• Title/Summary/Keyword: intelligent controller

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Optimun number of Fuzzy Labeling and Control Performance for Fuzzy Control.

  • Kankubo, Kouichi;Murakami, Shuta
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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    • pp.1191-1194
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    • 1993
  • We consider a fuzzy controller corresponding to PI controller. This controller is applied to a controlled object which is a first order lag system with dead time. An antecedent part is divided into 3, 5, and 7 parts ( membership function of triangle shape ), and a consequent part into 3, 5, and 7 parts ( membership function of singleton ). In each combination of an antecedent part and a consequent one. We compare control efficiency under the performance criteria such that the overshoot is kept 20% and the ITAE index is minimized.

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Architecture of a PDM VLSI Fuzzy Logic Controller with an Explicit Rule Base

  • Ungering, Ansgar P.;Goser, K.
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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    • pp.1386-1389
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    • 1993
  • We are describing the architecture of a fuzzy logic controller using pulse-width-modulation (PDM) technique and a pipeline structure. Features of this controller are: A new architecture for the inference unit, reduced chip area and less I/O-pins. Additionally we present two different rule-bases: one hardwired with reduced chip-area and the other programmable for prototyping. Also an architecture of a parallel minimum-gate is shown.

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COMPLETE AND INCOMPLETE FUZZY LOGIC CONTROLLERS

  • Teodorescu, H.N.;Brezulianu, A.
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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    • pp.1086-1089
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    • 1993
  • The paper deal with the differences between a fuzzy logic controller with a complete linguistic description and one with an incomplete linguistic description. The conditions to get a complete crisp controller by using a fuzzy logic controller with incomplete description are analyzed, and an application to the control of an analog PLL circuit is described, [1].

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Fuzzy logic을 利用한 交通 信號 control system (Traffic signal control system using fuzzy logic)

  • 文珠永;李尙培
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1996년도 추계학술대회 학술발표 논문집
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    • pp.180-183
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    • 1996
  • This work discusses simulation results for the fuzzy logic controller tested the project“Fuzzy Ramp Metering Algorithm Implementation.”The performance objectives were, in order of priority, to maximize total vehicle-miles, maximize mainline speeds, and minimize delay per vehicle while maintaining an acceptable ramp queue. In the fuzzy logic controller, the sensors from the on-ramps were helpful in maintaining reasonable ramp queue and mainline congestion because it considered these factors simultaneously. Each metered ramp had a parameter input file, which allowed the controller to be modified without recompiling the software. Consequently, maintenance costs should be minimal.

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Neural Network Based Guidance Control of a Mobile Robot

  • Jang, Pyoung-Soo;Jang, Eun-Soo;Jeon, Sang-Woon;Jung, Seul
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.1099-1104
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    • 2003
  • In this paper, the position control of a car-like mobile robot using neural network is proposed. The positional information of the mobile robot is given by a laser range finder located remotely through wireless communication. The heading angle is measured by a gyro sensor. Considering these two sensor information as references, the robot posture by localization is corrected by a cascaded controller. In order to improve the tracking performance, a neural network with a cascaded controller is used to compensate for any uncertainty in the robot. The remotely located neural network filter modifies the reference trajectories to minimize the positional errors by wireless communication. A car-like mobile robot is built as a test-bed and experimental studies of proposed several control algorithms are performed. It turns out that the best position control can be achieved by a cascaded controller with neural network.

