• Proceedings of the KSME Conference
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• 2005.11a
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• pp.194.1-194.1
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• 2005

• Journal of the Korean Society for Precision Engineering
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• v.25 no.12
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• pp.89-99
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• 2008

In this paper, the position tracking control problem of the servo system with nonlinear dynamic friction is issued. The nonlinear dynamic friction contains a directly immeasurable friction state variable and the uncertainty caused by incomplete parameter modeling and its variations. In order to provide the efficient solution to these control problems, we propose the composite control scheme, which consists of the robust friction state observer, the FNN approximator and the approximation error estimator with sliding mode control. In first, the sliding mode controller and the robust friction state observer is designed to estimate the unknown internal state of the LuGre friction model. Next, the FNN estimator is adopted to approximate the unknown lumped friction uncertainty. Finally, the adaptive approximation error estimator is designed to compensate the approximation error of the FNN estimator. Some simulations and experiments on the servo system assembled with ball-screw and DC servo motor are presented. Results show the remarkable performance of the proposed control scheme. The robust friction state observer can successfully identify immeasurable friction state and the FNN estimator and adaptive approximation error estimator give the robustness to the proposed control scheme against the uncertainty of the friction parameters.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.1
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• pp.90-102
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• 2009

In this paper, a tracking control problem for a mechanical servo system with nonlinear dynamic friction is treated. The nonlinear friction model contains directly immeasurable friction state and the uncertainty caused by incomplete modeling and variations of its parameter. In order to provide the efficient solution to these control problems, we propose a hybrid control scheme, which consists of a robust friction state observer, a RFNN estimator and an approximation error estimator with sliding mode control. A sliding mode controller and a robust friction state observer is firstly designed to estimate the unknown infernal state of the LuGre friction model. Next, a RFNN estimator is introduced to approximate the unknown lumped friction uncertainty. Finally, an adaptive approximation error estimator is designed to compensate the approximation error of the RFNN estimator. Some simulations and experiments on the mechanical servo system composed of ball-screw and DC servo motor are presented. Results demonstrate the remarkable performance of the proposed control scheme.

• Journal of the Korean Institute of Gas
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• v.4 no.3 s.11
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• pp.46-52
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• 2000

In order to evaluate the risk assessment of Fireball, a program, FIRESTOR, was developed. With this program, thermal fluxes due to the fireball of propane and n-butane were predicted to analyze the damage of Puchen gas explosion accident and thermal fluxes compared with the BLEVE ESTIMATOR, and commercial program SAFER Dupont Co. Thermal fluxes with variation of distance from the explosion source by BLEVE ESTIMATOR, SAFER and FIRESTOR was made a comparative analysis each other for the constant pressure of propane and n-butane. The values calculated by FIRESTOR were between those by BLEVE ESTIMATOR and SAFER. Consequently FIRESTOR is proved to be an good program to analyze the damage of Fireball.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.7 no.3
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• pp.132-136
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• 2014

We introduce a new architecture of TSK-based fuzzy inference system. The proposed model used fuzzy c-means clustering method(FCM) for efficient disposal of data. The premise part of fuzzy rules don't assume any membership function such as triangular, gaussian, ellipsoidal because we construct the premise part of fuzzy rules using FCM. As a result, we can reduce to architecture of model. In this paper, we are able to use four types of polynomials as consequence part of fuzzy rules such as simplified, linear, quadratic, modified quadratic. Weighed Least Square Estimator are used to estimates the coefficients of polynomial. The proposed model is evaluated with the use of Boston housing data called Machine Learning dataset.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.7
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• pp.573-581
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• 2014

We proposed a hopping phase estimator to demodulate the received signals without any hopping information in frequency hopping spread spectrum systems. The demodulation process in this paper is as follows: hopped frequency tracking is accomplished by choosing a frequency component with maximum amplitude after taking discrete Fourier transform and a hopping frequency estimator which estimates the phase generated by hopped frequency is established through difference product and down-sampling. We obtained the probability density function and variance performance of the proposed estimator and confirmed that the analysis and the simulation results were agreed with each other.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.14 no.2
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• pp.155-163
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• 1989

For a one link flexible arm control, quadratic optimal control is applied to the dynamic modilling which is derived from an assumed mode method. For the quadratic optimal control technique, the full state feedback must be obtained for closing the control loop, but because some of the states in the flexible system(e.g. the rate of change of the time dependent variables of the mode shapes) can not be directly measured, state estimator is necessary to achieve the practical implementation of the optimal controller. When disturbances and measurement noise occur, stochastic approach must be applied to estimating the states of the system. Kalman Filter is used as a stste estimator. Through the simulation, the flexible system with state estimator is compared with the flexible system assuming that all the states can be measured.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2082-2084
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• 2003

A practical real-time LOS rate estimator is proposed to handle the time-varying measurement noise statistics. To calculate the optimal Kalman gain, the algebraic transformation method is taken into account. By using the algebraic transformation, the differential algebraic Riccati equation(DARE) regarding estimation error covariance is replaced by the simple algebraic Riccati equation(ARE). The proposed LOS estimation filter gain is only a function of relative range. Consequently, the proposed method is computationally very efficient and suitable for embedded environment.

• Proceedings of the KIPE Conference
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• 2007.11a
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• pp.7-10
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• 2007

The current model based sensorless method has many benefits that it can be robust control for large load torque. However, this method should determine a coefficient of back electro motive force(back-emf). This coefficient is varied by load torque and speed. Also, the coefficient determining equation is not exist, so it is determined only by experiment. On the other hands, using only back-emf estimatior method can not drive in low speed area and it has weakness in load variation. For these problems, this paper suggests the hybrid sensorless method that mixes the back-emf estimator regarding saliency and the current based sensorless model. This estimator offers not only non-necessary coefficient for current sensorless model, but also wide speed area operating in no specific transition method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.9 no.2
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• pp.85-93
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• 1984

This paper, with the linear multivariable systems as a model, proposes a method of evaluating the Kalman gain of the state estimator according to the shifting of poles in the system. The stochasic probability of the process and measurement noise is assumed to be identical to the stationary process. The proposed method, based on the diagonalized system, is easy to implement computationally if the correspondence between the poles of the estimator and the response of the system can be determined. Finally several examples are given to confirm and illustrate proposed method derived here.