• 제목/요약/키워드: Fuzzy control technique

검색결과 522건 처리시간 0.03초

퍼지 교통 제어 전문가 시스템 (Fuzzy Traffic Control Expert System)

  • 진정애;김용기
    • 지능정보연구
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    • 제1권2호
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    • pp.17-32
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    • 1995
  • 본 논문에서는 추론엔진 (inference engine)내에 퍼지정보 검색부(Fuzzy Information Retrieval part)를 갖는 교통신도 제어 전문가 시스템을 제안한다. 제안하는시스템은 다양하고 복잡한 도로 상화을 고려하여 그에 따른 적절한 주기를 각 도로별로 할당함으로써 원활한 교통 흐름을 제어한다. 추론엔진내의 퍼지정보 검색부는 퍼지 삼각 논리곱을 이용하여 도로의 상황을 분석한 후 각 도로에 맞는 가장 적절한 신호주기를 생성한다.

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퍼지 양자화에 의한 초저전송율 동영상 부호기의 율 제어 (Rate Control of Very Low Bit-rate Video Coder Using Fuzzy Quantization)

  • 양근호
    • 융합신호처리학회 학술대회논문집
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    • 한국신호처리시스템학회 2000년도 하계종합학술대회논문집
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    • pp.189-192
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    • 2000
  • A fuzzy controller for the evaluation of the quantization parameters in the H.263 coder has been introduced. We adopted a Mamdani fuzzy controller with centroid defuzzification. The inputs are variance, entropy, current motion vector and previous motion vector. This results is obtained a effective rate control technique using fuzzy Quantization.

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타부탐색기법에 의한 홍수시 저수지 운영에 관한 연구 (Reservoir Operation by Tabu Search Method during Flood)

  • 정한우;최승안;김형수;심명필
    • 한국수자원학회논문집
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    • 제38권9호
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    • pp.761-770
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    • 2005
  • 본 연구에서는 퍼지논리제어의 적용을 통해 홍수시 저수지의 방류량을 결정하는데 있어, 예측유입량 자료에 내재된 불확실성을 고려할 수 있는 저수지 운영 모형을 구성하고자 하였다. 제어규칙은 전문가들의 의견을 반영해 규칙기반을 설정하는데 이러한 일반적인 방법의 단점을 보완하고자 전역 최적화 기법인 타부탐색을 이용하여 제어규칙을 자동적으로 설정해 퍼지-타부탐색 모형을 구성하였다. 모형의 적용 결과, 첨두방류량이 감소되어 홍수조절율이 개선되었으며, 총 방류량도 감소하는 것으로 나타나 결과적으로 치수효과가 증대될 수 있음을 확인하였다. 또한 홍수 후에 가용할 수 있는 수자원의 양이 증가되어 실제운영방법보다 이수적 차원에서 향상된 결과를 나타내었다.

Development of Maneuvering Simulator for PERESTROIKA Catamaran using Fuzzy Inference Technique

  • Lee, Joon-Tark;Ji, Seok--Jun;Choi, Woo--Jin
    • Journal of Advanced Marine Engineering and Technology
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    • 제28권2호
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    • pp.192-199
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    • 2004
  • Navigation simulators have been used in many marine schools and manne training centers since the early 1960's. But these simulators were very expens~ve and were almost limited only in one engine system. In this paper, a catamaran with twin engine system. controlled by two remote control levers and its economic simulator based on a personal computer shall be introduced. One of the main features of catamaran is to control variously its progressing direction. In the static state, a catamaran can move into all the directions and in the dynamic state, ship can change immediately the heading and speed. Although a good navigator can skillfully operate one engine system, it is difficult to control smoothly the catamaran of twin engine system without any threat for the safety of passengers. Thus. in order to bring up the expert navigators. the development of a simulator which makes the training effective is necessary, Therefore, in this paper, a Fuzzy Inference Technique based Maneuvering Simulator for catamaran with twin engine system was developed. In general. in order to develop a catamaran simulator for effective training, first of all. its mathematical model must be acquired. According to the acquired system modeling. the dynamics of simulator is determined, But the proposed technique can omit a complex and tedious mathematical modeling procedures by using the fuzzy inference, which dependent upon only experiences of an expert and can design an efficient training program for unskillful navigators. This developed simulator was consisted of two fuzzy inference routines and two remote control levers, and was focused on effective training of navigators for the safe maneuvering to avoid a collision in a harbor.

