• Journal of Power Electronics
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• v.19 no.1
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• pp.254-264
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• 2019

This paper proposes an indirect current control technique based on a proportional resonant (PR) approach for the seamless mode transfer of utility interactive inverters. Direct-current and voltage hybrid control methods have been used for inverter control under grid-connected and islanded modes. A large bandwidth can be selected due to the structure of single-loop control. However, this results in poor dynamic transients due to sudden changes of the controller during mode changes. Therefore, inverter control based on indirect current is proposed to improve the dynamic transients by consistently controlling the output voltage under all of the operation modes. A PR-based indirect current control topology is used in this study to maintain the load voltage quality under all of the modes. The design processes of the PR-based triple loop are analyzed in detail while considering the system stability and dynamic transients. The mode transfer techniques are described in detail for both sudden unintentional islanding and islanded mode voltage quality improvements. In addition, they are described using the proposed indirect control structure. The proposed method is verified by the PSiM simulations and laboratory-scale VDER-HILS experiments.

• Journal of Mechanical Science and Technology
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• v.20 no.7
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• pp.950-960
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• 2006

An output time delay always exists in practical systems. Analysis of the delay phenomenon in a continuous-time domain is sophisticated. It is appropriate to obtain its corresponding discrete-time model for implementation via a digital computer. A new method for the discretization of nonlinear systems using Taylor series expansion and the zero-order hold assumption is proposed in this paper. This method is applied to the sampled-data representation of a nonlinear system with a constant output time-delay. In particular, the effect of the time-discretization method on key properties of nonlinear control systems, such as equilibrium properties and asymptotic stability, is examined. In addition, 'hybrid' discretization schemes resulting from a combination of the 'scaling and squaring' technique with the Taylor method are also proposed, especially under conditions of very low sampling rates. A performance of the proposed method is evaluated using two nonlinear systems with time-delay output.

• Journal of Aerospace System Engineering
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• v.18 no.3
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• pp.48-55
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• 2024

In recent years, as the commercialization of unmanned aerial vehicles (UAVs) has been actively promoted, much attention has been focused on developing a technology to ensure the safety of UAVs. In general, the UAV has the potential to enter an uncontrollable state caused by sudden maneuvers, disturbances, and pilot error. To prevent entering an uncontrolled situation, it is essential to predict the flight state of the UAV. In this paper, we propose a flight state prediction technique based on an improved CNN-LSTM hybrid mode to enhance the flight state prediction performance. Simulation results show that the proposed prediction technique offers better state prediction performance than the existing prediction technique, and can be operated in real-time in an on-board environment.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.11
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• pp.206-212
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• 2000

This paper presents a hybrid actuator scheme to actively control the end-point position and vibration of a two-link flexible robot arm. Control scheme consists of four different actuators; two servo-motors at the hubs and two piezoceramics bonded to the surfaces of the flexible links. Two sliding hyperplanes are designed for two servo-motors which have time varying parameters to maintain control performance in any configuration. The surface gradients of the hyperplanes are determined by pole assignment technique to guarantee the stability on the hyperplanes themselves. During the motion, undesirable oscillations caused by the torques based on the rigid link dynamics are actively suppressed by applying feedback control voltages to the piezoceramic actuators. Consequently, desired tip motion is achieved. In order to demonstrate the effectiveness of the proposed methodology, experiments are performed for the regulating and tracking control problems.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.181-188
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• 2014

Heterogeneous physical systems and computational devices are incorporated on a large-scale in a CPS (cyber-physical system) environment. Simulations can be useful for the reliable behaviors of CPSs. Time synchronization is one of major technical issues for the simulations. In the CPS, distributed systems control themselves by interacting with each other during runtime. When some simulation models have high complexity, wrong control commands as well as incorrect data can be exchanged due to the time error. We propose a time synchronization algorithm for the hybrid model that has characteristics of both continuous time systems and discrete event systems. In addition, we develop a CPS simulator based on our algorithm. For the verification of the algorithm and the execution of the simulator, we develop an example hybrid model and simulate considering user controls as well as interactions among the distributed systems.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2007.11a
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• pp.313-318
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• 2007

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 fuzzy neural network controller and artificial neural network(ANN). This control method is applicable over the entire speed range which 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 Adaptive-FNN controller and ANN controller. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper reposes speed control of IPMSM using Adaptive-FNN and estimation of speed using 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 a lied to IPMSM drive system controlled Adaptive-FNN and ANN controller, 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-FNN and ANN controller.

