• 전기학회논문지
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• 제65권11호
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• pp.1894-1899
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• 2016

In this paper, because the position sensor represents the important factor in BLDC (Brushless DC) motor drives, BLDC motor is necessary that the three Hall-sensors evenly be distributed around the stator circumference in case of the 3 phase motor. The Hall-sensor is set up in this motor to detect the main flux from the rotor. So the output signal from Hall-sensor is used to drive IGBT to control the stator winding current. However, in case of breakdown Hall sensor, we research that the estimation algorithm of Hall sensor signal to detect rotor position and for the speed feedback signals with BLDC motor whose six stator and two rotor designed. In addition, this paper presents a sensorless speed control of BLDC Motor using terminal voltage of the one phase. Rotor position information is extracted by indirectly sensing the back EMF from only one of the three terminal voltages for a three-phase BLDC motor.

• 전력전자학회:학술대회논문집
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• 전력전자학회 1999년도 전력전자학술대회 논문집
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• pp.544-548
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• 1999

Using Observer, on the sensorless vector control system is a novel techniques for modern induction motor control. In this paper, a speed estimation algorithm of an induction motor using an extended kalman filter was proposed. Extended kalman filter can solve the problem, that have steady state error of estimated speed in flux and slip estimation method. The extended Kalman filter is employed to identify the speed of an induction motor and rotor flux based on the measured quantities such as stator current and DC link voltage. In order to confirming above proposal, computer simulation carried out using Matlab Simulink and show the effectiveness of the control drives for induction motor speed estimation.

• 전력전자학회:학술대회논문집
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• 전력전자학회 1999년도 전력전자학술대회 논문집
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• pp.526-530
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• 1999

This paper presents a newly developed speed sensorless drive using Neural Network algorithm. Neural Network algorithm can be divided into three categories. In the first one, a Back Propagation-based NN algorithm is well-known to gradient descent method. In the second scheme, a Extended Kalman Filter-based NN algorithm has just the time varying learning rate. In the last scheme, a Recursive Least Square-based NN algorithm is faster and more stable than the classical back-propagation algorithm for training multilayer perceptrons. The number of iterations required to converge and the mean-squared error between the desired and actual outputs is compared with respect to each method. The theoretical analysis and experimental results are discussed.

• Journal of Advanced Marine Engineering and Technology
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• 제27권7호
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• pp.930-936
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• 2003

A new method of direct current motor drive, which requires neither shaft encoder nor speed estimator, is presented. The proposed scheme is based on decreasing current gap between a numerical model and an actual motor. By supplying the identical instantaneous voltage to both model and motor in the direction of reducing the current difference, the rotor approaches to the model speed, that is, reference value. The performance of direct current motor drives without speed sensor is generally poor at very low speed. However, in this system, it is possible to obtain good speed performance in the low speed range.

• 전력전자학회:학술대회논문집
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• 전력전자학회 1998년도 전력전자학술대회 논문집
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• pp.384-387
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• 1998

This paper presents a newly developed speed sensorless drive using RLS(Recursive Least Squares) based on Neural Network Training Algorithm. The proposed algorithm based on the RLS has just the time-varying learning rate, while the well-known back-propagation (or generalized delta rule) algorithm based on gradient descent has a constant learning rate. The number of iterations required by the new algorithm to converge is less than that of the back-propagation algorithm. The RLS based on NN is used to adjust the motor speed so that the neural model output follows the desired trajectory. This mechanism forces the estimated speed to follow precisely the actual motor speed. In this paper, a flux estimation strategy using filter concept is discussed. The theoretical analysis and experimental results to verify the effectiveness of the proposed analysis and the proposed control strategy are described.

• 전력전자학회:학술대회논문집
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• 전력전자학회 1998년도 전력전자학술대회 논문집
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• pp.212-216
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• 1998

For a Switched Reluctance Motor(SRM) drive, the important things are 1) reducing torque ripple, 2) improving efficiency, 3) sensorless speed control, 4) accurate position. The position information impotant for the efficiency and smoothness drives. Since SRMs characteristics are nonlinear. It is difficult to estimated phase current in saturation region. This paper describes a method for indirect sensing of the rotor position in SRM which use both voltage and current. The method obtains rotor position by using unconducting phase. The information about the rotor position is achieved by differentiating the unconducting phase current or the voltage gradient. And then, this paper presents a torque control with indirect rotor position detection methods. This torque control is achieved by developing a detailed nonlinear model of the motor.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제55권2호
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• pp.98-106
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• 2006

This paper proposes to position and speed control of interior Permanent magnet synchronous motor(IPMSM) drive without mechanical sensor. Also, this paper develops a adaptive fuzzy controller based fuzzy logic control for high performance of PMSM drives. In the proposed system, fuzzy control is used to implement the direct controller as well as the adaptation mechanism. A Gopinath observer is used for the mechanical state estimation of the motor. The observer was developed based on nonlinear model of IPMSM, that employs a d-q rotating reference frame attached to the rotor. A Gopinath observer is implemented to compute the speed and position feedback signal. The validity of the proposed scheme is confirmed by various response characteristics.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 A
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• pp.149-151
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• 1998

Speed and position sensors require the additional mounting space, reduce the reliability, and increase the cost of motor. Various control algorithms have been proposed for the elimination of speed senor. This paper compares several schemes of MRAC for field-oriented control of induction motor without speed and flux sensors. These schemes are based on observing the fluxes, the counter EMF, and the instantaneous reactive power of motor. A review of these schemes of MRAC is presented. Then sensorless drives using each estimation method are compared through simulation and experiment.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.2255-2257
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• 2001

This paper introduces a indirect rotor position and speed estimation algorithm for the SRM(switched reluctance motor) sensorless control, based on the sliding mode observer. The information of position and speed is generally provided by encoder or resolver. However, the position sensor not only adds complexity, cost, and size to the whole drive system, but also causes limitation for industrial applications. In this paper, in order to eliminate the position sensor, indirect position sensing method using sliding mode observer is used for SRM drives. And this observer parameters are optimized by evolutionary algorithm. PI controller is also optimized for the SRM to track precisely using evolutionary algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.173-174
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• 2007

In this paper, a new speed sensorless control based on an instantaneous reactive power and a fuzzy PI compensator are proposed for the interior permanent magnet synchronous motor (IPMSM) drives. The conventional fixed gain PI and PID controllers are very sensitive to step change of command speed, parameter variations and load disturbance. Also, to the estimated speeds are compensated by using an instantaneous reactive power in synchronously rotating reference frame. In a fuzzy compensator, the system control parameters are adjusted by a fuzzy rule based system, which is a logical model of the human behavior for process control. The effectiveness of algorithm is confirmed by the experiments.