• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 추계학술대회 논문집 학회본부
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• pp.148-151
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• 1991

This paper describes the vector control system estimates rotor speed based on MRAS(Model Reference Adaptive Control) and this estimate is used for speed feedback control. The stability of speed estimator is proved on the basis of hyperstability theory. In order to improve the performance of speed control, the load torque is estimated by load torque observer and speed controller compensates this estimate value. Thus the robust vector control system against load torque disturbance is constructed.

• 전력전자학회:학술대회논문집
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• 전력전자학회 1996년도 창립기념 전력전자학술발표회 논문집
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• pp.13-16
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• 1996

A new instantaneous torque control technique is presented for a high performance control of a permanent magnet synchronous motor. Using the model reference adaptive system technique, the linkage flux of the motor is estimated and the torque is instantaneously controlled by the proposed torque controller combining with a variable structure control and space vector PWM. The proposed torque control provides the advantage of reducing the torque pulsation caused by the flux harmonics. This control strategy is applied to the high torque PM synchronous motor drives for direct drive systems and is implemented by using a software of the DSP TMS320C30. The experiments are carried out for this system and the results well demonstrate the effectiveness of the proposed control.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1988년도 추계학술대회 논문집 학회본부
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• pp.76-79
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• 1988

The sliding mode control in an effective method to eatablish robustness against parameter variation and disturbance. But. In sliding mode strategy, the control function is discontinuous on the hyperplane. However the discontinuous change in control structure caves the controller input to chaffer and gives non-zero steady state error. Consequently, a multiloop feedback control system supplemented by a complelmentary controller is used to improved the drive performence of a DC servo motor and reduce sensitivity to parameter variation, nonlinear effects, and other disturbances.

• 한국기계가공학회지
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• 제2권4호
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• pp.46-52
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• 2003

For position control of electro-hydraulic servo system, single rod cylinders and double rod cylinders are used. Single rod cylinders have simple structure for manufacturing but different volume ratio of two sides induce to non-linearity in process of then mathematical modeling. So only with conventional PID control method it is difficult to control single rod cylinders precisely. For mole precise position control of single rod cylinders, a controller which is inserted a velocity feedback PID controller and MRAC controller are proposed. With experiment control performances of three control methods are compared. In case of experiment, for external varying load to the system, a hydraulic cylinder and a pressure control valve are used. In conclusion a MRAC is considered a suitable control method for external varying load.

• 한국조명전기설비학회지:조명전기설비
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• 제9권1호
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• pp.54-62
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• 1995

본 논문은 기준 모델 적용-이산 슬라이딩 모드(MRA-DSN) 제어기를 이용한 유도전동기의 속도 제어에 관한 연구이다. 유도전동기의 속도 제어시, 부하 변동에 따라 전체 시스템이 파라미터 변화나 외란에 대해 둔감힌 강인성을 갖도록 하기 이해 이산 슬라이딩 모드(DSM) 알고리즘을 이용하여 마이크로프로세서에 의한 디지털 제어기로 시스템의 동특성을 제어하였다. 또한 슬라이딩 동작시에 발생하는 불연속 제어 입력을 보상하고 제어 대상의 파라미터 변동에 관계없이 기준 모델을 추종하여 제어할 수 있는 기준 모델 적응(MRA) 알고리즘을 부가한 MRA-DSM제어 알고리즘을 제시하였다. 제어 시스템 구성시, 제어 시스템의 성능을 국대화하고 실시간 처리를 위하여 각각의 기능을 갖는 마이크로프로세서들로 병렬 처리 제어기를 구성하였다. 또한 소프트웨어를 이용하여 시스템을 제어함으로써 하드웨어 구성을 단순화시킬 수 있었고, 시스템의 신뢰성을 향상시켰다. 그리고 DSM 제어를 기준으로 할 때, MRA-DSM 제어시 27.2%의 빠른 응답특성을 얻었다.

