• Journal of Korea Water Resources Association
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• v.44 no.3
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• pp.209-220
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• 2011

Input uncertainty is one of the major sources of uncertainty in hydrologic modeling. In this paper, first, three alternate rainfall inputs generated by different interpolation schemes were used to see the impact on a distributed watershed model. Later, the residuals of precipitation interpolations were tested as a source of ensemble streamflow generation in two river basins in the U.S. Using the Monte Carlo parameter search, the relationship between input and parameter uncertainty was also categorized to see sensitivity of the parameters to input differences. This analysis is useful not only to find the parameters that need more attention but also to transfer parameters calibrated for station measurement to the simulation using different inputs such as downscaled data from weather generator outputs. Input ensembles that preserves local statistical characteristics are used to generate streamflow ensembles hindcast, and showed that the ensemble sets are capturing the observed steamflow properly. This procedure is especially important to consider input uncertainties in the simulation of streamflow forecast.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.24.1-24
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• 1996

The development of future aircraft that involves the expanded flight envelop will place increased performance requirements on the design of the flight control system. Maneuvering areas are expanding into flight envelopes characterized by significantly larger levels of modeling uncertainty than encountered in present flight control designs. Conventional flight control techniques that ignore the effects of large parameter variations, modeling uncertainties and nonlinearities, will likely produce designs with poor performance and robustness. Recent advances in modern control theories called advanced control theories, most notably the H$\_$.inf./ synthesis technique, adaptive control and neural network application, offer the promise of a design technique that can produce both high performance and robust controllers for next generation aircraft. This special lecture will survey the recent development in advanced flight control and review the possible application of advanced control theories.

• Journal of Power System Engineering
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• v.9 no.4
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• pp.175-180
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• 2005

Incorrections between model and plant are parameter, system order uncertainties and modeling error due to disturbance like friction. Therefore to achieve a good tracking performance, adaptive discrete time sliding mode tracking controller is used under time-varying desired position. Based on the diophantine equation, a new discrete time sliding function is defined and utilized for the control law. Robustness is increased by using both a recursive least-square method and a sliding function-based nonlinear feedback. The effectiveness of the proposed control algorithm is proved by the results of simulation and experiment.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.7
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• pp.785-790
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• 2011

The goal of this study is to estimate the force acting on the knee joint in the human body by using the Hilltype muscle model based on a musculoskeletal model of the human lower extremity in the sagittal plane. For estimating the force applied, the human leg is modeled using multi-body modeling. This leg model comprises biarticular muscles acting on two joints of the upper and lower limbs, and the muscles include some of the major muscles such as the hamstring. In order to analyze the uncertainty of the applied forces acting on the knee joint, statistical distributions of human body, leg part, parameters are required and to obtain the parameter's statistical characteristic of the part sample survey method is employed. Finally, by using the sensitivity information of the parameters, the force acting on the knee joint can be estimated.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.1
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• pp.79-87
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• 2017

The microphysical processes of the numerical weather prediction (NWP) model cover the following : fall speed, accretion, autoconversion, droplet size distribution, etc. However, the microphysical processes and parameters have a significant degree of uncertainty. Parameter estimation was generally used to reduce errors in NWP models associated with uncertainty. In this study, the micro- genetic algorithm and harmony search algorithm were used as an optimization algorithm for estimating parameters. And we estimate parameters of microphysics for the Unified model in the case of precipitation in Korea. The differences which occurred during the optimization process were due to different characteristics of the two algorithms. The micro-genetic algorithm converged to about 1.033 after 440 times. The harmony search algorithm converged to about 1.031 after 60 times. It shows that the harmony search algorithm estimated optimal parameters more quickly than the micro-genetic algorithm. Therefore, if you need to search for the optimal parameter within a faster time in the NWP model optimization problem with large calculation cost, the harmony search algorithm is more suitable.

• Journal of Korea Water Resources Association
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• v.49 no.5
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• pp.411-422
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• 2016

Rainfall-runoff modeling in conjunction with rainfall frequency analysis has been widely used for estimating design floods in South Korea. However, uncertainties associated with underlying distribution and sampling error have not been properly addressed. This study applied a Bayesian method to quantify the uncertainties in the rainfall frequency analysis along with Gumbel distribution. For a purpose of comparison, a probability weighted moment (PWM) was employed to estimate confidence interval. The uncertainties associated with design rainfalls were quantitatively assessed using both Bayesian and PWM methods. The results showed that the uncertainty ranges with PWM are larger than those with Bayesian approach. In addition, the Bayesian approach was able to effectively represent asymmetric feature of underlying distribution; whereas the PWM resulted in symmetric confidence interval due to the normal approximation. The use of long period data provided better results leading to the reduction of uncertainty in both methods, and the Bayesian approach showed better performance in terms of the reduction of the uncertainty.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.3
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• pp.65-72
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• 2001

Generally, it is said that control of the inertia system is to track the reference input quickly while suppressing the vibration due to the system itself. In this case, the difficulty fur designing a controller is caused by modeling uncertainty and parameter variation. The purpose of this paper is to propose a design method to suppress the vibration of three-mass inertia system based on the LMI theory. That is, the generalized plant model by which we can cope with conservativeness of the existing H$_{*}$ theory is proposed and analyzed in terms of LMI. The results of simulation fur the three-mass inertia system show that the proposed design approach is quite effective under the given situations.

• 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 Korea Water Resources Association
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• v.44 no.9
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• pp.711-720
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• 2011

SWAT (Soil and Water Assessment Tool) model was calibrated for the flow rate of the Deachung lake with a large area of 3108.29 $km^2$. Application of SWAT model requires significant number of input data and is prone to result in uncertainties due to errors in input data, model structure and model parameters. The SUFI-2 (Sequential Uncertainty Fitting Ver. 2) program and GLUE (Generalized Likelihood Uncertainty Estimation) program in SWAT-CUP (SWAT-Calibration and Uncertainty Program) are used to select the best parameters for SWAT model. Optimal combination of parameter values was determined through 2,000 iterative SWAT model runs. The Nash-Sutcliffe values and $R^2$ values were 0.87 and 0.89 respectively indicating both methods show good agreements with observed data successfully. RMSE and MSE values also showed similar results for both programs. It seems the SWAT-CUP has a great practical appeal for parameter optimization especially for large basin area and it also can be used for less experienced SWAT model users.

• Computers and Concrete
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• v.23 no.2
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• pp.145-153
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• 2019

Adaptive schemes are constructed in this paper for modeling the effective chloride diffusion coefficient of cement-based materials (paste and concrete). Based on the polarization approximations for the effective conductivity of isotropic multicomponent materials, we develop some fitting procedures to include more information about the materials, to improve the accuracy of the scheme. The variable reference parameter of the approximation involves a few free scalars, which are determined through the available numerical or experimental values of the macroscopic chloride diffusion coefficient of cement paste or concrete at some volume proportions of the component materials. The various factors that affect the chloride diffusivity of cement-based material (porous material structure, uncertainty of value of the chloride diffusion coefficient in water-saturated pore spaces, etc.) may be accounted to make the predictions more accurate. Illustrations of applications are provided in a number of examples to show the usefulness of the approach.