• 제목/요약/키워드: fuzzy logic controller(FLC)

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Absolute Stability of the Simple Fuzzy Logic Controller

  • Park, Byung-jae
    • 한국지능시스템학회논문지
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    • 제11권7호
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    • pp.574-578
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    • 2001
  • The stability analysis for the fuzzy logic controller (FLC) has widely been reported. Furthermore many research in the FLC has been introduced to decrease the number of parameters representing the antecedent part of the fuzzy control rule. In this paper we briefly explain a single-input fuzzy logic controller (SFLC) or simple-structured FLC which uses only a single input variable. And then we analyze that it is absolutely stale based on the sector bounded condition. We also show the feasibility of the proposed stability analysis through a numerical example of a mass-damper-spring system.

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퍼지 PI 제어기를 이용한 SRM 속도 응답 특성에 관한 연구 (A Study of SRM Speed Responce Characteristics Using Fuzzy PI Controller)

  • 박희성;최재동;오인석;황영성;성세진
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 1998년도 전력전자학술대회 논문집
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    • pp.200-203
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    • 1998
  • In this paper, it deals with Switched Reluctance Motor(SRM) which has fuzzy logic contoroller(FLC). The modeling and FLC of SRM are presented. The modeling and FLC of SRM are presented. The results of simulation show the speed responce characteristics of SRM with FLC. As a result, the SRM controller with FLC is verified by comparison between PI controller and fuzzy logic controller.

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Modularized Gain Scheduled Fuzzy Logic Control with Application to Nonlinear Magnetic Bearings

  • Hong, Sung-Kyung
    • 한국지능시스템학회논문지
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    • 제9권4호
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    • pp.384-388
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    • 1999
  • This paper describes an approach for synthesizing a modularized gain scheduled PD type fuzzy logic controller(FLC) of nonlinear magnetic bearing system where the gains of FLC are on-line adapted according to the operating point. Specifically the systematic procedure via root locus technique is carried out for the selection of the gains of FLC. Simulation results demonstrate that the proposed gain scheduled fuzzy logic controller yields not only maximization of stability boundary but also better control performance than a single operating point (without gain scheduling)fuzzy controller.

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The Study of Gain Scheduled PD-like Fuzzy Logic Control : Application to High Maneuverable Aircraft

  • Hong, Sung-Kyung;Lee, Jung-Young
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.141.1-141
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    • 2001
  • This paper describes an approach for synthesizing a modularized gain scheduled PD type fuzzy logic controller(FLC) for a high maneuverable aircraft system, where the gains of FLC are on-line adapted according to the flight condition. Specially, the systematic procedure via root locus technique is carried out for the sellection of the gains of FLC. Simulation results demonstrate that the proposed gain scheduled fuzzy logic controller yields better control performance than the normal (without gain scheduling) fuzzy controller.

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자전 안정화 플랫트폼 위치제어용 퍼지 논리 제어기 설계 (The design of a fuzzy logic controller for the pointing loop of the spin-stabilized platform)

  • 유인억;이상정
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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    • pp.112-116
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    • 1992
  • In this paper, a fuzzy logic controller(FLC) is designed for the pointing loop of the spin-stabilized platform. For the fuzzy inference, a fuzzy accelerator board using the Togai InfraLogic software and digital fuzzy processor(DFP110FC) is designed, and a validation of an algorithm for fuzzy logic control is also presented. The pointing loop of the spin-stabilized platform using FLC has better performance of step responses than a proportional controller in case of same loop hain through the software simulation and the experiment of implemented hardware.

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Comparing type-1, interval and general type-2 fuzzy approach for dealing with uncertainties in active control

  • Farzaneh Shahabian Moghaddam;Hashem Shariatmadar
    • Smart Structures and Systems
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    • 제31권2호
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    • pp.199-212
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    • 2023
  • Nowadays fuzzy logic in control applications is a well-recognized alternative, and this is thanks to its inherent advantages. Generalized type-2 fuzzy sets allow for a third dimension to capture higher order uncertainty and therefore offer a very powerful model for uncertainty handling in real world applications. With the recent advances that allowed the performance of general type-2 fuzzy logic controllers to increase, it is now expected to see the widespread of type-2 fuzzy logic controllers to many challenging applications in particular in problems of structural control, that is the case study in this paper. It should be highlighted that this is the first application of general type-2 fuzzy approach in civil structures. In the following, general type-2 fuzzy logic controller (GT2FLC) will be used for active control of a 9-story nonlinear benchmark building. The design of type-1 and interval type-2 fuzzy logic controllers is also considered for the purpose of comparison with the GT2FLC. The performance of the controller is validated through the computer simulation on MATLAB. It is demonstrated that extra design degrees of freedom achieved by GT2FLC, allow a greater potential to better model and handle the uncertainties involved in the nature of earthquakes and control systems. GT2FLC outperforms successfully a control system that uses T1 and IT2 FLCs.

