• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.111-114
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• 1996

This paper proposes a robust control method using Universal Learning Network(U.L.N.) and second order derivatives of U.L.N.. Robust control considered here is defined as follows. Even if external input (equal to reference input in this paper) to the system at control stage changes awfully from that at learning stage, the system can be controlled so as to maintain a good performance. In order to realize such a robust control, a new term concerning the perturbation is added to a usual criterion function. And parameter variables are adjusted so as to minimize the above mentioned criterion function using the second order derivative of the criterion function with respect to the parameters.

• Bulletin of the Korean Chemical Society
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• v.15 no.6
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• pp.488-496
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• 1994

An approximate nonlinear theory of the Oregonator model is obtained with the aid of an ordinary perturbation method when the system is perturbed by some kinds of external input. The effects of internal and external parameters on the oscillations are discussed in detail by taking specific values of the parameters. A simple approximate solution for the Oregonator model under the influence of a constant input is obtained and the result is compared with the numerical result. For other types of external inputs the approximate solutions up to the fourth order expansion are compared with the numerical results. For a periodic input, we found that the entrainment depends crucially on the difference between the internal and external frequencies near the bifurcation point.

• Bulletin of the Korean Chemical Society
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• v.12 no.4
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• pp.383-387
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• 1991

A new perturbation theory called as star expansion method is used to obtain the nonlinear retarded solution of the Schlogl models with some kinds of external input. The approximate nonlinear solutions are compared with the exact solution, linear solutions, and those obtained by the Feynman method.

• Bulletin of the Korean Chemical Society
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• v.13 no.5
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• pp.560-565
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• 1992

A new perturbation theory called the star expansion method is used to obtain an approximate nonlinear solution of the Lotka-Volterra model under the influence of some kinds of external input. The effects of nonlinearity, amplitude and frequency of the external input on the chemical oscillations in the model are evaluated by taking specific values for the model parameters, and the results are discussed in detail.

• Journal of Power System Engineering
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• v.17 no.3
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• pp.82-88
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• 2013

For commercialized servo drives of the motion stage to include embedded controller, external terminal is provided for tracking command and encoder output, but internal terminal is not for control input. Thus, it is difficult to combine out signal of embedded controller with that of external compensator such as disturbance observer. In this study, for precise tracking control of motion stage without hardware change of the servo drive, tacking control system is composed of an inner loop of servo drive and an outer loop of disturbance observer. Then, the control system is designed so that the output response of actual plant corresponds with nominal model's in transient state as well as in steady state. Finally, the experiment results show that the designed control system is effective to reconcile actual plant behavior with nominal model under nonlinear friction and parameter perturbation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.5
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• pp.779-787
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• 2001

The multi degree of freedom system using magnetic levitation has been implemented successfully. Differently from another noncontact systems, the developed system was focused on the maximization of the system stiffness under the constraint of a limited input. The variation of a relative adopting point between the magnetic pair, its location on the fixed base, and the selection of optimal specifications for the main active magnetic elements give us another chance to realize the increased robustness against external disturbances with the less control inputs. In this paper, the overall development procedures are given including the optimal design, the dynamic modeling, the various control tests, and the main issues to be solved.

• Journal of the Korea institute for structural maintenance and inspection
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• v.11 no.1
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• pp.141-152
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• 2007

Considering uncertainties of random input data, it is more reasonable to use probabilistic method than the conventional deterministic method for the design of structures or for the assessment of the responses of structures, which are designed as safe even under extreme loads. Therefore, to assess the quantitative effects of the constructed cable stayed bridge by the input random variables, a sensitivity analysis is studied. Using perturbation method, an analysis program is developed for the iterative probabilistic finite element analyses and sensitivity analyses of the cable stayed bridge, except the initial shape analysis. Monte-Carlo Simulations were used for the verification of the developed program. The results of sensitivity analysis shows the governing effects of external loads. Because the results also provide the sensitive effects of the stiffness of members and the magnitudes of prestressing force of cables, the developed

• The Journal of Korean Institute of Information Technology
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• v.17 no.9
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• pp.19-30
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• 2019

Photovoltaic power generation requires MPPT algorithm to track stable and efficient maximum power output power point according to external changes such as solar radiation and temperature. This study implemented a model that could track MPP more quickly than original MPPT algorithm using artificial neural network. The proposed model finds the current and voltage of MPP using the original MPPT algorithm for various combinations of insolation and temperature for training data of artificial neural networks. The acquired MPP data was learned using the input node as insolation and temperature and the output node as the current and voltage. The Experiment results show tracking time of the original algorithms P&O, InC and Fuzzy were respectively 0.428t, 0.49t and 0.4076t for the 0t~0.3t range, and MPP tracking time of the proposed model was 0.32511t and it is 0.1t faster than the original algorithms.