• The KIPS Transactions:PartB
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• v.8B no.6
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• pp.693-698
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• 2001

Noisy data are often fitted using a smoothing parameter, controlling the importance of two objectives that are opposite to a certain extent. One of these two is smoothness and the other is closeness to the input data. The optimal value of this parameter minimizes the error of the result. This optimum cannot be found exactly, simply because the exact data are unknown. This paper propose the threshold value for noise reduction based on wavelet-thresholding. In the proposed method PSNR results show that the threshold value performs excellently in comparison with conventional methods without knowing the noise variance and volume of signal.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1838-1842
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• 2004

Gain and phase margins of a first order plus delayed time (FOPDT) process controlled by generalized predictive controller (GPC) are related to the control parameters ${\lambda}$ (control move suppression parameter) and ${\alpha}$ (smoothing filter coefficient) and the normalized delay of the process. Variation ranges of gain and phase margins are determined. It is shown that the margins cannot be assigned independently for a wide range of variation and the range is narrowing by increase of the normalized delay of the process. And finally curves are given to use for adjustment of the controller parameters in order to obtain a specific pair of gain and phase margins.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.936-941
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• 2004

An Optimal Feedforward Integral Variable Structure or FIVSC approach for an electrohydraulic position servo control system is presented in this paper. The FIVSC algorithm combines feedforward strategy and integral in the conventional Variable Structure Control (VSC) and calculating the control function to guarantee the existence of a sliding mode. Furthermore, the chattering in the control signal is suppressed by replacing the sign function in the control function with a smoothing function. The simulation results illustrate that the purposed approach gives a significant improvement on the tracking performances when compared with some existing control methods, like the IVSC and MIVSC strategies. Simulation results illustrate that the purposed approach can achieve a zero steady state error for ramp input and has an optimal motion with respect to a quadratic performance index. Moreover, Its can achieve accurate servo tracking in the presence of plant parameter variation and external load disturbances.

• International Journal of Automotive Technology
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• v.8 no.4
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• pp.467-476
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• 2007

This work verifies the chaotic motion of a steer-by-wire vehicle dynamic system, and then elucidates an application of dither smoothing to control the chaos of a vehicle model. The largest Lyapunov exponent is estimated from the synchronization to identify periodic and chaotic motions. Then, a bifurcation diagram reveals complex nonlinear behaviors over a range of parameter values. Finally, a method for controlling a chaotic vehicle dynamic system is proposed. This method involves applying another external input, called a dither signal, to the system. The designed controller is demonstrated to work quite well for nonlinear systems in achieving robust stability and protecting the vehicle from slip or spin. Some simulation results are presented to establish the feasibility of the proposed method.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.8
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• pp.193-200
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• 2001

Recently, the concrete floor finishing robot, which can be used for flattening and smoothing the concrete floor, has been developed in Korea and Japan. While the previous research assumes that the concrete floor is deformable and the trowel is rigid in modeling the concrete floor finisher, we assume that the concrete floor is rigid and the trowel is deformable. Based on this assumption, we derived the equations of motion and found the convergent velocity of the concrete floor finisher using the computer simulation. From these results, we can understand the relationship between the motion characteristics and the design and control parameter of the robot.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.12
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• pp.2271-2282
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• 2006

This paper is concerned with simulation issues arising in the PDE-based image restoration such as the total variation minimization(TVM) and its generalizations. In particular, we study the issues of staircasing and excessive dissipation of TVM-like smoothing operators. A strategy of scaling the algebraic system and a non-convex minimization are considered respectively for anti-staircasing and anti-diffusion. Furthermore, we introduce a variable constraint parameter to better preserve image edges. The resulting algorithm has been numerically verified to be efficient and reliable in denoising. Various numerical results are shown to confirm the claim.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1998.04a
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• pp.115-123
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• 1998

A $Si_3N_4$ tappet shim was devdoped in a direct OHC engine for the friction reduction of valve train system that contributes significantly to the engine friction in real driving condition. For commercializing $Si_3N_4$ tappet shim, it is important to reduce the machining cost. Therefore we analytically and experimentally figure out the optimum condition. Using ceramic tappet shims machined with different surface roughness, the effects of roughness on the friction loss were analyzed in view of the lubrication behavior. From this results it is shown that the friction torque of valve train system quickly drops at a certain surface roughness of ceramic tappet shim and its value remains constant despite further smoothing.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.542-549
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• 2004

The compressive strength of concrete is commonly used criterion in producing concrete. However, the tests on the compressive strength are complicated and time-consuming. More importantly, it is too late to make improvement even if the test result does not satisfy the required strength, since the test is usually performed at the 28th day after the placement of concrete at the construction site. Therefore, accurate and realistic strength estimation before the placement of concrete is being highly required. In this study, the estimation of the compressive strength of concrete was performed by probabilistic neural network (PNN) on the basis of concrete mix proportions. The estimation performance of PNN was improved by considering the correlation between input data and targeted output value. Adaptive probabilistic neural network (APNN) was proposed to automatically calculate the smoothing parameter in the conventional PNN by using the scheme of dynamic decay adjustment algorithm. The conventional PNN and APNN were applied to predict the compressive strength of concrete using actual test data of a concrete company. APNN showed better results than the conventional PNN in predicting the compressive strength of concrete.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.10
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• pp.1738-1747
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• 2003

Smoothed Particle Hydrodynamics (SPH), a pure Lagrangian numerical method, is applied to analysis of penetration phenomenon of bumper plate which is installed outside of spacecraft hull to protect the spacecraft against hypervelocity meteorite impact. Effects of SPH parameters, such as artificial viscosities, smoothing lengths, numbers of particles and time increments, are analysed by comparing the SPH simulation results with experimental ones with regard to subsequent formation of debris cloud. An optimum range of parameter values is determined by error analysis and various SPH numerical results are compared with experiments.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.167-170
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• 2003

We develop semiparametric methods for matched case-control studies using regression splines. Three methods are developed: an approximate crossvalidation scheme to estimate the smoothing parameter inherent in regression splines, as well as Monte Carlo Expectation Maximization (MCEM) and Bayesian methods to fit the regression spline model. We compare the approximate cross-validation approach, MCEM and Bayesian approaches using simulation, showing that they appear approximately equally efficient, with the approximate cross-validation method being computationally the most convenient. An example from equine epidemiology that motivated the work is used to demonstrate our approaches.