• 대한수학회지
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• 제31권3호
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• pp.339-352
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• 1994

A sumbanifold M of a quaternionic Kaehlerian manifold $\tilde{M}^m$ of real dimension 4m is called a generic submanifold if the normal space N(M) of M is always mapped into the tangent space T(M) under the action of the quaternionic Kaehlerian structure tensors of the ambient manifold at the same time.The purpose of the present paper is to study generic submanifold of quaternionic Kaehlerian manifold of constant Q-sectional curvature with nonvanishing parallel mean curvature vector. In section 1, we state general formulas on generic submanifolds of a quaternionic Kaehlerian manifold of constant Q-sectional curvature. Section 2 is devoted to the study generic submanifolds with nonvanishing parallel mean curvature vector and compute the restricted Laplacian for the second fundamental form in the direction of the mean curvature vector. As applications of those results, in section 3, we prove our main theorems. In this paper, the dimension of a manifold will always indicate its real dimension.

• Journal of Power Electronics
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• 제12권2호
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• pp.285-293
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• 2012

Multilevel inverters have gained attention in high-power applications due to their numerous advantages in comparison with conventional two-level inverters. In this paper a simplified Space-Vector Modulation (SVM) algorithm for a three-level Neutral-Point Clamped (NPC) inverter is implemented on a Freescale$^{(R)}$ DSP56F8037. The algorithm is based on a simplification of the space-vector diagram for a three-level inverter so that it can be used with a two-level inverter. Once the simplification has been achieved, calculation of the dwell times and the switching sequences are carried out in the same way as for the two-level SVM method. Details of the hardware design are included. Experimental results are analyzed to validate the performance of the simplified algorithm.

• 한국정밀공학회지
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• 제22권2호
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• pp.70-78
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• 2005

In this paper, a novel rotor flux estimation method of an induction motor using support vector regression(SVR) is presented. Two well-known different flux models with respect to voltage and current are necessary to estimate the rotor flux of an induction motor. Training of SVR which the theory of the SVR algorithm leads to a quadratic programming(QP) problem. The proposed SVR rotor flux estimator guarantees the improvement of performance in the transient and steady state in spite of parameter variation circumstance. The validity and the usefulness of proposed algorithm are throughly verified through numerical simulation.

• Journal of Power Electronics
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• 제11권6호
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• pp.846-855
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• 2011

This paper proposes a control mode switching scheme between vector control and constant V/f control for induction machine (IM) drives for maximum torque utilization in a higher speed region. For the constant V/f scheme, a smooth transition method from the linear range of PWM up to the six-step mode is applied, by which the machine flux and torque can be kept constant in a high-speed range. Also, a careful consideration of the initial phase angle of the voltage in the transient state of the control mode change between the vector control and V/f schemes is described. The validity of the proposed strategy is verified by the experiment result for a 3-kW induction motor drives.

• 전기학회논문지P
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• 제53권2호
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• pp.51-57
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• 2004

Vector control schemes are used in inverter-fed induction motor drives to obtain high performance. Crucial to the success of the vector control scheme is the knowledge of the instantaneous position of the rotor flux. However, the position of the rotor flux change with temperature and magnetic saturation of the motor. This variation cause deterioration of both steady state and dynamic operation of the motor drives. Performance degradation is in the form of input-output torque nonlinearity and saturation of the motor. Analytic expressions are derived to evaluate the effects due to parameter sensitivity. Also, dynamic response is shown by speed command with the variation of stator and rotor resistance.

• East Asian mathematical journal
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• 제37권3호
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• pp.333-354
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• 2021

A support vector machine (SVM) is a state-of-the-art machine learning model rooted in structural risk minimization. SVM is underestimated with regards to its application to real world problems because of the difficulties associated with its use. We aim at showing that the performance of SVM highly depends on which kernel function to use. To achieve these, after providing a summary of support vector machines and kernel function, we constructed experiments with various benchmark datasets to compare the performance of various kernel functions. For evaluating the performance of SVM, the F1-score and its Standard Deviation with 10-cross validation was used. Furthermore, we used taylor diagrams to reveal the difference between kernels. Finally, we provided Python codes for all our experiments to enable re-implementation of the experiments.

• Journal of Electrical Engineering and Technology
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• 제12권5호
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• pp.1821-1834
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• 2017

Medium voltage control applications due to obtain better output voltage and reduced electro-magnetic interference multi level inverter is used. In closed loop control with inverter, the PI controller does not operate satisfactorily when the operating point changes. This paper presents the performance of Co-Efficient diagram PI controller based indirect vector controlled induction motor drive fed from three-level inverter under different operating conditions (dynamic and steady state). The proposed Co-Efficient diagram PI controller based three level inverter significantly reduces the torque ripple compared to that of conventional PI controller. The performance of the indirect vector controlled induction motor drive has been simulated at different operating conditions. For three-level inverter control, a simplified space vector modulation technique is implemented, which reduces the coordinate transformations complications in the algorithms. The performance parameters, torque ripple contents and THD of induction motor drive with three-level inverter is compared under different operating conditions using CDM-PI and conventional PI controllers.

• Journal of Electrical Engineering and Technology
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• 제10권3호
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• pp.1058-1065
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• 2015

This paper present a current predicting control method for PMSM (permanent magnet synchronous motor) to improve the tracking performance of stator current, which regards the current vector as the control target. Solving the model state equation in the static frame (α-β frame), the dynamic change of current vector will be gained as three independent terms. These change terms, which contain the prediction of current vector, are discretized and simplified by Taylor series expansion and used to get the voltage vector as the predictive control quantity. SVPWM will transform the control voltage to the switching signal of inverter, which is newly deduced for the current vector. Simulation and experiment results are given to testy and verify the performance of this method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.1084-1085
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• 2007

This paper presents a vector control implementation for SPMSM(Surface-mounted Permanent Magnet Synchronous Motor) using dSPACE 1104 system and MATLAB/SIMULINK. SPMSM can be treated as a DC motor provided that currents of flux and torque component are controlled independently using vector control. Therefore various control algorithms for conventional DC motor control can be adopted to SPMSM. The system is designed to improve set-point tracking capability, fast response, and accuracy. In This paper, d-q equivalent modeling of PMSM is derived based on vector control theory. The PI controller is used for speed control and state feedback PI current control method is used for current control. For the implementation of high performance vector control system, dSPACE 1104 system is used. Simulations and experiments were carried out to examine validity of the proposed vector control implementation.

• Bulletin of the Korean Chemical Society
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• 제14권1호
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• pp.21-29
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• 1993

For the study of relaxation processes in complex spin system, a general master equation, which can be used to simulate a vast range of pulse experiments, has been formulated using the Liouville representation of quantum mechanics. The state of a nonequilibrium spin system in magnetic field is described by a density vector in Liouville space and the time evolution of the system is followed by the application of a linear master operator to the density vector in this Liouville space. In this master equation the nuclear spin relaxation due to intramolecular dipolar interaction or randomly fluctuating field interaction is explicitly implemented as a relaxation supermatrix for a strong coupled two-spin (1/2) system. The whole dynamic information inherent in the spin system is thus contained in the density vector and the master operator. The radiofrequency pulses are applied in the same space by corresponding unitary rotational supertransformations of the density vector. If the resulting FID is analytically Fourier transformed, it is possible to represent the final nonstationary spectrum using a frequency dependent spectral vector and intensity determining shape vector. The overall algorithm including relaxation interactions is then translated into an ANSIFORTRAN computer program, which can simulate a variety of two dimensional spectra. Furthermore a new strategy is tested by simulation of multiple quantum signals to differentiate the two relaxation interaction types.