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태양광 발전시스템에서 사용하는 마이크로인버터용 무선지능형제어기 설계 및 구현 (Design and Implementation of Wireless Intelligent Controller for Micro-Inverter in Solar Power Systems)

  • 한성택
    • 디지털산업정보학회논문지
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    • 제15권4호
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    • pp.9-17
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    • 2019
  • Sun power generation systems which use large capacity centralized inverters have loss of power generation due to cloud and building shadows, pollution, cell deterioration, etc. To minimize loss of power generation, decentralized solar power systems using multiple micro-inverters are being proposed as an alternative. A distributed solar power system consisting of a system-connected system uses power line communication to collect data from the micro-inverters. Power line communication has the advantage of using power lines without separate lines for data transmission, but in distributed solar power generation systems that use a large number of micro-inverters, the bit error rate is less reliable due to the phenomenon caused by limited transmission power, high load interference and noise, variable signal attenuation, and impedance characteristics. So we proposed wireless intelligent controller for micro-inverter that is used to build distributed solar power systems. and we design and implement that. Further, the proposed wireless intelligent controller for micro-inverter was used to establish a small-volume solar power plant to check its function and operation.

신경망을 이용한 퍼지 하이퍼큐브의 적응 학습방법 (An Adaptive Learning Method of Fuzzy Hypercubes using a Neural Network)

  • 제갈욱;최병걸;민석기;강훈
    • 한국지능시스템학회논문지
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    • 제6권4호
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    • pp.49-60
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    • 1996
  • 본 논문의 목적은 신경망을 이용한 퍼지 하이퍼큐브의 적응 학습 제어알고리듬의 개발이다. 퍼지 시스템 규칙베이스 후건부의 실시간적인 수정, 초기 퍼지 제어규칙의 일시적인 안정성을 가정하여 퍼지제어기와 신경망의 장점만을 살린 지능형 제어시스템의 설계방법을 제안하였다. 퍼지 제어기로는 실현 가능한 퍼지 하이퍼큐브의 구조를 선택하였고, 퍼셉트론 신경만의 학습법칙을 적용하여 출력오차로써 퍼지 제어기의 규칙을 실시간적으로 수정해 나가는 방법을 사용하였다. 결과적으로 적응 퍼지-뉴로 제어시스템을 Cart-Pole 제어에 응용함으로써 이러한 지능형 제어기의 유효성과 강인성을 보였다.

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비선형 시스템의 안정화를 위한 자기순환 뉴로-퍼지 제어기의 설계 (Design of Self Recurrent Neuro-Fuzzy Controller for Stabilization of Nonlinear System)

  • 탁한호;이인용;이성현
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2007년도 춘계학술대회 학술발표 논문집 제17권 제1호
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    • pp.390-393
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    • 2007
  • In this paper, applications of self recurrent neuro-fuzzy controller to stabilization of nonlinear system are considered. The architecture of self recurrent neuro-fuzzy controller is fix layer, and the hidden layer is comprised of self recurrent architecture. Also, generalized dynamic error-backpropagation algorithm is used for the learning of the self recurrent neuro-fuzzy controller. To demonstrate the efficiency of the self recurrent neuro-fuzzy control algorithm presented in this study, a self recurrent neuro-fuzzy controller was designed and then a comparative analysis was made with LQR controller through an simulation.

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PID Control with Fuzzy Compensation for Electric Power Generation Unit

  • Kim, Seung-Cheol;Cho, Yong-Sung;Park, Jae-Hyung;Lim, Young-Do;Lee, Ihn-Yong
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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    • pp.326-329
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    • 2003
  • Controller that is designed in this paper is form that apply PID controller about Fuzzy algorithm. Fuzzy Controller that using this paper is can speak that compensation style fuzzy controller as form to solidify action of PID controller for plant. This is not form that autotuning the each PID coefficient. We Apply and examined the response character to AGC(Automatic Generation Control) system using designed controller.

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Design of a PID type Fuzzy Controller

  • Jibril Jiya;Cheng Shao;Chai, Tian-You
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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    • pp.189-193
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    • 1998
  • A PID type fuzzy Controller is proposed based on a crisp type model in which the consequent parts of the fuzzy control rules are functional representation or real numbers. Using the conventional PID control theory, a new PID type fuzzy controller is developed, which retains the characteristics of the conventional PID controller. An advantage of this approach, is that it simplifies the complicated defuzzification algorithm which could be time consuming. Computer simulation results have shown that the proposed PID fuzzy controller has satisfactory tracking performance.

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