• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1165-1168
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• 2002

This paper presents a neural network based self-tuning fuzzy PID control scheme with variable learning rate for sensorless vector controlled induction motor drives. MRAS(Model Reference Adaptive System) is used for rotor speed estimation. When induction motor is continuously used long time. its electrical and mechanical parameters will change, which degrade the performance of PID controller considerably. This paper re-analyzes the fuzzy controller as conventional PID controller structure, introduces a single neuron with a back-propagation learning algorithm to tune the control parameters, and proposes a variable learning rate to improve the control performance. The proposed scheme is simple in structure and computational burden is small. The simulation using Matlab/Simulink and the experiment using DS1102 board show the robustness of the proposed controller to parameter variations.

• Proceedings of the KIPE Conference
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• 1997.07a
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• pp.357-363
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• 1997

The windup phenomenon appears and results in the performance degradation when the PI controller output is saturated. A new anti-windup PI controller is proposed to improve the control performance of the variable-speed motor drives and it is experimentally applied to the speed control of a vector-controlled induction motor driven by a pulse width modulated(PWM) voltage source inverter (VSI). The integral state is separately controlled corresponding to whether the PI controller output is saturated or not. The experimental results show that the speed response has the much improved performances such as small overshoot and fast settling time over the conventional anti-windup technique. Although the operating speed command is changed, the similar control performance can be obtained by using the PI gains selected in the linear region.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.53 no.4
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• pp.195-200
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• 2004

Many kinds of speed sensorless control system of induction motor had been developed. But it is difficult to implement at the real system because of complex algorithm and equations. This paper investigates a novel speed sensorless control of induction motor using neural networks. The proposed control strategy is based on neural networks using stator current and output of neural model based on state observer. The errors between the stator current and the output of neural model are back-propagated to adjust the rotor speed, so that adaptive state variable will coincide with the desired state variable. This algorithm may overcome several shortages of conventional model, such as integrator problems, small EMF at low speed and relatively large sensitivity of stator resistance variation. Also, this paper presents a newly developed optimal equation about the momentum constant and the learning rate. The proposed algorithms are verified through simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.8
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• pp.1502-1509
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• 2011

This Paper presents characteristic analysis in terms of interior permanent magnet synchronous motor for electric vehicle propulsion using numerical analysis. Torque ripple analysis, thermal analysis, demagnetization analysis of permanent magnet and mechanical stress analysis with variable operating condition are presented. According to these characteristic analysis, both the performance of motor and possible problems during the operation are examined thoroughly in advance.

• Proceedings of the KIEE Conference
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• 1992.07b
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• pp.1221-1224
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• 1992

To obtain a robustness which is one of important characteristics needed in servo drive, the sliding mode control method is used as a control strategy. However, the undesired phenomenon of chattering is a serious problem. In this paper, an adaptive chattering alleviation algorithm for variable structure system control is proposed to solve this serious problem. Digital controller using the theory of chattering alleviation control is applied to the position control problem of an induction motor system. Comparisons of this algorithm with other variable structure system control algorithms indicate that the chattering can be alleviated. This controller is implemented using IBM-PC(8088 CPU) which controls current controlled PWM inverter consisted of IGBT as a switching device to drive motor.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.2
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• pp.49-56
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• 2008

In order to reduce energy consumption, secondary controlled system has been applied to many types of equipments. In lifting equipments or press machines using hydraulic cylinder, a hydraulic transformer is used as a control component instead of a valve for motion control and a component for recovering potential energy of load. The transformer is a combination of a variable displacement pump/motor as a secondary controlled element and a fixed displacement pump/motor. In this paper the effect of transformer is studied. Multiple closed loop controllers with displacement feedback of variable pump/motor, speed feedback and position feedback of cylinder are used. The efficiency and energy consumption when cylinder is driven up and down is calculated by simulation. Simulation results show that considerable energy saving is achieved by choosing load ratio, circuit type and supply pressure.

• Proceedings of the KAIS Fall Conference
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• 2011.12b
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• pp.385-388
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• 2011

This study is about development of remote controlled bollard using the BLDC motor mechatronics theory. A bollard is composed of the sensor part and the control part. The sensor part is consisted of sensors that detect the locations of a bollard. The role of the control part are adjusting motor speed and power through variable resistance. In order to confirm required performance, The speed of decent and ascent of the bollard, the time and the RPM of BLDC motor were tested according to the variable resistance and the load.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.10
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• pp.690-696
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• 2004

This paper is proposed a hybrid intelligent controller based on the vector controlled surface permanent magnet synchronous motor(SPMSM) drive system. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of SPMSM using neural network-fuzzy(NNF) control and speed estimation 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 error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.6
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• pp.719-727
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• 1999

A robust position control method of the BLDC motor using a new sliding mode control strategy is presented. The main property of variable structure system(VSS) is that the system response is robust and insensitive to parameter variations and external disturbances in the sliding mode. When using the conventional VSS, generally the reaching phase problem occurs, which cause the system response to be sensitive to parameter variations and external disturbances. Furthermore, the speed of response is relatively slow because the swithching surface is a linear function. In order to overcome these problems, VSS with nonlinear sliding surface eliminating reaching phase is proposed. The validity of the proposed scheme is shown by results of simulations of simulations and experiments for the BLDC motor with variable load.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.1
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• pp.58-69
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• 2016

This paper describes the design and implementation of a new diode clamped multilevel inverter for variable frequency drive. The diode clamp multilevel inverter has been widely used for low power, high voltage applications due to its superior performance. However, it has some limitations such as increased number of switching devices and complex PWM control. In this paper, a new topology is proposed. New topology requires only (N-1) switching devices and (N-3) clamping diodes compared to existing topology. A modified APO-PWM control method is used to generate gate pulses for inverter. The proposed inverter topology is coupled with single phase induction motor and its performance is tested by MATLAB simulation. Finally, a prototype model has built and its performance is tested with single phase variable frequency drive.