• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1998.10a
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• pp.13-18
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• 1998

The assessment of machined surface is difficult because the freeform surface must be evaluated by surface fairness as well as dimensional accuracy. In this paper, the methodology of freeform surface generation using measured data on the machine tool is presented. The reliability of measured points data is obtained by measuring error compensation. The compensated data are formulated through Non-uniform G-spline surface modeling. In order to improve the surface fairness, the generated model si smoothened by parameterization The validity and usefulness of the proposed method are examined through computer simulation and experiments on the machine tool.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.3
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• pp.253-257
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• 2010

The frequency is an important operation parameter for the control, protection, and stability of a power system. The frequency as a key index of power quality can be indicative of system abnormal conditions and disturbances. Due to the sudden change in generation and loads or faults in power system, the frequency is supposed to deviate from its nominal value. It is essential that the frequency must be maintained very close to its nominal frequency. An accurate monitoring of the power frequency is essential to optimal operation and prevention for wide area blackout. As most conventional frequency estimation schemes are based on DFT filter, it has been pointed out that the gain error could cause defects when the frequency is deviated from nominal value. This paper presents an advanced frequency estimation technique using gain compensation to improve the performance of DFT filter based techniques. To evaluate performance of the proposed algorithm, the 765kV T/L system in Korea is simulated by EMTP-RV software. The proposed technique can reduce the gain error caused when the power system frequency deviates from nominal value.

• Journal of Mechanical Science and Technology
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• v.14 no.11
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• pp.1198-1205
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• 2000

A two-degrees-of-freedom servosystem for step-type reference signals has been preposed, in which the integral compensation is effective only when there is a modeling error or a disturbance input. this paper considers robust stability of the servosystem incorporating an observer against both structured and unstructured uncertainties of the plant. A condition is obtained as a linear matrix inequality, under which the servosystem is robustly stable independently of the gain of the integral compensator. This result implies that we can tune the gain to achieve a desirable transient response of the servpsystem preserving robust stability. An example is presented to demonstrate that under the robust stability condition, the transient response can be improved by increasing the gain of the integral compensator.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.8
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• pp.757-764
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• 2015

Mathematical modeling of focal plane compensation device in the small earth-observation satellite camera has been conducted experimently for compensation of micro-vibration disturbance. The PZT actuators are used as control actuators for compensation device. It is quite difficult to build up mathematical model because of hysteresis characteristic of PZT actuators. Therefore, the compensation device system is assumed as a $2^{nd}$ order linear system and modeled by using MATLAB System Identification Toolbox. It has been found that four linear models of compensation device are needed to meet 10% error in the input frequency range of 0~50Hz. These models describe accurately the dynamics of compensation device in the 4 divided domains of the input frequency range of 0~50Hz, respectively. Micro-vibration disturbance can be compensated by feedback control strategy of switching four models appropriately according to the input frequency.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.7
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• pp.711-719
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• 2010

Heliostat, as a concentrator reflecting the incident solar energy to the receiver located at the tower, is the most important system in the tower-type solar thermal power plant, since it determines the efficiency and performance of solar thermal plower plant. Thus, a good sun tracking ability as well as its good optical property are required. In this paper, we propose a method to compensate the heliostat sun tracking error. We first model the sun tracking error, which could be measured using BCS (Beam Characterization System), by multilayered neural network. Then the extended Kalman filter was employed to train the neural network. Finally the model is used to compensate the sun tracking errors. Simulated result shows that the method proposed in this paper improve the heliostat sun tracking performance dramatically. It also shows that the training of neural network by the extended Kalman filter provides faster convergence property, more accurate estimation and higher measurement noise rejection ability compared with the other training methods like gradient descent method.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.2B no.3
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• pp.81-89
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• 2002

