• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.324-327
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• 1994

In this paper, a new design method of variable structure model following control system(VSMFCS) for robot manipulators is proposed. The proposed controller overcomed reaching phase problem by using function augmenting scheme to the sliding surface. Therefore, it can be guaranteed that the overall system always has a robust property against parameter variations and external disturbances. Furthermore, the proposed controller does not use the model state, .chi.$_{m}$, different from other previous works. Regardless of not using the model state, the model following error dynamics, virtual dynamics, is shown to be globally exponentially stable. The efficiency of the proposed method has been demonstrated by an example.e.

• Journal of the Korea Convergence Society
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• v.2 no.1
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• pp.15-20
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• 2011

There are various remedies that are proposed from aspects of education and social welfare for social integration of multi-cultural families which is different from ethnic and cultural background. This study proposed educational process model for information literacy education of multi-cultural children. The proposed model is consedered to reduce digital divide by using five factor from the earlier information literacy. At last, this study explained characteristics, objective, contents, teaching-learning method and estimating method of proposed model.

• International Journal of Concrete Structures and Materials
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• v.10 no.1
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• pp.99-112
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• 2016

During earthquake, reinforced concrete walls show complicated post-yield behavior varying with shear span-to-depth ratio, re-bar detail, and loading condition. In the present study, a macro-model for the nonlinear analysis of multi-story wall structures was developed. To conveniently describe the coupled flexure-compression and shear responses, a reinforced concrete wall was idealized with longitudinal and diagonal uniaxial elements. Simplified cyclic material models were used to describe the cyclic behavior of concrete and re-bars. For verification, the proposed method was applied to various existing test specimens of isolated and coupled walls. The results showed that the predictions agreed well with the test results including the load-carrying capacity, deformation capacity, and failure mode. Further the proposed model was applied to an existing wall structure tested on a shaking table. Three-dimensional nonlinear time history analyses using the proposed model were performed for the test specimen. The time history responses of the proposed method agreed with the test results including the lateral displacements and base shear.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.396-399
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• 1999

In this paper, the efficient HW/SW co-simulation method which selects the ISA model dynamically is proposed. Because the ISA models with only fixed accuracy have been used in previous co-simulation environment, it may result in bad performance in speed or accuracy. In the proposed method, the cycle accurate ISA model is used in the case that the states of the detailed system are to be inspected. In other case, instruction-based model is executed in order to accelerate the simulation speed. The proposed dynamic model selection can be done by setting the conversion point in the application code before the simulation starts. The experiment on the embedded RISC processor have been performed, and its result shows that the proposed method is more efficient than the case of using fixed ISA model.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.6
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• pp.722-728
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• 1998

In this paper real-time estimation methods for identifying the tire-road friction coefficient are presented. Taking advantage of the Magic Formula Tire Model, the similarity technique and the specific model for the vehicle dynamics, a reduced order observer/filtered-regressor-based method is proposed. The Proposed method is evaluated on simulations of a full-vehicle model with an eight state nonlinear vehicle/transmission model and nonlinear suspension model. It has been shown through simulations that it is possible to estimate the tire-road friction from measurements of engine rpm, transmission output speed and wheel speeds using the proposed identification method. The proposed method can be used as a useful option as a part of vehicle collision warning/avoidance systems and will be useful in the implementation of a warning algorithm since the tire-road friction can be estimated only using RPM sensors.

• Proceedings of the KWS Conference
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• 2005.11a
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• pp.201-203
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• 2005

A kinetic model for particle coarsening behavior in the weld heat affected zone (HAZ) was proposed. Unlike the conventional approach, where the mean-sized particle is considered to grow continuously, the proposed model considered the critical particle size which can be derived from the Gibbs-Thomson equation. In this study, the proposed particle coarsening model was applied to study the behavior of (Ti, Nb )(C, N) complex particle in the weld HAZ. The predicted particle size distributions using the proposed model were in agreement with the experimental results.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.267-270
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• 1997

In this paper, we proposed an optimazation method using Genetic Algorithm for nonlinear system modeling. Fuzzy Neural Network(FNNs) was used as basic model of nonlinear system. FNNs was fused of Fuzzy Inference which has linguistic property and Neural Network which has learning ability and high tolerence level. This paper, We used FNNs which was proposed by Yamakawa. The FNNs was composed Simple Inference and Error Back Propagation Algorithm. To obtain optimal model, parameter of membership function, learning rate and momentum coefficient of FNNs are tuned using genetic algorithm. And we used simplex algorithm additionaly to overcome limit of genetic algorithm. For the purpose of evaluation of proposed method, we applied proposed method to traffic choice process and waste water treatment process, and then obtained more precise model than other previous optimization methods and objective model.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1471-1474
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• 2002

In this paper, we propose a robust indirect adaptive fuzzy state feedback regulator based on Takagi-Sugeno fuzzy model. The proposed adaptive fuzzy regulator is less sensitive to singularity than the conventional one based on the feedback linearization method. Furthermore, the proposed control method is applicable to not only plants with a perfect model but also plants with an imperfect model, which causes uncertainties. We verify the global stability of the proposed method by using Lyapunov method. In order to support the achievement, the application of the proposed adaptive fuzzy regulator to the control of a nonlinear system under the external disturbance is presented and the performance was verified by some simulation result.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.3
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• pp.439-444
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• 2016

The method for extracting the SPICE model parameter of Schottky diode under DC forward bias is proposed. A method for improving the accuracy of the SPICE model parameter at various temperatures is proposed. Three analysis steps according to the magnitude of the current is used in order to extract the parameters effectively. At each analysis step, initial parameters are calculated by using the current-voltage equations and the Levenberg-Marquardt analysis is proceeded. To verify the validity of the proposed method, the SPICE model parameters for the BAT45 and FSV1045 under DC forward bias is extracted. Schottky diode currents obtained from the proposed method shows the average relative error of 6.1% and 9% compared with the measured data for the BAT45 and FSV1045 sample at various temperatures.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3004-3006
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• 2000

In this paper, we propose an optimal design method of Fuzzy-Neural Networks model with parallel structure for complex and nonlinear systems. The proposed model is consists of a multiple number of FNN connected in parallel. The proposed FNNs with parallel structure is based on Yamakawa's FNN and it uses simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rules. We use a HCM clustering and GAs to identify the structure and the parameters of the proposed model. Also, a performance index with a weighting factor is presented to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model. we use the time series data for gas furnace and the numerical data of nonlinear function.