퍼지 논리 제어기의 강인성에 대하여 (On the Robustness of a Fuzzy Logic Controller)

  • 이수영;정명진
    • 전자공학회논문지B
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    • 제32B권6호
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    • pp.828-839
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    • 1995
  • Although the fuzzy logic controller(FLC) has been adopted in many engineering applications, its performance is not guaranteed since there is no definite theoretic analysis. It may be the main factor that one hesitates to adopt the FLC in critical applications. In this paper, observing the similarity in the pattern of control input between the FLC and a conventional robust controller, i.e., the variable structure controller, we present theoretic analysis for robustness of a fuzzy control system based on the Lyapunov theory.

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신경회로망을 이용한 SVC용 적응 퍼지제어기의 설계 (Design of Adaptive Fuzzy Logic Controller for SVC using Neural Network)

  • 손종훈;황기현;김형수;박준호
    • 한국전기전자재료학회:학술대회논문집
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    • 한국전기전자재료학회 2002년도 춘계합동학술대회 논문집
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    • pp.121-126
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    • 2002
  • We proposed the design of SVC adaptive fuzzy logic controller(AFLC) using Tabu search and neural network. We tuned the gains of input-output variables of fuzzy logic controller(FLC) and weights of neural network using Tabu search. Neural network was used for adaptively tuning the output gain of FLC. The weights of neural network was learned from the back propagation algorithm in real-time. To evaluate the usefulness of AFLC, we applied the proposed method to single-machine infinite system. AFLC showed the better control performance than PD controller and GAFLC[8] for. three-phase fault in nominal load which had used when tuning AFLC. To show the robustness of AFLC, we applied the proposed method to disturbances such as three-phase fault in heavy and light load. AFLC showed the better robustness than PD controller and GAFLC[8].

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자전 안정화 플랫트폼 위치제어용 퍼지 논리제어기 설계 (A Fuzzy Logic Controller Design for the Pointing Loop of the Spin-Stabilized Platform)

  • 유인억;김병연;이상정
    • 전자공학회논문지B
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    • 제30B권4호
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    • pp.56-66
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    • 1993
  • In this paper, a fuzzy logic controll(FLC) is designed for the pointing loop of the spinstabilized platform. For the fuzzy inference, a fuzzy accelerator board using the Togai InfraLogic software and digital fuzzy processor(DFP110FC) is designed, and a validation of an algorithm for fuzzy logic control is also presented. Through the simulation and the experiment, it can be seen that the designed FLC shows better performance than a conventional controller using the same loop gain.

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T-S형 퍼지제어기의 후건부 멤버십함수 동조방법 (The Tuning Method on Consequence Membership Function of T-S Type FLC)

  • 최한수;이경웅
    • 제어로봇시스템학회논문지
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    • 제17권3호
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    • pp.264-268
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    • 2011
  • This paper presents a Takagi-Sugeno (T-S) type Fuzzy Logic Controller (FLC) with only 3 rules. The choice of parameters of FLC is very difficult job on design FLC. Therefore, the choice of appropriate linguistic variable is an important part of the design of fuzzy controller. However, since fuzzy controller is nonlinear, it is difficult to analyze mathematically the affection of the linguistic variable. So this choice is depend on the expert's experience and trial and error method. In this paper, we propose the method to choose the consequence linear equation's parameter of T-S type FLC. The parameters of consequence linear equations of FLC are tuned according to the system error that is the input of FLC. The full equation of T-S type FLC is presented and using this equation, the relation between output and parameters can represented. The parameters are tuned with gradient algorithm. The parameters are changed depending on output. The simulation results demonstrate the usefulness of this T-S type 3 rule fuzzy controller.