• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.1027-1028
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• 2006

In this paper, design of current and speed controller for DC motor drive system using Embedded Target for TI C2000DSP in Matlab/Simulink is introduced. Current and speed controller is designed and implemented using program simply and easily, and speed control response of DC motor can be advanced. Current and speed control of DC motor is carried in eZdsp F2812 control board using Embeded Target for TI C2000DSP in Matlab/Simulink. Speed feedback is processed through A/D converter using tacho generator as speed sensor, and current feedback is processed through A/D converter using hall sensor as current sensor. Controller is designed to PI current controller and PI speed controller. Current and speed response is verified through simulations and experiments.

• Proceedings of the KIEE Conference
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• 1999.07a
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• pp.461-464
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• 1999

To improve traction effort performance and stability for the Korean High-Speed Railway Train, practical re-adhesion controller including a novel anti-slip control scheme is proposed. The presented method is verified by train running simulation results based on induction motor vector control with PWM inverter.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.516-518
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• 1999

This paper presents an feed-forward neural network design instead PI controller for the speed control of an Induction Motor. The design employs the training strategy with Neural Network Controller(NNC) and Neural Network Emulator(NNE). Emulator identifies the motor by simulating the input and output map. In order to update the weights of the Controller. Emulator supplies the error path to the output stage of the controller using backpropagation algorithm. and then Controller produces an adequate output to the system due to neural networks learning capability. Therefore it becomes adjustable to the system with changing characteristics caused by a load. The speed control based on neural networks for induction motor is implemented by a vector controlled induction motor. The simulation results demonstrate that actual motor speed with neural network system well follows the reference speed minimizing the error and is available to implement on the vector control theory.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.566-569
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• 2005

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. The paper is proposed maximum torque control of IPMSM drive using artificial intelligent(AI) controller. The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using AI controller. This paper is proposed speed control of IPMSM using learning mechanism fuzzy neural network(LM-FNN) and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled LM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also. this paper is proposed the experimental results to verify the effectiveness of AI controller.

• The Transactions of the Korean Institute of Power Electronics
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• v.23 no.1
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• pp.16-23
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• 2018

PM synchronous motor may be rotated to an arbitrary direction and speed by outside wind under natural condition in cases where the fan is applied outside, such as in vehicle radiators and outdoor air-conditioners. Sensorless controls that cannot detect rotor position requires additional sensorless control algorithm because a rotor is rotated by an external load. In this study, the sensorless control of a PM synchronous motor under naturally rotating condition is proposed. The natural rotation conditions are classified as forward high-speed rotation, reverse high-speed rotation, and low-speed rotation. Experiment results verify the performance of the sensorless control, including the rotor speed and position detection at natural rotation mode and switch to the closed-loop sensorless control.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.3
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• pp.110-114
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• 2006

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. In this paper maximum torque control of IPMSM drive using artificial intelligent(AI) controller is proposed. The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using AI controller. This paper is proposed speed control of IPMSM using adaptive learning mechanism fuzzy neural network(ALM-FNN) and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled ALM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the experimental results to verify the effectiveness of AI controller.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2006.05a
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• pp.309-314
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• 2006

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. This paper proposes maximum torque control of IPMSM drive using adaptive learning fuzzy neural network and artificial neural network. This control method is applicable over the entire speed range which considered the limits of the inverter's current md voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using adaptive teaming fuzzy neural network and artificial neural network. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper proposes speed control of IPMSM using adaptive teaming fuzzy neural network and estimation of speed using artificial neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled adaptive teaming fuzzy neural network and artificial neural network, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the adaptive teaming fuzzy neural network and artificial neural network.

• Journal of Advanced Navigation Technology
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• v.10 no.3
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• pp.191-197
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• 2006

In the paper propose a sensorless sliding mode control method of an induction motor using an adaptive speed control. The control objective is apply to adaptive speed observer instead of a encoder and to remove errors using the sliding mode current controller by parameters variation and disturbances that include the current controller. A stability of the sliding mode current controller and the adaptive speed observer using a design controller is guaranteed by the Lyapunov stability criterion. The performance of the proposed control system is demonstrated by simulation using the matlab silmulink and experimental results using induction motor show that the proposed method can apply an induction motor control.

• Journal of Korean Port Research
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• v.11 no.2
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• pp.273-280
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• 1997

Recently the importance of the cargo handling equipments in a port has been increasing to get strong competition from other ports. Many ports are making efforts to modernize their cargo handling equipments. The kernel technology of such equipments is the speed control of DC motor which is used as an essential part of them. In this paper, we discuss the speed control of a DC motor as a basic work for building cargo handling equipments in a port. DC Motors are still widely used in industrial fields, as driving power motor for electrical fields. DC drives, being easy to control, are widely used in many variable-speed and position control drive system. Traditional analog control circuits used in such applications have many disadvantages. Complex control schemes are difficult to implement with analog components. All these factor and invention of the microprocessor has made it possible to use digital control circuits, using microprocessing system. These digital circuits have been found to be reliable, flexible, and also immune to noise. In this paper it presents the speed control of a SCR DC motor driver which using dual converter by 80c196kc microprocessor. We developed a thyristor power amplifier which does not cause damage thyristor because it is designed to prevent triggering the two SCRs in the same arm simultaneously. And it was analyzed voltage and currents wave at reactive load.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1473-1479
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• 2011

In this paper, speed control of IPMSM drives for the next generation domestic high speed railway system using multilevel inverter is presented. Multilevel inverter is suitable for the high-voltage high-capacity motor drive system because noise and switching frequency of power semiconductor devices is reduced. For the speed control of IPMSM using multilevel inverter, maximum torque control is applied in a constant torque region, and field weakening control is applied in a constant power region. Simulation programs based on Matlab/Simulink are developed. Finally the designed system is verified by simulation and their characteristics are analyzed by the simulation results.