• Journal of Power Electronics
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• v.1 no.1
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• pp.56-64
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• 2001

This paper presents the switching angle and voltage for maximizing the torque or efficiency and minimizing torque ripple of an 8/6, SRM. The approximate analysis and computer simulation determine the switching angle and voltage by using SIMULINK$^\textregistered$. This is performed as a function of the speed and torque required by the load. From the results, new three facts can be known: First, the maximum torque depends on voltage and speed depends on switching angle. The others, the maximum efficiency and minimum torque ripple relay on switching angle. We control the switching angle and voltage of and asymmetrical inverter for the SRM with one-chip micro controller.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.10
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• pp.184-193
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• 2001

In vector control technique, stator currents of an induction motor are transformed to equivalent d-q currents in a reference frame consist of d and q axis, each of which is coincide with flux and torque direction respectively. Since the current in q-axis is related to the torque in a synchronously rotating frame, torque is estimated as a function of q-axis current and flux. In this paper, a method to estimate torque of an induction motor based on the measurement of 3-phase currents and rotating velocity of a rotor is presented. Graphic-programming is used to measure signals, to estimate the torque and to show the result in the form of user friendly graph in window environment. To stabilize the fluctuation of estimated torque caused from the small measurement error of the rotor velocity, the stator current is reconstructed in a program based on measured signals. The experimental results executed under the velocity of 500 rpm, 1500 rpm without load and 1500 rpm with load show that the proposed method estimates the torque very well.

• Proceedings of the KIPE Conference
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• 1997.07a
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• pp.177-181
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• 1997

In the speed control system of motors using the low resolution rotary encoder, the period of encoder pulse becomes longer than the sampling time for speed control in the range of very low speed. Therefore, it is difficult to obtain accurate speed information. In this paper, the speed estimating method at the very low speed region using reduced order torque observer, which has been widely used, is examined. The results of simulation show that the characteristics of the speed control at the very low speed region is improved by using the reduced order torque observer.

• Proceedings of the KIPE Conference
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• 1999.07a
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• pp.386-389
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• 1999

In this paper a Direct Torque Control(DTC) scheme for PWM three level inverter-fed induction motor drives, is presented and discussed. In orde to deal with DTC scheme applied three level inverter, the selection of voltage vector is proposed to minimize switching frequency and torque ripple. The simulation results shows a validity of the control scheme.

• Proceedings of the KIPE Conference
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• 2013.07a
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• pp.86-87
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• 2013

본 논문에서는 직접 토크 제어(Direct Torque Control, DTC) 방식을 이용한 매입형 영구자석 동기전동기(Interior Permanent Magnet Synchronous Motor, IPMSM)의 운전 영역을 자속 평면에서 분석하고, 약자속 제어를 포함한 전 운전 영역에서의 최대 토크 운전 기법을 제안하였다.

• Proceedings of the KIEE Conference
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• 1993.07b
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• pp.686-688
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• 1993

This paper proposes a robust speed control algorithm of Induction Motor. The main idea of this paper is to compensate the torque component of motor current with load torque observer and feedforward control. The speed response of the conventional PI controller is affected by variation of system parameters. However the proposed system has robust characteristics against the variation of system parameters. The simulation results and experiment prove the validity of proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1949-1954
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• 2005

One of control methods for underactuated manipulators is known as a switching control which selects a partially-stable controller using a prespecified switching rule. A switching computed torque control with a fuzzy energy region method was proposed. In this approach, some partly stable controllers are designed by the computed torque method, and a switching rule is based on fuzzy energy regions. Design parameters related to boundary curves of fuzzy energy regions are optimized offline by a genetic algorithm (GA). In this paper, we discuss on parameters obtained by GA. The effectiveness of the switching fuzzy energy method is demonstrated with some simulations.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.3
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• pp.150-157
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• 2002

This paper presents preliminarily an implementation of digital high-performance motion control system of Reluctance Synchronous Motor (RSM) drives with direct torque control (DTC). The system consist of stator flux observer, torque estimator, two hysteresis band controllers, an optimal switching look-up table, IGBT voltage source inverter, and TMS320F240 DSP controller made by Texas Instruments. The stator fluff observer is based on the combined voltage and current model with stator flux feedback adaptive control, and the input of the observer are the stator voltage and current of motor terminal for wide speed range. The rotor position and speed sensor used 6000 pulse/rev encoder. In order to prove rightness of the suggested control algorithm, we have some simulation and actual experimental system at $\pm$20 and $\pm$2000 rpm. The developed digitally high-performance motion control system+ are shown a good response characteristic of control results and high performance features using 1.0kW RSM which has 2.57 Ld/Lq salient ratio.

• Journal of Power Electronics
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• v.2 no.2
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• pp.146-153
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• 2002

this paper presents an implementation of digital control system of speed sensorless for Reluctance Synchronous Motor (RSM) drives with direct torque control (DTC). The problem of DTC for high-dynamic performance RSM drive is generating a nonlinear torque due to a saturated nonlinear inductance curve with various load currents. The control system consists of stator flux observer, compensating inductance look-up table, rotor position/speed/torque estimator, two hysteresis band controllers, an optimal switching look-up table, IGBT voltage source unverter, and TMS320C31 DSP controller. The stator flux observer is based on the combined voltage and current model with stator flux feedback adapitve control that inputs are the compensated inductances, current and voltage sensing of motor terminal with estimated rotor angle for wide speed range. The rotor position is estimated rotor speed is determined by differentiation of the rotor position used only in the current model part of the flux observer for a low speed operation area. It does not requrie the knowledge of any montor paramenters, nor particular care for moter starting, In order to prove the suggested control algorithm, we have simulation and testing at actual experimental system. The developed sensorless control system is showing a good speed control response characterisitic result and high performance features in 20/1500 rpm with 1.0Kw RSM having 2.57 ratio of d/q reluctance.

• 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.