• Journal of the Korean earth science society
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• v.36 no.1
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• pp.109-124
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• 2015

A novel approach, hybrid surface rainfall (KNU-HSR) technique developed by Kyungpook Natinal University, was utilized for improving the radar rainfall estimation. The KNU-HSR technique estimates radar rainfall at a 2D hybrid surface consistings of the lowest radar bins that is immune to ground clutter contaminations and significant beam blockage. Two HSR techniques, static and dynamic HSRs, were compared and evaluated in this study. Static HSR technique utilizes beam blockage map and ground clutter map to yield the hybrid surface whereas dynamic HSR technique additionally applies quality index map that are derived from the fuzzy logic algorithm for a quality control in real time. The performances of two HSRs were evaluated by correlation coefficient (CORR), total ratio (RATIO), mean bias (BIAS), normalized standard deviation (NSD), and mean relative error (MRE) for ten rain cases. Dynamic HSR (CORR=0.88, BIAS= $-0.24mm\;hr^{-1}$, NSD=0.41, MRE=37.6%) shows better performances than static HSR without correction of reflectivity calibration bias (CORR=0.87, BIAS= $-2.94mm\;hr^{-1}$, NSD=0.76, MRE=58.4%) for all skill scores. Dynamic HSR technique overestimates surface rainfall at near range whereas it underestimates rainfall at far ranges due to the effects of beam broadening and increasing the radar beam height. In terms of NSD and MRE, dynamic HSR shows the best results regardless of the distance from radar. Static HSR significantly overestimates a surface rainfall at weaker rainfall intensity. However, RATIO of dynamic HSR remains almost 1.0 for all ranges of rainfall intensity. After correcting system bias of reflectivity, NSD and MRE of dynamic HSR are improved by about 20 and 15%, respectively.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.8 s.101
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• pp.911-917
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• 2005

There were many attempts to reduce noise behind the noise barrier using active control techniques. Omoto(1993) Shao(1997) and Yang(2001) tried to actively control the diffracted noise behind the barrier and main concerns were about the arrangement methods for the control sources. Baek (2004) tried to get better results using the simulated annealing method and the sequential searching technique. The main goal of this study is to develop and compare the performance of several optimization techniques including those mentioned above, hybrid version of simulated annealing and genetic algorithm for the optimal control source positions of active noise barrier system. The simulation results show fairly similar performance lot the small size of searching problem. However, as the number of control sources are increased, the performance of simulated annealing algorithm and genetic algorithm are better than the others. Simulations are also made to show the performance of the selected optimal control source positions not only at the receiver position but at the surrounding volume of the receiver position and plotted the noise reduction level in 3-D.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.12
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• pp.1864-1871
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• 2012

This paper proposes the hybrid proportional integral(HBPI) controller for maximum power point tracking(MPPT) control of photovoltaic system. The output characteristics of the solar cell are a nonlinear and affected by a temperature, the solar radiation and influence of a shadow. The MPPT control is a very important technique in order to increase an output and efficiency of the photovoltaic system. The conventional constant voltage(CV), perturbation and observation(PO) and incremental conductance(IC) are the method which finding maximum power point(MPP) by the continued self-excitation vibration, and uses the fixed step size. If the fixed step size is a large, the tracking speed of maximum power point is faster, but the tracking accuracy in the steady state is decreased. On the contrary, when the fixed step size is a small, the tracking accuracy is increased and the tracking speed is slower. Therefore, in order to solve these problems, this paper proposes HBPI controller that is adjusted gain of conventional PI control using fuzzy control, and the maximum power point tracks using this controller. The validity of the controller proposed in this paper proves through the results of the comparisons.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2007.11a
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• pp.307-312
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• 2007

The paper is proposed artificial neural network(ANN) sensorless control of induction motor drive with fuzzy learning control-fuzzy neural network(FLC-FNN) controller. 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 induction motor using FLC-FNN and estimation of speed using 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 proposed control algorithm is applied to induction motor drive system controlled FLC-FNN and ANN controller, Also, this paper is proposed the analysis results to verify the effectiveness of the FLC-FNN and ANN controller.