• 제목/요약/키워드: a fuzzy technique

검색결과 935건 처리시간 0.029초

퍼지 PID 제어 기법을 이용한 비선형 유압시스템의 제어 (Nonlinear Hydraulic System Control Using Fuzzy PID Control Technique)

  • 박장호;김종화;류기석
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.69-69
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    • 2000
  • Control systems using a hydraulic cylinder as an actuator are modeled to a nonlinear system owing to varying of moments and nonlinearities of hydraulic itself. In this paper, we want to control nonlinear hydraulic systems by adopting the fuzzy PID control technique which include nonlinear time varying control parameters. To do this, we propose the design method of fuzzy Pm controller and in order to assure effectiveness of fuzzy PID controller, computer simulations were executed for the control system.

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SVC를 포함한 전력시스템의 안정도 향상을 위한 최적 퍼지-PI 제어기의 설계 (A Design of Optimal Fuzzy-PI Controller to Improve System Stability of Power System with Static VAR Compensator)

  • 김해재;주석민
    • 전기학회논문지P
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    • 제53권3호
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    • pp.122-128
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    • 2004
  • This paper presents a control approach for designing a fuzzy-PI controller for a synchronous generator excitation and SVC system. A combination of thyristor-controlled reactors and fixed capacitors(TCR-FC) type SVC is recognized as having the most flexible control and high speed response, which has been widely utilized in power systems, is considered and designed to improve the response of a synchronous generator, as well as controlling the system voltage. A Fuzzy-PI controller for SVC system was proposed in this paper. The PI gain parameters of the proposed Fuzzy-PI controller which is a special type of PI ones are self-tuned by fuzzy inference technique. It is natural that the fuzzy inference technique should be based on humans intuitions and empirical knowledge. Nonetheless, the conventional ones were not so. Therefore, In this paper, the fuzzy inference technique of PI gains using MMGM(Min Max Gravity Method) which is very similar to humans inference procedures, was presented and applied to the SVC system. The system dynamic responses are examined after applying all small disturbance condition.

퍼지논리를 이용한 Bin picking 방법 (A fuzzy logic based bin picking technique)

  • 김태원;서일홍;김기엽
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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    • pp.979-983
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    • 1991
  • A novel 2-dimensional matched filter of the parallel-jaw type using fuzzy logics is proposed for bin picking. Specifically, averaged pixel intensity of the windowed region for the filtering is considered to be fuzzy. Also membership function for darkness and brightness are designed by employing the intensite histogram of image. Then a rule is given to know how much a windowed region can be a possible holdsite. Furthermore eight rules are made to determine the part orientation, where Mamadi's resoning method is applied. To show the validities of our proposed technique. some experimental results are illustrated and compared with the results by conventional matched filter technique.

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Crack Identification Using Neuro-Fuzzy-Evolutionary Technique

  • Shim, Mun-Bo;Suh, Myung-Won
    • Journal of Mechanical Science and Technology
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    • 제16권4호
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    • pp.454-467
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    • 2002
  • It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. Toidentifythelocation and depth of a crack in a structure, a method is presented in this paper which uses neuro-fuzzy-evolutionary technique, that is, Adaptive-Network-based Fuzzy Inference System (ANFIS) solved via hybrid learning algorithm (the back-propagation gradient descent and the least-squares method) and Continuous Evolutionary Algorithms (CEAs) solving sir ale objective optimization problems with a continuous function and continuous search space efficiently are unified. With this ANFIS and CEAs, it is possible to formulate the inverse problem. ANFIS is used to obtain the input(the location and depth of a crack) - output(the structural Eigenfrequencies) relation of the structural system. CEAs are used to identify the crack location and depth by minimizing the difference from the measured frequencies. We have tried this new idea on beam structures and the results are promising.

부하주파수제어를 위한 퍼지-신경망 제어기에 관한 연구 (A Study on the Fuzzy-Neural Network Controller for Load Frequency Control)

  • 정형환;김상효;주석민;정문규
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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    • pp.137-144
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    • 1998
  • This paper proposed a optimal scale factors technique of a fuzzy-neural network for a load frequency control of two areas power system. The optimal scale factors control technique is optimize from an initial fuzzy logic control rule, and then is learned with an error back propagation learning algorithm of the fuzzy-neural network. In application two areas the load frequency control of the power system, it hopes to have response characteristic better than optimal control technique which is the conventional control technique and to show to minimize a frequency deviation and reaching and settling time of a tie line power flow deviation

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Neural Network Compensation Technique for Standard PD-Like Fuzzy Controlled Nonlinear Systems

  • Song, Deok-Hee;Lee, Geun-Hyeong;Jung, Seul
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제8권1호
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    • pp.68-74
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    • 2008
  • In this paper, a novel neural fuzzy control method is proposed to control nonlinear systems. A standard PD-like fuzzy controller is designed and used as a main controller for the system. Then a neural network controller is added to the reference trajectories to form a neural-fuzzy control structure and used to compensate for nonlinear effects. Two neural-fuzzy control schemes based on two well-known neural network control schemes, the feedback error learning scheme and the reference compensation technique scheme as well as the standard PD-like fuzzy control are studied. Those schemes are tested to control the angle and the position of the inverted pendulum and their performances are compared.

