• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.1081-1083
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• 2003

In this paper, a new speed sensorless induction motor scheme which can work at any speed including the zero speed is presented. The proposed method is robust to secondary resistance variations. Simultaneous estimation of speed and secondary resistance are realized based on a feedforward type torque control scheme. The secondary flux with a low frequency sinusoidal waveform is used to help the estimation. Simulations results supported by experiments are given to show the effectiveness of this method.

• Structural Engineering and Mechanics
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• v.53 no.5
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• pp.939-956
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• 2015

In this study, in order to propose an efficient model to predict the torque capacity of steel fiber reinforced concrete (SFRC) beams, the existing experimental data related to torsional response of beams is reviewed. It is observed that existing data neglects the effects of some parameters on the variation of torque capacity. Thus, an experimental research was also conducted to obtain the effects of neglected parameters. In the experimental study, a total of seventeen SFRC beams are tested against torsion. The parameters considered in the experiments are concrete compressive strength, steel fiber aspect ratio, volumetric ratio of steel fibers and longitudinal reinforcement ratio. The effect of each parameter is discussed in terms of torque versus unit angle of twist graphs. The data obtained from this experimental research is also combined with the data got from previous studies and employed in artificial neural network (ANN) analysis to estimate the ultimate torque capacity of SFRC beams. In addition to parameters considered in the experiments, aspect ratio of beam cross-section, yield strengths of both transverse and longitudinal reinforcements, and transverse reinforcement ratio are also defined as parameters in ANN analysis due to their significant effects observed in previous studies. Assessment of the accuracy of ANN analysis in estimating the ultimate torque capacity of SFRC beams is performed by comparing the analytical and experimental results. Comparisons are conducted in terms of root mean square error (RMSE), mean absolute error (MAE) and coefficient of efficiency ($E_f$). The results of this study revealed that addition of steel fibers increases the ultimate torque capacity of reinforced concrete beams. It is also found that ANN is a powerful method and a feasible tool to estimate ultimate torque capacity of both normal and high strength concrete beams within the range of input parameters considered.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.6
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• pp.855-864
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• 2011

In this paper, a nonlinear controller based on adaptive back-stepping method is proposed for high performance operation of IPMSM(Interior Permanent Magnet Synchronous Motor). First, in order to improve the performance of speed tracking a nonlinear back-stepping controller is designed. Since it is difficult to control the high performance driving without considering parameter variation, a parameter estimator is included to adapt to the variation of load torque in real time. In addition, for the efficiency of power consumption of the motor, controller is designed to operate motor with minimum current for maximum torque. The proposed controller is applied through simulation to the a 2-hp IPMSM for the angular velocity reference tracking performance and load torque volatility estimation, and to test the MTPA(Maximum Torque per Ampere) operation in constant torque operation region. The result verifies the efficacy of the proposed controller.

• International Journal of Naval Architecture and Ocean Engineering
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• v.2 no.1
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• pp.24-33
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• 2010

Design of a Pump Jet Propulsor (PJP) was undertaken for an underwater body with axisymmetric configuration using axial/low compressor design techniques supported by Computational Fluid Dynamics (CFD) analysis for performance prediction. Experimental evaluation of the PJP was earned out through experiments in a Wind Tunnel Facility (WTF) using momentum defect principle for propulsive performance prior to proceeding with extensive experimental evaluation in towing tank and cavitation tunnel. Experiments were particularly conducted with respect to Self Propulsion Point (SPP), residual torque and thrust characteristics over a range of vehicle advance ratio in order to ascertain whether sufficient thrust is developed at the design condition with least possible imbalance torque left out due to residual swirl in the slip stream. Pumpjet and body models were developed for the propulsion tests using Aluminum alloy forged material. Tests were conducted from 0 m/s to 30 m/s at four rotational speeds of the PJP. SPP was determined confirming the thrust development capability of PJP. Estimation of residual torque was carried out at SPP corresponding to speeds of 15, 20 and 25 m/s to examine the effectiveness of the stator. Estimation of thrust and residual torque was also carried out at wind speeds 0 and 6 m/s for PJP RPMs corresponding to self propulsion tests to study the propulsion characteristics during the launch of the vehicle m water where advance ratios are close to Zero. These results are essential to assess the thrust performance at very low advance ratios to accelerate the body and to control the body during initial stages. This technique has turned out to be very useful and economical method for quick assessment of overall performance of the propulsor and generation of exhaustive fluid dynamic data to validate CFD techniques employed.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1617-1620
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• 2005

The current control for interior permanent magnet machines is more complicate than surface permanent magnet machine because of its torque characteristic depending on the reluctance. For high performance torque control, it requires state decoupling between the d-current and q-current dynamics. However the variation of the inductances, which couples the state dynamics of the currents, makes the state decoupling difficult. So some decoupling methods have developed to cope this variations and each current can be regulated independently. This paper presents a novel approach for fully decoupling the states cross-coupling using parameter adaptation. The adaptation method is based on the error between reference currents and the currents with state decoupling which have to follow the references. This method is more object-oriented than the other online parameter estimation methods in IPM machine and other electrical machines

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.196-203
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• 2010

2DOF is applied to induction moor in order to supply these weak points of PI torque control method in this paper. and The proposed method utilize the combination of the voltage model based on stator equivalent model and the current model based on rotor equivalent model, which enables stable estimation of rotor flux. To prove the propriety of this paper, the various simulations carried out adequacy and stability using Matlab, and at the same time real system is made, so it is proved. As the results of embodying the system, the robust system is realized.

• Proceedings of the KIEE Conference
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• summer
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• pp.1085-1087
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• 2004

The space harmonic analysis, as an analytical method, is used to estimate the flux distribution in the air gap of the brushless motors in this paper. With the flux distribution, back-emf and torque characteristics can be estimated.[1-7] Therefore, the air gap flux distribution of surface type permanent magnet motor according to the motor specifications are studied to estimate the torque characteristics in this paper. To validate the analysis result of this method, 2-dimensional finite element analysis is performed and the air gap flux density is compared to that from space harmonic analysis.

• Journal of Power Electronics
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• v.10 no.4
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• pp.396-404
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• 2010

This paper presents simple schemes used to estimate the initial rotor position and the d- and q-axis inductances for effective Maximum Torque per Ampere (MTPA) operation in a wind-power system using an IPMSM (Interior Permanent Magnet Synchronous Machine). An IPMSM essentially requires an exact coordinate transformation and accurate inductance values to use a reluctance torque caused by the saliency characteristic. In the proposed high-frequency voltage testing method, there is no voltage drop caused by the resistance and the electromotive force. The initial rotor position and the inductance can be measured through an analysis of the stator current without turning the rotor. The experimental results are presented in order to illustrate the feasibility of the proposed method.

• The Transactions of the Korean Institute of Power Electronics
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• v.18 no.3
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• pp.289-295
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• 2013

It is important to know exact values of Interior Permanent Magnet Synchronous Motors(IPMSM)' parameters such as stator resistance and inductance in order to have their high performance. This paper proposes a novel motor parameter(stator resistance, d&q axis inductance) estimation algorithm for IPMSM. The proposed estimation method utilizes back-EMF equations and model reference adaptive system(MRAS). The algorithm using back-EMF estimates d and q axis inductances in the constant torque region, and the stator resistance is estimated by using MRAS with the estimated inductance regardless of speed regions. The validity of the proposed algorithm is verified by simulations and experiments.