• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.61-64
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• 1988

This paper deals with some aspects for the design of induction servomotors with respect to permanent magnet servomotors and standard induction motors as control components. Induction servomotors have much lower weight and moment of inertia than the DC servomotor but cannot reach the excellent values of a brushless DC servomotor with rare earth magnets.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.452-455
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• 2003

Based on a field-oriented model of induction motor, adaptive backstepping approach using neural network(RBFN) is proposed for the control of induction motor in this paper. In order to achieve the speed regulation with the consideration of avoiding singularity and improving power efficiency, rotor angular speed and flux amplitude tracking objectives are formulated. rotor resistance uncertainty is compensated by adaptive backstepping and mechanical lumped uncertainty such as load torque disturbance, inertia moment, friction by RBFN. Simulation is provided to verify the effectiveness of the proposed approach.

• 한국기계연구소 소보
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• s.17
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• pp.49-59
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• 1987

• 전기의세계
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• v.29 no.8
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• pp.491-494
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• 1980

• JOURNAL OF ELECTRICAL WORLD
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• no.8 s.80
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• pp.13-16
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• 1983

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.60 no.3
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• pp.138-143
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• 2011

Electric locomotive is adapted to high speed driving and mass transportation due to obtaining high traction force. The electric locomotive is operated by motor blocks and traction motors. Train speed is controlled by suppling power from motor blocks to traction motors according to reference speed. Speed control of the electric locomotive is efficient by spending energy between motor blocks and traction motors. Currently, switched reluctance motors have been studied because the efficient is higher than induction motors. In this paper, model of the switched reluctance motor is presented and the PID controller is applied to the model for the speed control by using Simulink. Asymmetry converter is used for real-time control and system performance is demonstrated by simulating the speed of switched reluctance motor including PID controller.

• Journal of Power Electronics
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• v.17 no.1
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• pp.149-160
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• 2017

To improve the performance of sensorless induction motor (IM) drives, an adaptive speed estimation method based on a strong tracking extended Kalman filter with a least-square algorithm (LS-STEKF) for induction motors is proposed in this paper. With this method, a fading factor is introduced into the covariance matrix of the predicted state, which forces the innovation sequence orthogonal to each other and tunes the gain matrix online. In addition, the estimation error is adjusted adaptively and the mutational state is tracked fast. Simultaneously, the fading factor can be continuously self-tuned with the least-square algorithm according to the innovation sequence. The application of the least-square algorithm guarantees that the information in the innovation sequence is extracted as much as possible and as quickly as possible. Therefore, the proposed method improves the model adaptability in terms of actual systems and environmental variations, and reduces the speed estimation error. The correctness and the effectiveness of the proposed method are verified by experimental results.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.65 no.2
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• pp.88-93
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• 2016

Soft starters are used with large induction motors in blowers, fans, pumps and the crane hoist drives. AC voltage controllers are used as soft starters in induction motors for starting and to adjust its speed. Soft-starter starting system uses phase control method of input electric source through the setting of the thyristor(SCR) firing angle ${\alpha}$, and it can control input electric source stably and continuously from beginning of starting to ending of starting. In this paper, it is verified that power stack of high-voltage with SCR series system possesses dielectric strength and input electric source is controlled stably by phase control. Especially, from the driving experimental of proposed soft-starter operating, a smoothing acceleration and inrush current decrease can be achieved by the series SCR trigger.

• Journal of Power Electronics
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• v.17 no.5
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• pp.1203-1210
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• 2017

This paper presents an improved switching selection method for the direct torque control (DTC) of five-phase induction motors (IMs). The proposed method is conducted using optimal switching selection. A five-phase inverter has 32 voltage vectors which are divided into 30 nonzero voltage vectors and two zero voltage vectors. The magnitudes of the voltage vectors consist of large, medium, and small voltage vectors. In addition, these vectors are related to the torque response and torque ripple. When a large voltage vector is selected in a drive system, the torque response time decreases with an increased torque ripple. On the other hand, when a small voltage vector is selected, the torque response time and torque ripple increase. As a result, this paper proposes an optimal voltage vector selection method for improved DTC of a five-phase induction machine depending on the situation. Simulation and experimental results verify the effectiveness of the proposed control algorithm.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.48 no.2
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• pp.49-55
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• 1999

This paper proposes an efficient 2D Finite Element Method(FEM) taking into account the end-ring of three phase squirrel-cage induction motors. The parameters of the squirrel-cage induction motor such as conductivity of secondary conductor have an effect on the characteristics of a motor. Especially, if the characteristic analysis is done without considering the end-ring, the good results can not be obtained. Therefore, we calculated a new resistivity of the secondary conductor including the end-ring's resistance to apply the 2D FEM. Then, the performances of the motors are analyzed by using the new resistivity of secondary conductor which contains the end-ring resistivity. The validity of the proposed method is verified by comparing the numerical results with experimental ones.