비선형(非線型) 시스템의 퍼지 모델링 기법과 안정도(安定度) 해석(解析)에 관한 연구 (Fuzzy Modeling Technique of Nonlinear Dynamical System and Its Stability Analysis)

  • 이준탁;소명옥;이상석;지석준;김태우
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1995년도 하계학술대회 논문집 B
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    • pp.801-803
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    • 1995
  • This paper presents the linearized fuzzy modeling technique of nonlinear dynamical system and the stability analysis of fuzzy control system. Firstly, the nonlinear system is partitionized by multiple linear fuzzy subcontrol systems based on fuzzy linguistic variables and fuzzy rules. Secondly, the disturbance adaptation controllers which guarrantee the global asymptotic stability of each fuzzy subsystem by an optimal feedback control law are designed and the stability analysis procedures of the total fuzzy control system using Lyapunov functions and eigenvalues are discussed in detail through a given illustrative example.

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Parametric Design on Bellows of Piping System Using Fuzzy Knowledge Processing

  • Lee Yang-Chang;Lee Joon-Seong;Choi Yoon-Jong
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제6권2호
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    • pp.144-149
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    • 2006
  • This paper describes a novel automated analysis system for bellows of piping system. An automatic finite element (FE) mesh generation technique, which is based on the fuzzy theory and computational geometry technique, is incorporated into the system, together with one of commercial FE analysis codes and one of commercial solid modelers. In this system, a geometric model, i.e. an analysis model, is first defined using a commercial solid modelers for 3-D shell structures. Node is generated if its distance from existing node points is similar to the node spacing function at the point. The node spacing function is well controlled by the fuzzy knowledge processing. The Delaunay triangulation technique is introduced as a basic tool for element generation. The triangular elements are converted to quadrilateral elements. Practical performances of the present system are demonstrated through several analysis for bellows of piping system.

Parametric Study on Bellows of Piping System Using Fuzzy Theory

  • Lee Yang-Chang;Lee Joon-Seong
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제6권1호
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    • pp.58-63
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    • 2006
  • This paper describes a novel automated analysis system for bellows of piping system. An automatic finite element (FE) mesh generation technique, which is based on the fuzzy theory and computational geometry technique, is incorporated into the system, together with one of commercial FE analysis codes and one of commercial solid modelers. In this system, a geometric model, i.e. an analysis model, is first defined using a commercial solid modelers for 3-D shell structures. Node is generated if its distance from existing node points is similar to the node spacing function at the point. The node spacing function is well controlled by the fuzzy knowledge processing. The Delaunay triangulation technique is introduced as a basic tool for element generation. The triangular elements are converted to quadrilateral elements. Practical performances of the present system are demonstrated through several analysis for bellows of piping system.

Fuzzy-technique-based expert elicitation on the occurrence probability of severe accident phenomena in nuclear power plants

  • Suh, Young A;Song, Kiwon;Cho, Jaehyun
    • Nuclear Engineering and Technology
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    • 제53권10호
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    • pp.3298-3313
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    • 2021
  • The objective of this study is to estimate the occurrence probabilities of severe accident phenomena based on a fuzzy elicitation technique. Normally, it is difficult to determine these probabilities due to the lack of information on severe accident progression and the highly uncertain values currently in use. In this case, fuzzy set theory (FST) can be best exploited. First, questions were devised for expert elicitation on technical issues of severe accident phenomena. To deal with ambiguities and the imprecision of previously developed (reference) probabilities, fuzzy aggregation methods based on FST were employed to derive the occurrence probabilities of severe accidents via four phases: 1) choosing experts, 2) quantifying weighting factors for the experts, 3) aggregating the experts' opinions, and 4) defuzzifying the fuzzy numbers. In this way, this study obtained expert elicitation results in the form of updated occurrence probabilities of severe accident phenomena in the OPR-1000 plant, after which the differences between the reference probabilities and the newly acquired probabilities using fuzzy aggregation were compared, with the advantages of the fuzzy technique over other approaches explained. Lastly, the impact of applying the updated severe accident probabilities on containment integrity was quantitatively investigated in a Level 2 PSA model.