• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제53권5호
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• pp.332-337
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• 2004

A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and stator resistance in IPMSM Drives. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying. parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator is confirmed by the operating characteristics controlled by neural networks control.

• 제어로봇시스템학회논문지
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• 제13권5호
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• pp.429-433
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• 2007

A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and ststor resistance in IPMSM Drives. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator is confirmed by the operating characteristics controlled by neural networks control.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 심포지엄 논문집 정보 및 제어부문
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• pp.207-209
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• 2006

A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and ststor resistance in IPMSM Drives. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator is confirmed by the operating characteristics controlled by neural networks control.

• Journal of Power Electronics
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• 제15권5호
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• pp.1264-1273
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• 2015

An inverter output power control based power factor correction (PFC) strategy is being extensively used for permanent magnet synchronous motor (PMSM) drives in appliances because such a strategy can considerably reduce the cost and size of the inverter. In this strategy, PFC circuits are removed and large electrolytic DC-link capacitors are replaced with small film capacitors. In this application, the PMSM d-q axes currents are controlled to produce ripples, the frequency of which is twice that of the AC main voltage, to obtain a high power factor at the AC mains. This process indicates that the PMSM operates under periodic magnetic saturation conditions. This paper proposes a back electromotive-force (back-EMF) estimator for the high-speed sensorless control of PMSM operating under periodic magnetic saturation conditions. The transfer function of the back-EMF estimator is analyzed to examine the effect of the periodic magnetic saturation on the accuracy of the estimated rotor position. A simple compensation method for the estimated position errors caused by the periodic magnetic saturation is also proposed in this paper. The effectiveness of the proposed method is experimentally verified with the use of a PMSM drive for a vacuum cleaner centrifugal fan, wherein the maximum operating speed reaches 30,000 rpm.

• 전기전자학회논문지
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• 제1권1호
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• pp.55-63
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• 1997

본 논문의 목적은 유도 전동기의 속도 센서 없는 견실한 벡터 제어의 구현에 있다. 이를 위해 MRAS(Model Reference Adaptive System)를 사용하여 유도 전동기의 속도를 추정하였고 파라미터 변동에 견실한 두 개의 회전자 자속 관측기를 설계하여 MRAS 속도 추정기에 기준 모델과 추정 모델로 사용하였다. MRAS에 근거를 둔 전체 제어 기법은 2.2kW 유도 전동기의 벡터 제어 드라이브를 사용하여 실현되었으며, 본 논문에서 제한한 속도 센서 없는 벡터 제어 기법이 기존의 속도 센서 없는 제어 기법에 비해 보다 안정하고 견실함을 증명하였다.

• 한국전자통신학회논문지
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• 제3권4호
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• pp.266-275
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• 2008

본 논문에서는 전동기 파라미터와 부하에 강인한 속도 특성을 위해 디지털 IP제어를 이용한 BLDC 전동기의 센서리스 속도제어 방식을 제안한다. 단자 전압을 이용한 BLDC 전동기의 센서리스 구동시 회전자 위치 추정을 위해 아날로그 필터를 사용하기 때문에 부하나 속도에 영향을 받는다. 전동기 파라미터에 둔감하고 부하의 영향에도 강건한 센서리스 속도제어를 하기 위해서는 정확한 회전자 위치 추정과 연동하는 강인한 속도 제어기가 필요하다. 본 논문에서는 디지털 IP제어를 이용하여 부하의 변동에도 강인한 정속제어와 일정 부하로 운전 중 가감속시 임의의 속도변화에 대해 BLDC 전동기의 안정된 센서리스 제어가 가능하도록 구성하였다. 이에 대한 타당성은 실험을 통하여 입증하고자 한다.

• Wind and Structures
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• 제26권6호
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• pp.383-395
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• 2018

An accurate determination of wind speed distribution is the basis for an evaluation of the wind energy potential required to design a wind turbine, so it is important to estimate unknown parameters of wind speed distribution. In this paper, Gumbel distribution is used in modelling wind speed data, and alternative robust estimation methods to estimate its parameters are considered. The methodologies used to obtain the estimators of the parameters are least absolute deviation, weighted least absolute deviation, median/MAD and least median of squares. The performances of the estimators are compared with traditional estimation methods (i.e., maximum likelihood and least squares) according to bias, mean square deviation and total mean square deviation criteria using a Monte-Carlo simulation study for the data with and without outliers. The simulation results show that least median of squares and median/MAD estimators are more efficient than others for data with outliers in many cases. However, median/MAD estimator is not consistent for location parameter of Gumbel distribution in all cases. In real data application, it is firstly demonstrated that Gumbel distribution fits the daily mean wind speed data well and is also better one to model the data than Weibull distribution with respect to the root mean square error and coefficient of determination criteria. Next, the wind data modified by outliers is analysed to show the performance of the proposed estimators by using numerical and graphical methods.

• 한국정밀공학회지
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• 제20권3호
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• pp.58-65
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• 2003

Vehicle acceleration data from an accelerometer and wheel speed data from standard, 50-tooth antilock braking system wheel speed sensors are used to estimate the absolute longitudinal speed of a vehicle. We develop the four velocity estimation algorithms. And we compare experimental results with the Butterworth filtered speed from the fifth wheel and find that it is possible to estimate absolute longitudinal vehicle speed during a hard braking maneuver lasting three seconds.

• 한국통신학회논문지
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• 제33권5C호
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• pp.378-385
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• 2008

본 논문은 고속 임베디드 시스템에 사용하기 위해 CMOS AD 변환기(Analog-to-Digital Converter)를 설계하였다. 이 AD 변환기는 효율적인 구조로 설계하기 위하여 전압을 예측할 수 있는 플래시 AD 변환기와 자동 영을 기반으로 하여 설계된 비교기를 사용하였다. 이 구조의 변환속도는 기존의 플래시 AD 변환기와 거의 같지만 비교기와 연결된 회로가 줄어들었기 때문에 전체 회로의 크기를 크게 줄일 수 있었다. 이 ADC는 $0.25{\mu}m$ 디지털 CMOS 기술로 구현되었다.

• 전력전자학회논문지
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• 제24권1호
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• pp.25-32
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• 2019

Recent high-end treadmills are demanding stable performance at lower speeds. In this study, a slip control-based induction motor sensorless algorithm for treadmills, which have heavy load variations, is proposed. A modified Gopinath flux estimator is used to evaluate the rotor flux. Results indicate that a good speed regulation performance is achieved even at a low speed of approximately 3 Hz with a nominal exercise load of 90 kg body weight. The slip calculation method in the stationary coordinate system is adopted to improve the control stability. The proposed algorithm is verified throughout the simulation study using PSIM, and the experimental test consists of a commercial treadmill system.