinear, because the fuzzy logic controller has more degree of freedom to select the control gain than the PD controller. By designing the fuzzy logic controller using the proposed method, it simplified the design of fuzzy logic controller, and it simplified the comparison of these two controllers.

Design and Analysis of Interval Type-2 Fuzzy Logic System (Interval Type-2 Fuzzy논리 집합의 설계 및 분석)

  • Kim, Dae-Bok;Oh, Sung-Kwun
    • Proceedings of the KIEE Conference
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    • pp.155-156
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    • 2008
  • In this paper, an interval type-2 fuzzy logic system is designed and compared with a type-1 fuzzy logic system. To compare performance of a type-1 fuzzy logic system with the type-2 fuzzy logic system, we apply type-1 fuzzy logic system and type-2 system to modeling the noised data. Membership function of interval type-2 fuzzy logic system is designed consequents of rules including uncertainty. For general type-2 fuzzy logic system computational complexity is severe. On the other hand, theoretic and arithmetic computations for interval type-2 fuzzy logic systems are very simple.

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Lotfi A. Zadeh

  • Lee, Seung-On;Kim, Jin-Tae
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • pp.311-312
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    • 2008
  • Fuzzy logic is introduced by Zadeh in 1965. It has been continuously developed by many mathematicians and knowledge engineers all over the world. A lot of papers concerning with the history of mathematics and the mathematical education related with fuzzy logic, but there is no paper concerning with Zadeh. In this article, we investigate his life and papers about fuzzy logic. We also compare two-valued logic, three-valued logic, fuzzy logic, intuisionistic logic and intuitionistic fuzzy sets. Finally we discuss about the expression of intuitionistic fuzzy sets.

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An Exponential Representation Form for Fuzzy Logic

  • Shen, Zuliang;Ding, Liya
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • pp.1281-1284
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    • 1993
  • By the exponential representation form (EF) for fuzzy logic, any fuzzy value a (in fuzzy valued logic or fuzzy linguistic valued logic) can be represented as Bc, where B is called the truth base and C the confidence exponent. This paper will propose the basic concepts of this form and discuss its interesting properties. By using a different truth base, the exponential form can be used to represent the positive and the negative logic in fuzzy valued logic as well as in fuzzy linguistic valued logic. Some Simple application examples of EF for approximate reasoning are also illustrated in this paper.

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Control of the Washing Machineos Motor by the GA-Fuzzy Algorithm (GA-Fuzzy Algorithm에 의한 세탁기 모터의 제어)

  • 이재봉;김지현;박윤서;선희복
    • Journal of the Korean Institute of Intelligent Systems
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    • v.5 no.2
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    • pp.3-12
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    • 1995
  • A controller utilizing fuzzy logic is developed to control the speed of a motor in a washing machine by choosing an appropriate phase. Due to the hardship imposed on obtaining a result from a relation established for inputs, present speed and present rate of speed, and ouput, a phase, of the system that can be tested against an experimental result, it is impossible to apply a genetic algorithm to fine-tune the fuzzy logic controller. To avoid this difficulty, a proper assumption that the parameters of an if-part of a primary fuzzy logic controller have a functional relationship with an error between computed values and experimental ones in made. Setting up of a fuzzy relationship between the parameters and the errors is then achieved through experimentally obtained data. Genetic Algorithm is then applied to this secondary fuzzy logic controller to verify the fuzzy logic. In the verification process, the primary fuzzy logic controller is used in obtaining experimental results. In this way the kind of difficulty in obtaining enough experimental values used to verify the fuzzy logic with genetic algorithm is gotten around. Selection of the parameters that would produce the least error when using the secondary fuzzy logic controller is done with applying genetic algorithm to the then-part of the controller. In doing so the optimal values for the parameters of the if-part of the primary fuzzy logic controller are assumed to be contained. The experimental result presented in the paper validates the assumption.

