• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.22-27
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• 1989

In this paper influences of disturbances and Modeling errors are qualitatively for the linear approximation model of turret servo system, and then LQG/LTR Control theory is applied to linear approximation model in order to design a controller which satisfies robustneas/stability for the modeling errors. Finally the performance and robustness of designed controller for the given plant are verified through the simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.39-39
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• 2000

In this paper, a decoupler of tandem cold rolling mill is designed. Before designing the decoupler, this paper improved conventional linear model by considering friction and yield stress of rolling strip. In a stand, the decoupler let an output be controlled by an input. And even if states of other stands should be changed, current stand takes no interference from those changes. In addition, with the same method, a feedforward controller is designed for an input strip thickness error. Finally, performance of controllers above is shown with nonlinear simulation.

• Environmental Engineering Research
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• v.16 no.3
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• pp.113-119
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• 2011

This study traces the origin, evolution, and current state-of-the-art of engineering-oriented water-quality management and modeling. Three attributes of polluted water underlie human concerns for water quality: rubbish (aesthetic impairment), stink (ecosystem impairment), and death (public health impairment). The historical roots of both modern environmental engineering and water-quality modeling are traced to the late nineteenth and early twentieth centuries when European and American engineers worked to control and manage urban wastewater. The subsequent evolution of water-quality modeling can be divided into four stages related to dissolved oxygen (1925-1960), computerization (1960-1970), eutrophication (1970-1977) and toxic substances (1977-1990). Current efforts to integrate these stages into unified holistic frameworks are described. The role of water-quality management and modeling for developing economies is outlined.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.8
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• pp.935-944
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• 2015

This study performs the dynamic modeling and the simulation of variable speed wind power system and implements the models of wind speed, wind turbine & PMSG, and MPPT & pitch control as well. The simulation of wind turbine was performed by using the power coefficient and other simulation parameters which were extracted with reference to the commercial 5MW class wind turbine data. As the result of this simulation, MPPT control is confirmed, maintaining the maximum power coefficient as far as the rated speed 12[m/s]. Over 12[m/s] wind speed, this wind power system makes it possible to keep the stable output by controlling the pitch angle.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2016.05a
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• pp.76-77
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• 2016

This paper presents an automated construction quality nonconformity control method. Existing quality control process are confined attributed to the dependence on human quality personnels. They are inefficiency for continuos quality improvements and may cause project schedule delays when any nonconformity is handled timely fashion. For sure, It is important to identify the add hoc quality nonconformity control processes and to implement them into an automated system that controls its' work-flow. It would be desirable to develop the construction project quality nonconformity control system using Building information modeling(BIM) and Information and Communications Technologies(ICT). It may provide an effective platform to prevent quality issues that exist in the existing quality management practice.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.227-233
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• 1996

The Inverted Pendulum has been one of most popular nonlinear dynamic systems for the exploration of control techniques. This paper presents a new linear optimal control techniques and nonlinear neural network learning methods. The multiayered neural networks are used to add nonlinear effects on the linear optimal regulator(LQR). The new regulator can compensate nonlinear system uncertainties that are not considered in the LQR design, and can tolerated a wider range of uncertainties than the LQR alone. The new regulator has two neural networks for modeling and control. The neural network for modeling is used to obtain a more accurate model than the given mathematical equations. The neural network for control is used to overcome deficiencies by adding corrections to the linear coefficients of the LQR and by adding nonlinear effects on the LQR. Computer simulations are performed to show the applicability and a more robust regulator than the LQR alone.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.3
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• pp.107-118
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• 1998

Two-phase neuro-system identification method is presented. The 1$^{st}$-phase identification uses conventional neural network mapping for modeling an input-output system. The 2$^{nd}$ -phase modeling is also performed sequentially using the 1$^{st}$-phase modeling errors. In the 2$^{nd}$ a phase modeling, newly generated input signals, which are obtained by summing the 1st-phase modeling error and artificially generated uniform series, are utilized as system's I-O mapping elements. The 1$^{st}$-phase identification is interpreted as a “Real Model” system identification because it uses system's real data(i.e., observations and control inputs) while the 2$^{nd}$ -phase identification as a “Artificial Model” identification because of using artificial data. Experimental results are given to verify that the two-phase neuro-system identification could reduce the overall modeling errors.rrors.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.76.6-76
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• 2002

Introduction. Modeling. Controller. Simulation. Experiment. Conclusion

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.1
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• pp.23-31
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• 1997

The sway control problem of pendulum motion of a container hanging on a Portainer Crane, which transports containers from a container ship to trucks, is considered in the paper. The equations of motion are obtained through the Lagrange mechanics and simplified for control purposes. Considering that the fast traveling of trolley and no residual swing motion of the container at the end of acceleration and deceleration are crucial for quick transportation, several velocity patterns of trolley movement including the time-optimal control are investigated. Incorporating the change of rope length, a reference swing trajectory is introduced in the control loop and the error signal between the reference sway angle and the measured sway angle is feedbacked. Proposed control strategy is shown to be robust to disturbances like winds and initial sway motion.

• Journal of Advanced Marine Engineering and Technology
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• v.27 no.7
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• pp.862-871
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• 2003

In this paper, we addressed a modeling for the magnetic levitation stage. This planar magnetic levitator employs four permanent magnet liner motors. Each motor generates vertical force for suspension against gravity, as well as horizontal force for propulsion. Therefore. this stage can generate six degrees of freedom motion by the combination of forces. We derived a mechanical dynamics equation using Lagrangian method and electromechanical dynamics equation by using Co-energy method. Based on the derived dynamics, we can analyze the stage motion that is subject to the input currents and forces.