The sensorless AC motor drive is a popular topic of study due to the cost and reliability of speed and position sensors. Most sensorless algorithms are based on the mathematical modeling of motors including electrical variables such as phase current and voltage. Therefore, the accuracy of such variables largely affects the performance of the sensorless AC motor drive. However, the output voltage of the SVPWM-VSI, which is widely used in sensorless AC motor drives, has considerable errors. In particular, the SVPWM-VSI is error-prone in the low speed range because the constant DC link voltage causes poor resolution in a low output voltage command and the output voltage is distorted due to dead time and voltage drop. This paper investigates a novel high-performance strategy for overcoming these problems in a sensorless ac motor drive. In this paper, a variation of the DC link voltage and a direct compensation for dead time and voltage drop are proposed. The variable DC link voltage leads to an improved resolution of the inverter output voltage, especially in the motor's low speed range. The direct compensation for dead time and voltage drop directly calculates the duration of the switching voltage vector without the modification of the reference voltage and needs no additional circuits. In addition, the proposed strategy reduces a current ripple, which deteriorates the accuracy of a monitored current and causes torque ripple and additional loss. Simulation and experimentation have been performed to verify the proposed strategy.

• Journal of Electrical Engineering and Technology
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• v.3 no.1
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• pp.14-19
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• 2008

The paper presents an intelligent time series model to predict uncertain electricity market price in the deregulated industry environment. Since the price of electricity in a deregulated market is very volatile, it is difficult to estimate an accurate market price using historically observed data. The parameter of an intelligent time series model is obtained based on the simultaneous perturbation stochastic approximation (SPSA). The SPSA is flexible to use in high dimensional systems. Since prediction models have their modeling error, an error compensator is developed as compensation. The SPSA based intelligent model is applied to predict the electricity market price in the Pennsylvania-New Jersey-Maryland (PJM) electricity market.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.2
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• pp.178-184
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• 2002

This paper deals with the transfer alignment problem of SDINS(StrapDown Inertial Navigation System) subjected to roll and pitch motions of the ship. In order to reduce alignment errors induced by ship body flexure, a linearized error model for the velocity and attitude matching transfer alignment system is first derived by linearizing the nonlinear measurement equation with respect to the dominant y axis component and defining the flexure state of random constant type. And then a robust state estimation scheme is introduced to account for modeling uncertainty of the flexure. By interpreting the simulation results and comparing with the velocity and DCM(Direction Cosine Matrix) partial matching method, it is shown that the proposed method is effective enough to improve the azimuth alignment performance.

• Journal of the Korean Society for Precision Engineering
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• v.34 no.2
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• pp.125-131
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• 2017

2-Axis Pan and Tilt Motion Platform, a complex multivariate non-linear system, may incur any disturbance, thus requiring system controller with robustness against various disturbances. In this study, we designed an adaptive backstepping compensated controller by estimating the disturbance and error using the Radial Basis Function Neural Network (RBF NN). In this process, Uniformly Ultimately Bounded (UUB) was demonstrated via Lyapunov and stability was confirmed. By generating progressive disturbance to the irregular frequency and amplitude changes, it was verified for various environmental disturbances. In addition, by setting the RBF NN input vector to the minimum, the estimated disturbance compensation process was analyzed. Only two input vectors facilitated compensatory function of RBF NN via estimating the modeling and control error values as well as irregular disturbance; the application of the process resulted in improved backstepping controller performance that was confirmed through simulation.

• Journal of Drive and Control
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• v.17 no.2
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• pp.1-8
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• 2020

Recently, industrial systems are becoming quicker and lighter to enable the reduction of energy consumption and increase productivity. So the latest systems are more flexible and rapid than the previous systems. But, with this improvement, another problem has emerged, such as the increase in residual vibration when a system is started or stopped. The input shaper is a command generation method that can remove residual vibration. It can provide a solution to the problem of residual vibration in industrial systems. However, it is difficult to generate the input shaper in high order systems, such as a typical industrial system because the input shaper is induced from the system's vibration characteristics. This study focused on the extra insensitivity shaper that can compensate for the system's modeling error such as input dynamics, and the high order's system affection. A genetic algorithm was deployed to adjust a vibration limitation for the extra insensitivity of the input shaper. A plant is a low damping system that includes one zero and a pole. The fitness functions are an error signal of the system's response with normalized frequency variations. Verification of the suggested system is satisfied by comparison between the zero vibration derivative input shaper's response and the suggested one.