• Proceedings of the KIEE Conference
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• 2001.04a
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• pp.250-253
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• 2001

This paper is proposed a sinusoidal input voltage Multi-level AC-DC Converter using transformer. In this paper Multi-level PWM Control converter which controls input current by combining buck Converters together to improve input current characteristic, and confirmed its validity throughout simulation and experiment. This method, which is multiplying and duplicating output of converter of equal capacity, is able to control unit power factor of input current, reduce the problem caused by high frequency switching, and apply to high power converter because filter is not necessary.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.530-535
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• 2004

This paper considers a state set estimation (SSE) based model predictive control (MPC) for linear parameter- varying (LPV) systems with input constraint. We estimate, at each time instant, a feasible set of all states which are consistent with system model, measurements and a priori information, rather than the state itself. By combining a state-feedback MPC and an SSE, we design an SSE-based MPC algorithm that stabilizes the closed-loop system. The proposed algorithm is solved by semi-de�nite program involving linear matrix inequalities. A numerical example is included to illustrate the performance of the proposed algorithm.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.11
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• pp.156-163
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• 1997

Recently, the three phase AC to DC boost converter has become one of the most widely used power converters as DC power source in the industry applications. In this paepr, a three phase PWM AC toDC boost converter that operates with unity power factor and sinusodial input currents is presented. The current control of the converter is based onthe predicted current control strategy with fixed switching frequency and the input current tracks the reference cuent within one sampling time interval. Therefore, by using this control strategy low ripples in the output voltage, low harmonics in the input current and fast dynamic responses are achieved with a small capacitance in the DC link.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.1242-1244
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• 2000

A new control method using average comparison strategy have been proposed in this paper. This control method realizes sinusoidal input and output current. unity input displacement factor regardless of load power factor. Moreover, compensation of the asymmetrical and/or harmonic containing input voltage is automatically realized, and calculation time of control function is reduced.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2693-2695
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• 2000

Generally, neural networks can be used efficiently for the identification and control of nonlinear dynamical system, then it always needs to learn in order that the output values is closed to desired values. But, if plant input to control is limited to certain bounded values, former learning rules has the another problem. This paper demonstrates algorithm to control the bounded-input plant using neural network controller.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.6
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• pp.582-587
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• 1997

This paper deals with the control problem under nonlinear boiler systems with noise, and input constraints. MCMBPC(Multivariable Constrained Model-Based Predictive Controller) proposed by Wilkinson et al.[10,11] is used and nominal model is modified in this paper in order to applied to nonlinear boiler systems with feed-forward terms. The solution of the cost function optimization constrained on input and/or output variables is achieved using quadratic programming, via singular value decomposition(SVD). The controller designed is shown to satisfy the constraints and to have excellent tracking performance via simulation applied to nonlinear dynamic drum boiler turbine model for 16OMW unit.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.597-600
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• 1997

In this paper, the authors propose a new method for linearizing a nonlinear dynamical system by use of polynomial compensation. In this method, an M-sequence is applied to the nonlinear system and the crosscorrelation function between the input and the output gives us every crosssections of Volterra kernels of the nonlinear system up to 3rd order. We construct a polynomial compensation function from comparison between lst order Volterra kernel and high order kernels. The polynomial compensation function is, in this case, of third order whose coefficients are variable depending on the amplitude of the input signal. Once we can get compensation function of nonlinear system, we can construct a linearization scheme of the nonlinear system. That is. the effect of second and third order Volterra kernels are subtracted from the output, thus we obtain a sort of linearized output. The authors applied this method to a saturation-type nonlinear system by simulation, and the results show good agreement with the theoretical considerations.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.26 no.4
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• pp.402-409
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• 2017

Selection of optimal cutting conditions is important for improving productivity and implementing efficient process control in metal machining. In this study, improvement of cutting conditions in machining using end-mills is studied by using deep-layered neural networks, which comprise an input layer, output layer, and two hidden layers. System networks are designed with inputs as cutting conditions, and they output the cutting force. A pseudo-inverse network is designed that has the adjustable cutting condition as output and cutting force and other cutting conditions as input. The combination of the system network and pseudo-inverse network enables selection or improvement of cutting conditions that results in the expected cutting force.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.11
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• pp.1736-1742
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• 1989

In this thesis, to verify input-output characteristics of GaAs MESFET, light is illuminated to C-band oscillator which already designed and manufactured, thus input-output variation of GaAs MESFET is to be shown. Experimental results of two kinds of optical effects, optical tuning and opticla switching, of GaAs MESFET Oscillators are presented. For optical tuning, the Oscillation frequency decreases with optical illumination and the Oscillator power output generally increases with optical illumination, the increase being around 1 to 3 dBm at 1mW/mm\ulcornerlight intensity. While the DC-lingt illuminated Oscillator response data provide information of the optical senditivity of GaAs-MESFET Oscillators. Pulse-light illuminated transient response data can be invoked to understand the detailed optical-electrical interaction mechanisms response. Thus, it is shown that direct control of micro-devices is realisable, if we use optical effect of GaAs semiconductor compound.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.139.3-139
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• 2001

The free-model concept is introduced as an alternative intelligent system technique to design a controller with input and output data only. The idea of free model comes from the Taylor series approximation, where an output can be estimated when such data as position, velocity, and acceleration are known. The parameters in the free model can be estimated using the input-output data and a controller can be designed based on the free model. The free model thus developed is shown to be controllable, observable, and robust. The accuracy of the free-model approximation can be improved by increasing the observation window and the order of the free model. The LQR method is applied to the free model to design power system stabilizers ...