• Title/Summary/Keyword: Model reference controller

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A New Control Model for a 3 PWM Converter with Digital Current Controller considering Delay and SVPWM Effects

  • Min, Dong-Ki;Ahn, Sung-Chan;Hyun, Dong-Seok
    • Proceedings of the KIPE Conference
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    • 1998.10a
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    • pp.346-351
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    • 1998
  • In design of a digital current controller for a 3-phase (3 ) voltage-source (VS) PWM converter, its conventional model, i.e., stationary or synchronous reference frame model, is used in obtaining its discretized version. It introduces, however, inherent errors since the following practical problems are not taken into consideration: the characteristics of the space vector-based pulse-width modulation (SVPWM) and the time delays in the process of sampling and computation. In this paper, the new hybrid reference frame model of the 3 VS PWM converter is proposed considering these problems. In addition, the direct digital current controller based on this model is designed without any prediction or extrapolation algorithm to compensate the time delay. So the control algorithm is made very simple. It represents no steady-state error in input current control and has the optimized transient responses. The validity of the proposed algorithm is proved by the computer simulation and experimental results.

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Design of Adaptive Fuzzy Control for High Performance of PMSM Drive (PMSM 드라이브의 고성능 제어를 위한 적응 퍼지제어기의 설계)

  • 정동화;이홍균;이정철
    • The Transactions of the Korean Institute of Electrical Engineers B
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    • v.53 no.2
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    • pp.107-113
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    • 2004
  • This paper develops a adaptive fuzzy controller based fuzzy logic control for high performance of permanent magnet synchronous motor(PMSM) drives. In the proposed system, fuzzy control is used to implement the direct controller as well as the adaptation mechanism. The operation of the direct fuzzy controller and the fuzzy logic based adaptation mechanism is studied. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive fuzzy controller is evaluated by simulation for various operating conditions. The validity of the proposed adaptive fuzzy controller is confirmed by performance results for PMSM drive system.

An iterative learning and adaptive control scheme for a class of uncertain systems

  • Kuc, Tae-Yong;Lee, Jin-S.
    • 제어로봇시스템학회:학술대회논문집
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    • 1990.10b
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    • pp.963-968
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    • 1990
  • An iterative learning control scheme for tracking control of a class of uncertain nonlinear systems is presented. By introducing a model reference adaptive controller in the learning control structure, it is possible to achieve zero tracking of unknown system even when the upperbound of uncertainty in system dynamics is not known apriori. The adaptive controller pull the state of the system to the state of reference model via control gain adaptation at each iteration, while the learning controller attracts the model state to the desired one by synthesizing a suitable control input along with iteration numbers. In the controller role transition from the adaptive to the learning controller takes place in gradually as learning proceeds. Another feature of this control scheme is that robustness to bounded input disturbances is guaranteed by the linear controller in the feedback loop of the learning control scheme. In addition, since the proposed controller does not require any knowledge of the dynamic parameters of the system, it is flexible under uncertain environments. With these facts, computational easiness makes the learning scheme more feasible. Computer simulation results for the dynamic control of a two-axis robot manipulator shows a good performance of the scheme in relatively high speed operation of trajectory tracking.

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Speed Sensorless Control of an Induction Motor using Fuzzy Speed Estimator (퍼지 속도 추정기를 이용한 유도전동기 속도 센서리스 제어)

  • Choi, Sung-Dae;Kim, Lark-Kyo
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.56 no.1
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    • pp.183-187
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    • 2007
  • This paper proposes Fuzzy Speed Estimator using Fuzzy Logic Controller(FLC) as a adaptive law in Model Reference Adaptive System(MRAS) in order to realize the speed-sensorless control of an induction motor. Fuzzy Speed Estimator estimates the speed of an induction motor with a rotor flux of the reference model and the adjustable model in MRAS. Fuzzy logic controller reduces the error of the rotor flux between the reference model and the adjustable model using the error and the change of error of the rotor flux as the input of FLC. The experiment is executed to verify the propriety and the effectiveness of the proposed speed estimator.

Model reference adaptive control of missiles with nonminimum-phase characteristics (비최소 위상 특성을 갖는 유도탄의 기준 모델 적응 제어)

  • 송찬호;김승환
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10a
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    • pp.418-423
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    • 1992
  • In this paper, a model reference adaptive control algorithm is applied to the design of the normal acceleration controller for missiles with nonminimum-phase characteristics. The method used in this paper is due to Ohkubo. In this scheme, a feedforward compensator is designed first so that the extended system becomes minimum-phase and after that an adaptive control algorithms is designed for the extended system. The feedforwrd compensator is obtained by solving the robust stabilization problem. It is shown that the performance of the designed controller is satisfied via computer simulation.