The Speed Control and Estimation of IPMSM using Adaptive FNN and ANN

  • Lee, Hong-Gyun;Lee, Jung-Chul;Nam, Su-Myeong;Choi, Jung-Sik;Ko, Jae-Sub;Chung, Dong-Hwa
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.1478-1481
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    • 2005
  • As the model of most practical system cannot be obtained, the practice of typical control method is limited. Accordingly, numerous artificial intelligence control methods have been used widely. Fuzzy control and neural network control have been an important point in the developing process of the field. This paper is proposed adaptive fuzzy-neural network based on the vector controlled interior permanent magnet synchronous motor drive system. The fuzzy-neural network is first utilized for the speed control. A model reference adaptive scheme is then proposed in which the adaptation mechanism is executed using fuzzy-neural network. Also, this paper is proposed estimation of speed of interior permanent magnet synchronous motor using artificial neural network controller. The back-propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back-propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the analysis results to verify the effectiveness of the new method.

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비선형 시스템을 위한 퍼지모델 기반 일반예측제어 (Fuzzy Model Based Generalized Predictive Control for Nonlinear System)

  • 이철희;서선학
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2000년도 추계학술대회 논문집 학회본부 D
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    • pp.697-699
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    • 2000
  • In this paper, an extension of model predictive controller for nonlinear process using Takagi-Sugeno(TS) fuzzy model is proposed Since the consequent parts of TS fuzzy model comprise linear equations of input and output variables. it is locally linear, and the Generalized Predictive Control(GPC) technique which has been developed to control Linear Time Invariant(LTI) plants, can be extended as a parallel distributed controller. Also fuzzy soft constraints are introduced to handle both equality and inequality constraints in a unified form. So the traditional constrained GPC can be transferred to a standard fuzzy optimization problem. The proposed method conciliates the advantages of the fuzzy modeling with the advantages of the constrained predictive control, and the degree of freedom is increased in specifying the desired process behavior.

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Sampled-Data Observer-Based Decentralized Fuzzy Control for Nonlinear Large-Scale Systems

  • Koo, Geun Bum;Park, Jin Bae;Joo, Young Hoon
    • Journal of Electrical Engineering and Technology
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    • 제11권3호
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    • pp.724-732
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    • 2016
  • In this paper, a sampled-data observer-based decentralized fuzzy control technique is proposed for a class of nonlinear large-scale systems, which can be represented to a Takagi-Sugeno fuzzy system. The premise variable is assumed to be measurable for the design of the observer-based fuzzy controller, and the closed-loop system is obtained. Based on an exact discretized model of the closed-loop system, the stability condition is derived for the closed-loop system. Also, the stability condition is converted into the linear matrix inequality (LMI) format. Finally, an example is provided to verify the effectiveness of the proposed techniques.

온도제어를 위한 단상용 Fuzzy TPR 개발에 관한 연구 (Development of Single-phase Fuzzy TPR for temperature control)

  • 홍성훈;강문성
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1996년도 하계학술대회 논문집 B
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    • pp.1053-1055
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    • 1996
  • This paper proposes a Fuzzy TPR having the control function to a TPR used for the conversion of electricity in industrial field. The Fuzzy TPR based on the Fuzzy Logic Control technique is composed of the parts to calculate the low-level value and the high-level value. These values are calculated by error and change in error which are refer to the look-up table. To show the usefulness of the proposed Fuzzy TPR, it is applied to industrial temperature control system. In the results of experiment, we see that the system is able to fast reach steady-state, and for our approach to be robust to external disturbance than the method using the conventional TPR.

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슬라이딩 모드를 이용한 로봇 매니풀레이터의 간접적응 자기조정 퍼지제어 (Indirect Adaptive Self-Regulating Fuzzy Control of Robot Manipulators Using Sliding Mode)

  • 박원성;양해원;정기철;김도우
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2007년도 제38회 하계학술대회
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    • pp.1718-1719
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    • 2007
  • In this paper, a fuzzy sliding mode control that combines with a adaptive self-regulating technique is proposed for manipulators with uncertainties. Especially the system uncertainties is approximated using fuzzy rule adaptation technique. The proposed controller is composed of the equivalent control that includes the approximation of the system uncertainties and the hitting control that is used to constrain the states of the system to maintain on the sliding surfaces and used to guarantee the system robustness. Simulation results are presented to show the effectiveness of the proposed controller

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Intelligent Fuzzy Controller for Nonlinear Systems

  • Joo, Young-Hoon;Lee, Sang-Jun;Oh, Jae-Heung
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제2권2호
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    • pp.139-145
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    • 2002
  • In this paper, we proposed an intelligent digital redesign method for a class of fuzzy-model-based controllers, effective fur stabilization of continuous-time nonlinear systems. The TS fuzzy model is used to expend the results of the digital redesign technique to nonlinear systems. The proposed method utilized the recently developed LMI technique to obtain a digitally redesigned fuzzy-model-based controller. The intelligent digital redesign problem is converted to equivalent problem, and the LMI method is used to find the digitally redesigned fuzzy-model-based controller. The stabilization conditions of TS fuzzy model are derived for stabilization in the sense of Laypunov stability. In order to demonstrates the effectiveness and feasibility of the proposed controller design methodology, we applied this method to the single link flexible-joint robot arm.