• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.162-166
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• 2009

In this paper, we propose a novel approach of an acoustic echo cancellation (AEC) algorithm which is differently adopted in the relevant period condition by the suppression parameter of a parametric wiener filter (PWF). The PWF uses the suppression parameter to compensate uncertainty of acoustic echo signal estimation. The existing PWF method using the fixed suppression parameter derives the distortion of the near-end signal at the double-talk. To solve this problem, the boundary condition is devised using decision of the double-talk detection (DTD) algorithm and voice activity detector (VAD). The boundary condition makes it possible to treat differently depending on the case of the single-talk and double-talk. According to the experimental results, the proposed approach is found to be effective for acoustic echo cancellation using the boundary condition.

• Journal of Drive and Control
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• v.17 no.1
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• pp.13-20
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• 2020

Adaptive neural networks based lateral controller is presented to guarantee path following performance for vehicle lane keeping in the presence of parameter time-varying characteristics of the vehicle lateral dynamics due to the road surface condition, load distribution, tire pressure and so on. The proposed adaptive controller could compensate vehicle lateral dynamics deviated from nominal dynamics resulting from parameter variations by incorporating it with neural networks that have the ability to approximate any given nonlinear function by adjusting weighting matrices. The controller is derived by using Lyapunov-based approach, which provides adaptive update rules for weighting matrices of neural networks. To show the superiority of the presented adaptive neural networks controller, the simulation results are given while comparing with backstepping controller chosen as the baseline controller. According to the simulation results, it is shown that the proposed controller can effectively keep the vehicle tracking the pre-given trajectory in high velocity and curvature with much accuracy under parameter variations.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.421-424
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• 1990

An iterative learning control scheme for exact-tracking control and parameter estimation of uncertain robotic systems is presented. In the learning control structure, tracking and feedforward input converge globally and asymptotically as iteration increases. Since convergence of parameter errors depends only on the persistent exciting condition of system trajectories along the iteration independently of length of trajectories, it may be achieved with only system trajectories of small duration. In addition, these learning control schemes are expected to be effectively applicable to time-varying parametric systems as well as time-invariant systems, for the parameter estimation is performed at each fixed time along the iteration. Finally, no usage of acceleration signal and no in version of estimated inertia matrix in the parameter estimator makes these learning control schemes more feasible.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.560-564
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• 1996

A mixed H$^{2}$/$H^{\infty}$ controller design method for linear systems with time delay in all variables and parameter uncertainties in all system matrices is proposed. Robust $H^{\infty}$ performance and H$^{2}$ performance condition that accounts for model-matching of closed loop system and disturbance rejection is also derived. With expressing uncertain system with linear fractional transformation form, we transform the robust stability and performance problem to the H$^{2}$/$H^{\infty}$ optimization problem and design a mixed H$^{2}$/$H^{\infty}$ controller. Using the proposed method, mixed H$^{2}$/$H^{\infty}$ controller for underwater vehicle with time delay and parameter variations are designed. Simulations of a design example with hydrodynamic parameter variations and disturbance are presented to demonstrate the achievement of good robust performance.t performance.ance.

• Journal of the Korean Mathematical Society
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• v.50 no.4
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• pp.829-845
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• 2013

In this paper, we firstly establish a family of curvature invariant conditions lying between the well-known 2-nonnegative curvature operator and nonnegative curvature operator along the Ricci flow. These conditions are defined by a set of inequalities involving the first four eigenvalues of the curvature operator, which are named as 3-parameter ${\lambda}$-nonnegative curvature conditions. Then a related rigidity property of manifolds with 3-parameter ${\lambda}$-nonnegative curvature operators is also derived. Based on these, we also obtain a strong maximum principle for the 3-parameter ${\lambda}$-nonnegativity along Ricci flow.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.10
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• pp.148-155
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• 1998

For products of various shapes, compound surfaces are used. Blending surfaces are essential to the products of the compound surfaces. In this paper a method of making shape of blending surface flexible with parameter control is discussed. The parameter has quantitative control of shape of the blend. The blending surface is applied to NURBS and simple primitives in solid model. Intersection curves of surfaces is used to provide the blend with generality. Rail curve are found with the intersection curves. The blend is generated by rail curves and parameter control. Also, In strict constraint condition, blending surface with flexible shapes is discussed, keeping ;${GC}^1$ and ;${GC}^2$ continuity between free-formed surfaces and solids. Joining blending ,bridge blending and blending surface at corner are generated.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.4
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• pp.427-438
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• 1991

An iterative learning control scheme for exact-tracking control and parameter estimation of uncertain robotic system is preented. In the learning control structure, the control input converges globally and asymtotically to the desired input as iteration increases. Since convergence of parameter errors depends only on the persistent exciting condition of system trajectories along the iteration independently of the time-duration of trajectories, it may be achieved with system trajectories with small duration. In addition, the proposd learning control schemes are applicable to time-varying parametric systems as well as time-invariant systems, because the parameter estimation is performed at each fixed time along the iteration. In the parameter estimator, the acceleration information as well as the inversion of estimated inertia matrix are not used at all, which makes the proposed learning control schemes more feasible.

• Computers and Concrete
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• v.30 no.4
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• pp.269-276
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• 2022

In this paper, frequency vibrations of double-walled carbon nanotubes (CNTs) has been investigated based upon nonlocal elastic theory. The inference of small scale is being perceived by establishing nonlocal Love shell model. The wave propagation approach has been operated to frame the governing equations as eigen value system. An innovational nonlocal model to examine the scale effect on vibrational behavior of armchair, zigzag and chiral of double-walled CNTs. An appropriate selection of material properties and nonlocal parameter has been considered. The influence of dimensionless nonlocal parameter has been studied in detail. The dominance of end condition via nonlocal parameter is explained graphically. The results generated furnish the evidence regarding applicability of nonlocal shell model and also verified by earlier published literature.

• Structural Engineering and Mechanics
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• v.22 no.4
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• pp.401-418
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• 2006

Solutions to the problems of structural parameter estimation from modal response using leastsquares minimization of force or displacement residuals are generally sensitive to noise in the response measurements. The sensitivity of the parameter estimates is governed by the physical characteristics of the structure and certain features of the noisy measurements. It has been shown that the regularization method can be used to reduce effects of the measurement noise on the estimation error through adding a regularization function to the parameter estimation objective function. In this paper, we adopt the regularization function as the Euclidean norm of the difference between the values of the currently estimated parameters and the a priori parameter estimates. The effect of the regularization function on the outcome of parameter estimation is determined by a regularization factor. Based on a singular value decomposition of the sensitivity matrix of the structural response, it is shown that the optimal regularization factor is obtained by using the maximum singular value of the sensitivity matrix. This selection exhibits the condition where the effect of the a priori estimates on the solutions to the parameter estimation problem is minimal. The performance of the proposed algorithm is investigated in comparison with certain algorithms selected from the literature by using a numerical example.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.12
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• pp.1593-1598
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• 2011

The purpose of this study is to perform parameter selection and develop a method for the condition monitoring of an LCD conveyance robot. To determine the vibration characteristics of the driving part of the robot, the gear mesh frequency (GMF) of the speed-reducing gearbox is calculated and confirmed by frequency analysis. In order to ensure reproducibility of the measured data, an appropriate working pattern is selected and experiments are carried out. For condition monitoring of the robot, a wireless measurement system is constructed and used in parameter selection, with the GMF as the center. A method involving the use of the standard deviation of the measured data and another method involving the use of multiple value of amplitude are proposed.