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A study on the model reference adaptive control using neural network (신경회로망을 이용한 기준모델 제어기에 관한 연구)

  • 조규상;김규남;양태진;유시영;김경기
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10a
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    • pp.243-247
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    • 1992
  • This paper describes a neural network based control scheme with MRAC. The system consists of two neural network; one is for identifier and the other is for controller. Identification is firstly performed to learn the behavior of the nonlinear plant. Neural net controller is next trained by backpropagating the error at the output of plant through the identifier. Also the training method used in this paper repeatedly updates weights of neural network to track the reference model.

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A study on a structure of a model reference adaptive fuzzy controller(MRAFC) (모델 레퍼런스 적응 퍼지 제어기 구조에 관한 연구)

  • Lee, Gi-Bum;Choi, Jong-Soo;Joo, Moon-Gab
    • Proceedings of the KIEE Conference
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    • 1998.07b
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    • pp.512-514
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    • 1998
  • The paper presents a model reference adaptive control containing a fuzzy algorithm for tuning the gain coefficient which adjusts the level of the fuzzy controller output. The synthesis of a fuzzy tuning algorithm has been performed for the inverted pendulum system. The computer simulation results have proved the efficiency of the proposed method, showing stable system responses.

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The Vibration Suppression Control of a Two-Mass System using a Reference Model (2관성계의 규범모델에 의한 진동억제제어)

  • Kim, Jin-Soo;Kang, Seog-Jin;Kim, Hyun-Jung;Kim, Young-Seok
    • Proceedings of the KIEE Conference
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    • 1998.07f
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    • pp.1872-1875
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    • 1998
  • In the industrial motor drive system, a shaft torsional vibration is often generated when a motor and a load are connected with a flexible shaft. This paper treats the vibration suppression control of such a system. Recently, there are new methods which estimate unknown state variables by using a reduced order observer and feedback these state variables by using a pole placement design method. But there is a trade-off between the fast command following property and the attenuation of disturbances and vibrations in these design methods. In this paper, the vibration suppression control of a two-mass system using a reference model is proposed. Because of using a reference model, the proposed control satisfy the fast command following property and the attenuation of disturbances and vibrations. Control parameter can be changed to maintain high system performance in control using a reference model. Experimental results show the validity of the proposed state feedback control using a reference model, and this controller is compared with the state feedback controller.

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Power Control of a Pitch-controlled Wind Power System (피치제어형 풍력발전시스템의 출력제어)

  • 임종환;허종철
    • Journal of the Korean Society for Precision Engineering
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    • v.20 no.4
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    • pp.84-91
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    • 2003
  • The paper presents a power control algorithm for a full pitch-controlled wind power system. The design of a pitch controller, in general, is performed by linearizing the torque in the vicinity of a operating point assuming the tip speed ratio is constant. For power control, however, the tip speed ratio is no longer a constant. In this study, a reference pitch model is derived in terms of a wind speed, angular velocity, and pitch angle. The reference pitch model is used to design a controller without linearizing the non-linear torque model of the blade. The validity of the algorithm is demonstrated with the results produced through sets of simulation.

Design of Time Delay Controller for a System with Bounded Control Inputs (제한된 제어 입력을 갖는 시스템에 대한 시간 지연 제어기의 설계)

  • 송재복;변경석
    • Journal of Institute of Control, Robotics and Systems
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    • v.5 no.2
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    • pp.166-173
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    • 1999
  • Reference models are used in many control algorithms for improvement of transient response characteristics. They provide desired trajectories that the plant should follow Most control systems have bounded control inputs to avoid saturation of the plant. If we design the reference models that do not account for limits of the control inputs, control performance of the system may be deteriorated. In this paper a new approach of avoiding saturation by varying the reference model for TDC(time delay control) based systems subject to step changes in the reference input. In this scheme, the variable reference model is determined based on the information on control inputs and the size of the step changes in the reference inputs. This scheme was verified by application to the BLDC motor position control system in simulations and experiments. The responses of the TDC with the variable reference model showed better tracking performance than that with the fixed reference model.

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