• Title/Summary/Keyword: model-reference adaptive control

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DC Servo Motor Control using Model Reference Adaptive Fuzzy Controller (모델 기준 적응 퍼지 제어기를 이용한 DC 전동기 제어)

  • Son, Jae-Hyun;Kim, Je-Hong
    • Journal of the Korean Institute of Telematics and Electronics T
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    • v.36T no.4
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    • pp.60-70
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    • 1999
  • In this paper, model reference adaptive fuzzy controller (MRAFC) was proposed in order to overcome the difficulty of extracting rules and defects of the adaptation performance in the FLC. MRAFC comprised inner feedback loop consisting of the FLC and plant, and outer loop consisting of an adaptation mechanism which was designed for tuning a control rule of the FLC. A reference-model was used for design criteria of a fuzzy controller which characterizes and quantizes the control performance required in the overall control system. Tuning control rules of FLC is performed by the adaptation mechanism. The performance of proposed algorithm was verified through experiment for the DC servo motor.

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A Study on Sensorless Control of Transverse Flux Rotating Motor Based on MRAS with Parameter Estimation

  • Kim, Ji-Won;Kim, Kwang-Woon;Kisck, Dragos Ovidiu;Kang, Do-Hyun;Chang, Jung-Hwan;Kim, Jang-Mok
    • Journal of Power Electronics
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    • v.11 no.6
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    • pp.864-869
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    • 2011
  • This paper presents a sensorless control and parameter estimation strategies for a Transverse Flux Rotating Motor (TFRM). The proposed sensorless control method is based on a Model Reference Adaptive System (MRAS) to estimate the stator flux. Parameter estimation theory is also applied into the sensorless control method to estimate motor parameters, such as inductances. The effectiveness of the proposed methods is verified by some simulations and experiments.

A study on the Discrete-Time Adaptive Control for Robot Maninpulator (로보트 매니퓰레이터의 이산 시간 적응제어에 관한 연구)

  • Sung, Kwan-Young;Lee, Un-Cheol;Yoo, Jae-Guen;Nam, Moon-Hyun
    • Proceedings of the KIEE Conference
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    • 1991.07a
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    • pp.777-780
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    • 1991
  • The practical implementation of model reference adaptive systems(MRAS) using digital computer requires the derivation of discrete-time adaptation laws. This is specially important in the case of direct driver robot and light weight manipulator where inertia changes ang gravity effects are significant. We develope a discrete-time model reference adaptive control scheme for trajectory tracking of robot manipulator. Instead of the conventional Lyapunov approach hyperstabillty theory is more appealing than the Lyapunov approach. It is better suited to discrete time systems and offers more flexibility in design by providing additional free design parameters.

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Trajectory Tracking Control of Field Robot using Adaptive Control and System Identification (적응제어 및 시스템 규명을 이용한 Field Robot의 궤적 추종 제어)

  • 서우석;김승수;양순용;이병룡;안경관
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2002.04a
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    • pp.469-474
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    • 2002
  • The Field Robot means the machinery applied for outdoor tasks in construction, agriculture and undersea etc. In this study, to field-robotize a hydraulic excavator that is mostly used in construction working, we have developed an automatic excavation system and adaptive control system. A model- reference adaptive controller has been designed on the model that is obtained through off-line System Identification. It is illustrated by computer simulations that the proposed control system gives good performances in the trajectory tracking control and adaptation to parameter variation.

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Robustness Analysis of MRAC System in the Presence of Unmodelled Dynamics (비모형화 특성을 갖는 기준모델 적응제어 시스템의 견고성 해석)

  • 김성덕;양해원
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.36 no.10
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    • pp.748-754
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    • 1987
  • A robustness analysis for model reference adaptive control(MRAC) system with plant uncertainty is discussed in this paper. The adaptive control system is designed under assumptions that the controlled plant is represented by a lst order nominal model and that the system is drived by a constant reference signal. When using general gradient method(GGM), it is shown that unmodelled dynamics in plant model can cause the instability of the overall control loop during the adaptation process. However, as the algorithm of least square method(LSM) is introduced, the global stability of the system can be hold. And it is also given that the boundedness of adjustable parameters may be verified using the concept of an equilibrium point analysis.

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Design of Intelligent Speed Estimator for Speed Sensorless Control of Induction Motor (유도전동기의 속도 센서리스 제어를 위한 지능형 속도 추정기의 설계)

  • Park, Jin-Su;Choi, Sung-Dae;Kim, Sang-Hoon;Ko, Bong-Woon;Nam, Moon-Hyon;Kim, Lark-Kyo
    • Proceedings of the KIEE Conference
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    • 2004.07d
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    • pp.2304-2306
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    • 2004
  • This paper proposes an Intelligent Speed Estimator in order to realize the speed-sensorless vector control of an induction motor. Intelligent Speed Estimator used Model Reference Adaptive System which has Fuzzy-Neural adaptive mechanism as Speed Estimation method. The Intelligent Speed Estimator estimates the speed of an induction motor with a rotor flux of a reference model and adjustable model in MRAS. The Intelligent Speed Estimator reduces the error of the rotor flux between the voltage flux model and the current flux model using the error and the change of error as input of the Estimator. The computer simulation is executed to verify the propriety and the effectiveness of the proposed speed estimator.

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

  • Kim, Byung-Yeun;Lyou, Joon
    • 제어로봇시스템학회:학술대회논문집
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    • 1991.10a
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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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On the robust adaptive linearizing control for unknown and analytic relay nonlinearity

  • Lee, Jae-Kwan;Abe, Ken-ichi
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10a
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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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Speed and Position Sensorless Control of SPMSM with Adaptive Observer (적응 관측기에 의한 SPMSM의 속도 및 위치 센서리스 제어)

  • Lee, Hong-Gyun;Lee, Jung-Chul;Cha, Young-Doo;Chung, Dong-Hwa
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.54 no.1
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    • pp.1-7
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    • 2005
  • This paper is proposed the speed and position sensorless control of surface permanent magnet synchronous motor(SPMSM) with adaptive fuzzy and observer. A adaptive fuzzy controller is applied for speed control of SPMSM drive. A adaptive state observer is used for the mechanical state estimation of the motor. The observer was developed based on nonlinear model of SPMSM, that employs a d - q rotating reference frame attached to the rotor. A adaptive observer is implemented to compute the speed and position feedback signal. The validity of the proposed sensorless scheme is confirmed by various response characteristics.

Robust Adaptive Sliding Mode Control of Robot Manipulators Using a Model Reference Approach

  • Lee, Tae-Hwan;Bae, Jun-Kyung
    • Journal of Electrical Engineering and information Science
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    • v.3 no.1
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    • pp.36-44
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    • 1998
  • In this paper, a robust adaptive sliding mode control algorithm for accurate trajectory tracking of robot manipulators is proposed, with unknown parameters being estimated on-line. The controller is designed based on a Lyapunov method, which consists of adaptive feed-forward compensation part and a discontinuous control part. It is shown that, in the presence of the uncertainty and the disturbances arising from the actuator or some other causes, the tracking errors is bound to converge to zero asymptotically. An illustrative example is given to demonstrate the results of the propose method.

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