• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.5
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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.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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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.

• Proceedings of the KIEE Conference
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• 2006.04a
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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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• v.15 no.5
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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.

• Journal of IKEEE
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• v.1 no.1 s.1
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• pp.55-63
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• 1997

The purpose of this paper is to realize robust vector control of an induction motor without speed sensor. In order to do it, the speed of an induction motor is estimated using model reference adaptive system(MRAS) and two rotor flux observers which have robustness to the parameter variation are employed as the reference model and the adjustable model in MRAS speed estimator. The MRAS-based overall control scheme has been implemented on 2.2kW induction motor control system and it is verified that the proposed speed sensorless control scheme is more stable and robust than the conventional schemes.

• The Journal of the Korea institute of electronic communication sciences
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• v.3 no.4
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• pp.266-275
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• 2008

The sensorless speed control technique for BLDC motor using digital IP control is proposed in this paper for advanced speed characteristic which is robust to motor parameters and load variations. The sensorless drive of BLDC motor using terminal voltages is affected by load or speed because it uses analog filters to estimate the rotor position. For this reason, the robust speed controller with the accurate rotor position estimator is needed for sensorless control which is robust to load and insensitive to motor parameters. The constant speed robust to load variation and the stable sensorless control of BLDC motor robust to the increase or decrease of speed with constant load is implemented using digital IP control in this paper. The validity to these is established with experimentation.

• Wind and Structures
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• v.26 no.6
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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.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.3
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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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.5C
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• pp.378-385
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• 2008

This paper has been designed with CMOS Analog-to-Digital Converter(ADC) to use a high speed embedded system. It used flash ADC with a voltage estimator and comparator for background developed autozeroing. The speed of this architecture is almost similar to conventional flash ADC but the die size are lower due to reduced numbers of comparators and associated circuity. This ADC is implemented in a $0.25{\mu}m$ pure digital CMOS technology.

• The Transactions of the Korean Institute of Power Electronics
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• v.24 no.1
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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.