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Lotfi A. Zadeh, the founder of fuzzy logic (퍼지 논리의 시조 Zadeh)

  • Lee, Seung-On;Kim, Jin-Tae
    • Journal for History of Mathematics
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    • v.21 no.1
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    • pp.29-44
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    • 2008
  • Fuzzy logic is introduced by Zadeh in 1965. It has been continuously developed by many mathematicians and knowledge engineers all over the world. A lot of papers concerning with the history of mathematics and the mathematical education related with fuzzy logic, but there is no paper concerning with Zadeh. In this article, we investigate his life and papers about fuzzy logic. We also compare two-valued logic, three-valued logic, fuzzy logic, intuisionistic logic and intuitionistic fuzzy sets. Finally we discuss about the expression of intuitionistic fuzzy sets.

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Truncation Effects of the Fuzzy Logic Controllers

  • Moon, Byung-Soo;Moon, Je-Sun;Lee, Jongmin
    • Journal of the Korean Institute of Intelligent Systems
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    • v.4 no.2
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    • pp.35-40
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    • 1994
  • Fuzzy logic controllers are often found to behave better than PI controllers. One of the major reasons for this is that the fuzzy logic inferences used can produce nonlinear type controllers. For some applicatioins, howeveer, linear fuzzy logic controllers also perofrm better than PI controllers. In this paper, we examine linear fuzzy logic controllers to show that the truncation effects of the fuzzy logic controllers make them perform much better than the PI controllers. In terms of a performance index we used, the truncation effects reduced the index value by up to 80% for examples we studied.

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A Development of a Real-time, Traffic Adaptive Control Scheme Through VIDs. (영상검지기를 이용한 실시간 교통신호 감응제어)

  • 김성호
    • Journal of Korean Society of Transportation
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    • v.14 no.2
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    • pp.89-118
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    • 1996
  • The development and implementation of a real-time, traffic adaptive control scheme based on fuzzy logic through Video Image Detector systems (VIDs) is presented. Through VIDs based image processing, fuzzy logic can be used for a real-time traffic adaptive signal control scheme. Fuzzy control logic allows linguistic and inexact traffic data to be manipulated as a useful tool in designing signal timing plans. The fuzzy logic has the ability to comprehend linguistic instructions and to generate control strategy based on a priori verbal communication. The implementation of fuzzy logic controller for a traffic network is introduced. Comparisons are made between implementations of the fuzzy logic controller and the actuated controller in an isolated intersection. The results obtained from the application of the fuzzy logic controller are also compared with those corresponding to a pretimed controller for the coordinated intersections. Simulation results from the comparisons indicate the performance of the system is between under the fuzzy logic controller. Integration of the aforementioned schemes into and ATMS framework will lead to real-time adjustment of the traffic control signals, resulting in significant reduction in traffic congestion.

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Uninorm logic: toward a fuzzy-relevance logic(2)

  • Yang, Eun-Suk
    • Korean Journal of Logic
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    • v.11 no.1
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    • pp.131-156
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    • 2008
  • This paper first investigates several uninorm logics (introduced by Metcalfe and Montagna in [8]) as fuzzy-relevance logics. We first show that the uninorm logic UL and its extensions IUL, UML, and IUML are fuzzy-relevant; fuzzy in Cintula's sense, i.e., the logic L is complete with respect to linearly ordered L-matrices; and relevant in the weak sense that ${\Phi}{\rightarrow}{\Psi}$ is a theorem only if either (i) $\Phi$ and $\Psi$ share a sentential variable or constant, or (ii) both $\sim\Phi$ and $\Psi$ are theorems. We next expand these systems to those with $\triangle$.

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Current Mirror-Based Approach to the Integration of CMOS Fuzzy Logic Functions

  • Patyra, Marek J.;Lemaitre, Laurent;Mlynek, Daniel
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • pp.785-788
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    • 1993
  • This paper presents the prototype framework for automated integration of CMOS current-mode fuzzy logic circuits using an intelligent module approach. The library of modules representing the standard fuzzy logic operators was built. These modules were finally used to synthesized sophisticated fuzzy logic units. Fuzzy unit designs were made based upon the results of a newel methodology of the current mirror-based fuzzy logic function synthesis. This methodology is actually incorporated into the presented framework. As an example, the membership function unit was synthesized, simulated, and the final layout was generated using the presented framework. Finally, the fuzzy logic controller unit (FLC) was generated using the proposed framework. Simulation as well as measurement results show unquestionable advantages of the proposed fuzzy logic function integration system over the classical design methodology with respect to the area, relative error and performance.

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