• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.05a
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• pp.112-116
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• 2002

A sensorless control strategy for permanent magnet synchronous motors is presented in this paper. A speed control scheme based on the measurement and observation of stator current, voltage. and flux vector is proposed. Two phase voltages and two stator currents are measured and processed in discrete form in DSP. The rotor position and speed are estimated through the stator flux and its derivative estimation. Flux and its derivative are calculated in the stationary reference frame and used to estimate the speed and position. The rotor position angle is then used in a microcontroller to produce the appropriate stator current command signals for the hysteresis current controller of the inverter. The closed-loop speed control has been shown to be effective from standstill to rated speed. Moreover, a flux drift problem caused by the integration can be eliminated so that a stable sensorless starting and running operation can be achieved. Computer simulation and experimental results are presented to demonstrate the effectiveness of the proposed scheme.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.199-205
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• 2002

This application study presents a solution to control a Permanent Magnet Synchronous Motor without sensors. The use of this system yields enhanced operations, fewer system components, lower system cost , energy efficient control system design and increased efficiency. The control method presented is field oriented control (FOC). The sinusoidal voltage waveforms are generated by the power module using the space vector modulation technique. A practical solution is described and results are given in this application Study. The performance of a Sensorless architecture allows an intelligent approach to reduce the complete system costs of digital motion control applications using cheaper electrical motors without sensors. This paper deals with an overview of sensorless solutions in digital motor control applications whereby the focus will be the new Controller without sensors and its applications.

• Proceedings of the KIEE Conference
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• 1998.07f
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• pp.1993-1995
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• 1998

The compensation problem of error and various problems due to delay of speed sensor itself and speed detection have issued in case using speed sensor in the adjustable speed control of induction motor. This paper have applied the stator flux oriented vector control algorithm and space voltage vector PWM method in order to improve an dynamic character of voltage-source inverter system, and also used the better IP controller in the speed response than Pl controller as speed controller. This paper estimated the rotator speed using input current of inductor motor and flux component invoked through voltage drop by terminal voltage and stator resistor.

• Proceedings of the KIPE Conference
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• 1996.06a
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• pp.1-4
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• 1996

The purpose of this treatise is to estimate speed of an induction motor and realize a robust speed control system with estimated speed in field-weakening region. A speed estimation is based on Model Reference Adaptive System(MRAS) technique and two flux estimator are designed to be robust against parameter variation. The MRAS-based overall control scheme has been implemented on 7.5kW Spindle induction motor control system. And it is verified that the proposed control scheme is very stable and robust in field-weakening region.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2004.05a
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• pp.119-124
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• 2004

A new control method of spindle induction motor drive is proposed in this paper. In a conventional control method, the vector control was employed in the low speed range, while the constant V/f(volt-per-hertz) PWM control was employed in the high speed range. The two control modes were automatically selected at an intermediate speed. In a proposed control method, the direct vector-control with an encoder is employed in the low speed range(from 0 to 8,000rpm), and the vector control without an encoder is employed in th high speed(from 8,000 to 15,000rpm) by using flux observer and speed estimator. This paper describes problem of control method in a conventional spindle induction motor drive and proposes contort method as variation of motor speed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.4
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• pp.886-890
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• 2011

Induction motors are relatively cheap and rugged machines. For the vector control of induction motors, a position or speed sensor is needed. But a speed sensor increases motor cost and reduces reliability in harsh environment. Recently, many studies have been performed for sensorless speed control. This paper investigates an improved flux observer with the parameter error compensation for a sensorless induction motor. The proposed algorithm is verified through simulation and experiment.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.1
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• pp.169-175
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• 2006

This paper describes how an Artificial Neural Network(ANN) can be employed to improve a speed estimation in a vector controlled induction motor drive. The system uses the ANN to estimate changes in the motor resistance, which enable the sensorless speed control method to work more accurately. Flux Observer is used for speed estimation in this system. Obviously the accuracy of the speed control of motor is dependent upon how well the parameters of the induction machine are known. These parameters vary with the operating conditions of the motor; both stator resistance(Rs) and rotor resistance(Rr) change with temperature, while the stator leakage inductance varies with load. This paper proposes a parameter compensation technique using artificial neural network for accurate speed estimation of induction motor and simulation results confirm the validity of the proposed scheme.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.11a
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• pp.47-48
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• 2005

This paper describes how an Artificial Neural Network(ANN) can be employed to improve a speed estimation in a vector controlled induction motor drive. The system uses the ANN to estimate changes in the motor resistance, which enable the sensorless speed control method to work more accurately. Flux Observer is used for speed estimation in this system. Obviously the accuracy of the speed control of motor is dependent upon how well the parameters of the induction machine are known. These parameters vary with the operating conditions of the motor; both stator resistance(Rs) and rotor resistance(Rr) change with temperature, while the stator leakage inductance varies with load. This paper proposes a parameter compensation technique using artificial neural network for accurate speed estimation of induction motor and simulation results confirm the validity of the proposed scheme.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.5
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• pp.40-47
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• 2012

The PMSM position sensor using two rectangular hall sensors can restrictively acquire the 90[$^{\circ}$] position information of rotor according to electrical angle. Thus, the control method using this position sensor cannot react properly to a rapid load torque change. On the other hand, even though a sensorless method has the advantage of acquiring instantaneous rotor position information, the accuracy of position sensor can be determined by the gain value of estimator. This paper suggests a robust speed control method on torque fluctuation condition, which combines low cost two rectangular hall sensors and sensorless control method.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2304-2306
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• 2004

This paper proposes an Intelligent Speed Estimator in order to realize the speed-sensorless vector control of an induction motor. Intelligent Speed Estimator used Model Reference Adaptive System which has Fuzzy-Neural adaptive mechanism as Speed Estimation method. The Intelligent Speed Estimator estimates the speed of an induction motor with a rotor flux of a reference model and adjustable model in MRAS. The Intelligent Speed Estimator reduces the error of the rotor flux between the voltage flux model and the current flux model using the error and the change of error as input of the Estimator. The computer simulation is executed to verify the propriety and the effectiveness of the proposed speed estimator.