• 제목/요약/키워드: model reference adaptive system

검색결과 317건 처리시간 0.028초

FMRAS에 보상기를 이용한 유도전동기 속도제어 (Speed Control of Induction Motor Using Flux Compensation In Model Reference Adaptive System)

  • 서영수;이춘상
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 2002년도 전력전자학술대회 논문집
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    • pp.200-204
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    • 2002
  • When the vector control, which does not need a speed? signal from a mechanical speed sensor, it is possible to reduce the cost of the control equipment and to improve the control performance in many industrial application. This paper describes a rotor speed identification method of induction motor based on the theory of flux model reference adaptive system. The estimator execute the rotor speed identification so that the vector control of the induction motor may be achieved. The improved auxiliary variable of the two model are introduced to perform accurate rotor speed estimation. Simulation result show the validity of the proposed control method.

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퍼지 제어기를 이용한 영구자석 교류전동기의 센서리스 속도제어 (Sensorless Speed Control of Permanent Magnet AC Motor Using Fuzzy Logic Controller)

  • 최성대;고봉운;김낙교
    • 대한전기학회논문지:시스템및제어부문D
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    • 제53권6호
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    • pp.389-394
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    • 2004
  • This paper proposes a speed estimation method using FLC(Fuzzy Logic Controller) in order to realize the speed control of PMAM(Permanent Magnet AC Motor) with no speed sensor. This method uses FLC as a adaptive laws of MRAS(Model Reference Adaptive System) and estimates the rotor speed of PMAM with a difference between the reference model and the adjustable model. Speed control is performed by PI controller with the estimated speed. The experiment is executed to verify the propriety and the effectiveness of the proposed system.

일련의 상호연결된 연속시간 시스템의 비집중 적응 모델 추종 제어 방식 (A decentralized adaptive model following control scheme for a class of interconnected continuous system)

  • 김병연;유준
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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    • pp.1068-1072
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    • 1991
  • This paper presents a decentralized model reference adaptive control scheme for an interconnected continuous linear system composed of a number of single-input single-output subsystems in which outgoing interactions pass through the measurement channel and are subject to bounded external disturbance. The scheme can treat the unknown strength of interactions as well as the uncertainty of subsystems.

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Nonlinear Adaptive Control of Fermentation Process in Stirred Tank Bioreactor

  • Kim, Hak-Kyeong;Nguyen, Tan-Tien;Nam soo Jeong;Kim, Sang-Bong
    • Transactions on Control, Automation and Systems Engineering
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    • 제4권4호
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    • pp.277-282
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    • 2002
  • This paper proposes a nonlinear adaptive controller based on back-stepping method for tracking reference substrate concentration by manipulating dilution rate in a continuous baker's yeast cultivating process in stirred tank bioreactor. Control law is obtained from Lyapunov control function to ensure asymptotical stability of the system. The Haldane model for the specific growth rate depending on only substrate concentration is used in this paper. Due to the uncertainty of specific growth rate, it has been modified as a function including the unknown parameter with known bounded values. The substrate concentration in the bioreactor and feed line are measured. The deviation from the reference is observed when the external disturbance such as the change of the feed is introduced to the system. The effectiveness of the proposed controller is shown through simulation results in continuous system.

On the robust adaptive linearizing control for unknown and analytic relay nonlinearity

  • Lee, Jae-Kwan;Abe, Ken-ichi
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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    • pp.177-180
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    • 1996
  • The purpose of this paper is to design a robust adaptive control algorithm for a class of systems having continuous relay nonlinearity. This continuous relay nonlinearity can be defined as an analytic nonlinear function having unknown parameters and bounded unmodeling part. By this mathematical modeling, the whole system can be considered as a nonlinear system having unknown parameters and bounded perturbation. The control algorithm of this paper, RALC, can be constructed by robust adaptive law, feedback linearization, and indirect robust adaptive control. By this RALC, we can obtain that the output of given system can follow that of a stable reference linear model made by designer and the boundedness of all signals in closed-loop system can be maintained. Therefore, we can confirm a robust adaptive control for a class of systems having continuous relay nonlinearity.

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인공신경망을 이용한 지연시간이 일정치 않은 시스템의 제어 (Neural network-based control for uneven delay-time systems)

  • 이미경;이지홍
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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    • pp.446-449
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    • 1997
  • We propose a control law in discrete time domain of the bilateral feedback teleoperation system using neural network and the reference model type of adaptive control. Different from traditional teleoperation systems, the transmission time delay irregularly changes. The proposed control method controls master and slave systems through identification of master and slave models using neural networks.

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신경회로망을 이용한 AUV의 시스템 동정화 및 응용 (System Idenification of an Autonomous Underwater Vehicle and Its Application Using Neural Network)

  • 이판묵;이종식
    • 한국해양공학회지
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    • 제8권2호
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    • pp.131-140
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    • 1994
  • Dynamics of AUV has heavy nonlinearities and many unknown parameters due to its bluff shape and low cruising speed. Intelligent algorithms, therefore, are required to overcome these nonlinearities and unknown system dynamics. Several identification techniques have been suggested for the application of control of underwater vehicles during last decade. This paper applies the neural network to identification and motion control problem of AUVs. Nonlinear dynamic systems of an AUV are identified using feedforward neural network. Simulation results show that the learned neural network can generate the motion of AUV. This paper, also, suggest an adaptive control scheme up-dates the controller weights with reference model and feedforward neural network using error back propagation.

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External Force Control for Two Dimensional Contour Following ; Part 2. Analysis and Implementation of Analysis Control

  • Park, Young-Chil;Kim, Sungkwun
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
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    • pp.135-139
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    • 1992
  • Control of tool-environment interaction force to comply the robot system to an environment is of vital in many automated process. This paper presents the implementation of an adaptive force control with commercial robot system in two dimensional contour following task. A model reference adaptive control system, combined with the linear compensators, is implemented. That is, a use of adaptive control is to provide an auxiliary control system so that the contour following performance can be improved from that of using linear control system only. Hyperstability is used to derive the adaptive control law. Experimental verification of the proposed control system is obtained using PUMA 560 robot system. Data obtained experimentally shows that the use of additional adaptive control system improves the contour following performance about 30% in RMS contact force errors upon that of the system controlled by the linear compensators only.

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Chaos in nonlinear control systems

  • Lee, Joon-Suh;Chang, Kun-Soo
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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    • pp.758-762
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    • 1994
  • Complicated dynamical behavior can occur in model reference adaptive control systems when two external sinusoidal signals are introduced although the plant and reference model are stable linear first older systems. The phase portrait plot and the power spectral analysis indicate chaotic behavior. In the system treated, a positive Lyapuniov exponent and non-integer dimension clearly manifest chaotic nature of the system.

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