• The Transactions of the Korean Institute of Electrical Engineers P
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• v.52 no.4
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• pp.161-166
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• 2003

This paper proposes a sensorless vector control of interior permanent magnet synchronous motor(IPMSM) using a reduced order observer. This method introduce the auxiliary control inputs that can eliminate the nonlinear term in the electrical equations and realize the linearization of the motor model. The rotor speed estimate with the observer that needs only the q-axis current. The rotor position calculate using the estimated rotor speed. The speed and position control implement with the estimated value. The validity of the proposed scheme is confirmed by various response characteristics.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.9
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• pp.1239-1246
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• 1995

A forced commutated cycloconverter (FCC) is a direct ac-ac converter capable of providing simultaneous voltage and frequency transformations. In this paper, vector control of an induction motor controlling stator current with forced commutated cycloconverter is presented. The advantage of current control is that the stator dynamics are eliminated and high performance vector control can be achieved. A novel modulation method based on dq transformation techniques is presented. Proposed modulation strategy generates the low frequency modulation function by the instantaneous value of the desired output voltages not by the steady state values of output magnitude and output frequency. PI control and predictive control algorithm for current control are applied, and the validity of proposed method is confirmed through digital simulations. Simulation results of step response and torque distubance and current control are presented.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.8
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• pp.500-508
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• 2004

This paper presents a new sensorless vector control system for high performance induction motor drives fed by a matrix converter with non-linearity compensation and disturbance observer. The nonlinear voltage distortion that is caused by commutation delay and on-state voltage drop in switching device is corrected by a new matrix converter modeling. The lumped disturbances such as parameter variation and load disturbance of the system are estimated by the radial basis function network (RBFN). An adaptive observer is also employed to bring better responses at the low speed operation. Experimental results are shown to illustrate the performance of the proposed system.

• Journal of Power Electronics
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• v.15 no.1
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• pp.106-115
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• 2015

This paper proposes a novel direct power control (DPC) strategy for neutral-point-clamped (NPC) three-level rectifiers, to directly control the active power, the reactive power and the neutral point potential of the rectifiers by referring to three pre-calculated vector influence tables and minimizing an objective function. In the three vector influence tables, the influences of different voltage vectors on the active power, the reactive power and the neutral-point potential are shown explicitly. A conceptual description and control algorithm of the proposed controller are presented in this paper. Then, numerical simulations and experiments are carried out to validate the proposed method. Both the simulation and experimental results show that good performances during both the steady-state and transient operating conditions are achieved. As a result, the proposed strategy has been proven to be effective for NPC three-level rectifiers.

• Proceedings of the KIPE Conference
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• 2015.07a
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• pp.383-384
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• 2015

This paper presents a new space vector modulation (SVM) method for indirect matrix converters (IMCs) to reduce commonmode voltage as well as minimize output current ripple in a high voltage transfer ratio. In the proposed SVM, the three-vector modulation scheme is used in the rectifier stage, while the nonzero state modulation technique, where the three nearest active vectors are selected to synthesize the desired output voltage, is applied to inverter stage to reduce the CMV. The proposed SVM method can significantly reduce the output current ripple and common-mode voltage of the IMC without any extra hardware. Simulated results are provided to demonstrate the effectiveness of the proposed SVM method.

• Bulletin of the Korean Chemical Society
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• v.21 no.12
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• pp.1227-1232
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• 2000

Near the conical intersection for the 1,2 $^{2}A'$ states of $H_3$ the derivative coupling vector is calculated and analyzed on the plane of internal coordinates, (U,V) or its polar coordinates $(S{\theta})$, based on the squares of the internuclear distances. It is shown that in the vicinity of the conical intersection the derivative coupling vector behaves like ${\theta}/2S$, which is responsible for the sign changes of the real-valued electronic wave function when the nuclear configuration traverses a closed path enclosing a conical intersection. The analytic property of the wave functions is studied and especially the observation of the sign change in the configuration state function (CSF) coefficients of the real-valued electronic wave functions is demonstrated.

• Journal of information and communication convergence engineering
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• v.17 no.1
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• pp.14-20
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• 2019

Currently, microarray gene expression data take advantage of the sufficient classification of cancers, which addresses the problems relating to cancer causes and treatment regimens. However, the sample size of gene expression data is often restricted, because the price of microarray technology on studies in humans is high. We propose enhancing the gene expression classification of support vector machines with generative adversarial networks (GAN-SVMs). A GAN that generates new data from original training datasets was implemented. The GAN was used in conjunction with nonlinear SVMs that efficiently classify gene expression data. Numerical test results on 20 low-sample-size and very high-dimensional microarray gene expression datasets from the Kent Ridge Biomedical and Array Expression repositories indicate that the model is more accurate than state-of-the-art classifying models.

• Journal of the Korean Mathematical Society
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• v.58 no.1
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• pp.109-122
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• 2021

In this paper, we consider the problem of finding the hypersurface Mn in the Euclidean (n + 1)-space ℝn+1 that satisfies an equation of mean curvature type, called singular minimal hypersurface equation. Such an equation physically characterizes the surfaces in the upper half-space ℝ+3 (u) with lowest gravity center, for a fixed unit vector u ∈ ℝ3. We first state that a singular minimal cylinder Mn in ℝn+1 is either a hyperplane or a α-catenary cylinder. It is also shown that this result remains true when Mn is a translation hypersurface and u is a horizantal vector. As a further application, we prove that a singular minimal translation graph in ℝ3 of the form z = f(x) + g(y + cx), c ∈ ℝ - {0}, with respect to a certain horizantal vector u is either a plane or a α-catenary cylinder.

• KIEE International Transactions on Power Engineering
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• v.2A no.3
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• pp.109-113
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• 2002

This paper addresses the issue of parameter error identification and estimation in electric power systems. Parameter error identification and estimation is carried out as a part of the state estimation. A two stage estimation procedure is used to detect and identify parameter errors. Suspected parameters are identified by the WLAV state estimator in the first stage. A new WLAV state estimator adding suspected system parameters in the state vector is used to estimate the exact values of parameters. Supporting examples are given by using the IEEE 14 bus system.

• The Journal of Korea Robotics Society
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• v.1 no.2
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• pp.107-116
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• 2006

We propose a planning algorithm to automatically generate a robust behavior plan (RBP) with which mobile robots can achieve their task goal from any initial states under dynamically changing environments. For this, task description space (TDS) is formulated, where a redundant task configuration space and simulation model of physical space are employed. Successful task episodes are collected, where $A^*$ algorithm is employed. Interesting TDS state vectors are extracted, where occurrence frequency is used. Clusters of TDS state vectors are found by using state transition tuples and features of state transition tuples. From these operations, characteristics of successfully performed tasks by a simulator are abstracted and generalized. Then, a robust behavior plan is constructed as an ordered tree structure, where nodes of the tree are represented by attentive TDS state vector of each cluster. The validity of our method is tested by real robot's experimentation for a box-pushing-into-a-goal task.