• Journal of Positioning, Navigation, and Timing
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• 제5권1호
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• pp.1-9
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• 2016

Range-based wireless localization system must measure accurate range between a mobile node (MN) and reference nodes. However, non-line-of-sight (NLOS) error caused by the spatial structures disturbs the localization system obtaining the accurate range measurements. Localization methods using the range measurements including NLOS error yield large localization error. But filter-based localization methods can provide comparatively accurate location solution. Motivated by the accuracy of the filter-based localization method, a filter residual-based NLOS error estimation method is presented in this paper. Range measurement-based residual contains NLOS error. By considering this factor with NLOS error properties, NLOS error is mitigated. Also a process noise covariance matrix tuning method is presented to reduce the time-delay estimation error caused by the single dynamic model-based filter when the speed or moving direction of a MN changes, that is the used dynamic model is not fit the current dynamic of a MN. The presented methods are evaluated by simulation allowing direct comparison between different localization methods. The simulation results show that the presented filter is more accurate than the iterative least squares- and extended Kalman filter-based localization methods.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제49권9호
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• pp.626-634
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• 2000

The paper describes a new and rigorous mathematical model using counter-EMF for the rotor field oriented system with induction motor which uses the estimated speed and rotor flux based on a Model Reference Adaptive System as well as the real-time approach. The estimated speed and rotor flux is used for the speed and flux feedback control. The stability and the convergence of the estimator are improved on the basis of hyperstability theory for non-linear systems. The validity of the proposed method is verified by simulation and also the sensorless control was tested on the propulsion system simulator used for the development of Korean High-Speed Railway Train(KHSRT).

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 B
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• pp.1136-1139
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• 2000

The paper describes a new and rigorous mathematical model for the rotor field oriented system with induction motor which uses the estimated speed and rotor flux based on a Model Reference Adaptive System, as well as the real-time approach. The estimated speed and rotor flux is used for the speed and flux feedback control. The stability and the convergence of the estimator are improved on the basis of hyperstability theory for non-linear systems. The real-time controller and estimator are implemented with a sampling period of $926{\mu}s$ using a dual TMS320C44 floating-point digital signal processor. The validity of the proposed method is verified by simulation, and also, the sensorless control was tested on the propulsion system simulator, used for the development of Korean High-Speed Railway Train (KHSRT) [5].

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 춘계학술대회 논문집 에너지변화시스템부문
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• pp.26-28
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• 2009

This paper proposes maximum torque control of IPMSM drive using adaptive teaming mechanism-fuzzy neural network (ALM-FNN) controller, model reference adaptive fuzzy tonal(MFC) and artificial neural network(ANN). This control method is applicable over the entire speed range which considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using ALM-FNN, MFC and ANN controller. The proposed control algorithm is applied to IPMSM drive system controlled ALM-FNN, MFC and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the ALM-FNN, MFC and ANN controller.

• 조명전기설비학회논문지
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• 제25권5호
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• pp.22-33
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• 2011

An induction motor operated with a conventional direct self controller(DSC) shows a sluggish response during startup and under changes of torque command. Fuzzy logic controller(FLC) is used in conjection with DSC to minimize these problems. A FLC chooses the switching states based on a set of fuzzy variables. Flux position, error in flux magnitude and error in torque are used as fuzzy state variables. Fuzzy rules are determinated by observing the vector diagram of flux and currents. This paper proposes hybrid fuzzy controller for direct torque control(DTC) of induction motor drives. The speed controller is based on adaptive fuzzy learning controller(AFLC), which provide high dynamics performances both in transient and steady state response. Flux position, error in flux magnitude and error in torque are used as FLC state variables. The speed is estimated with model reference adaptive system(MRAS) based on artificial neural network(ANN) trained on-line by a back-propagation algorithm. This paper is controlled speed using hybrid fuzzy controller(HFC) and estimation of speed using ANN. The performance of the proposed induction motor drive with HFC controller and ANN is verified by analysis results at various operation conditions.