• 터널과지하공간
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• 제23권2호
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• pp.110-119
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• 2013

터널 시공 중 천단침하와 내공변위를 측정하는 것이 일반화되어 있다. 터널 시공 중 계측기를 설치한 후 첫 번째로 측정한 천단침하와 내공변위의 1일간 변위량을 각각 초기천단침하속도와 초기내공변위속도로 또 마지막으로 계측한 천단침하와 내공변위를 각각 최종천단침하와 최종내공변위로 정의하고 계측한 최종변위와 초기변위속도의 관계를 분석하였다. 이를 위한 분석용 자료는 서울지하철 906공구에서 터널 시공 중 계측한 것이다. 이 터널의 폭과 높이는 각각 약 11.5 m, 10 m이며 지표에서 터널천단까지의 깊이는 약 10-20 m의 저심도 터널이다. 또 터널이 시공된 지층은 풍화토 또는 풍화암으로 연약한 지반이다. 터널은 상하반으로 나누어 시공되었고 길이는 1,820 m이다. 이번 분석에 이용한 계측치는 터널 상하반 시공 중에 얻은 것으로 천단침하계측 결과가 184개, 내공변위계측 결과는 258개이다. 분석결과 풍화토의 터널에서 초기변위속도와 최종변위가 상대적으로 큰 경향이 있었다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국제학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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• pp.1051-1054
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• 1988

In this paper we present initial convergence properties of the Kalman filtering algorithm, we put an arbitrary small positive correlation matrix as an initial condition in the recursive algorithm. This arbitrary small initial condition perturbs the Kalman filtering algorithm and may lead to initial instability. We derive a condition which insures the stable operation of the Kalman filtering algorithm from the stochastic Lyapunov difference equation.

• 제어로봇시스템학회논문지
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• 제4권5호
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• pp.608-615
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• 1998

In this paper a second-order iterative learning control algorithm with feedback is proposed for the trajectory-tracking control of nonlinear dynamic systems with unidentified parameters. In contrast to other known methods, the proposed teaming control scheme utilize more than one past error history contained in the trajectories generated at prior iterations, and a feedback term is added in the learning control scheme for the enhancement of convergence speed and robustness to disturbances or system parameter variations. The convergence proof of the proposed algorithm is given in detail, and the sufficient condition for the convergence of the algorithm is provided. We also discuss the convergence performance of the algorithm when the initial condition at the beginning of each iteration differs from the previous value of the initial condition. The effectiveness of the proposed algorithm is shown by computer simulation result. It is shown that, by adding a feedback term in teaming control algorithm, convergence speed, robustness to disturbances and robustness to unmatched initial conditions can be improved.

• 한국해양공학회지
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• 제19권6호통권67호
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• pp.78-85
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• 2005

Initial alignment and localization are important topics in inertial navigation systems, since misalignment and initial position error wholly propagate into the navigation systems and deteriorate the performance of the systems. This paper presents the error convergence characteristics of the hybrid navigation system for underwater vehicles initial position, which is based on an inertial measurement unit (IMU) accompanying a range sensor. This paper demonstrates the improvement on the navigational performance oj the hybrid system with the range information, especially focused on the convergence of the estimation of underwater vehicles initial position error. Simulations are performed with experimental data obtained from a rotating ann test with a fish model. The convergence speed and condition of the initial error removal for random initial position errors are examined with Monte Carlo simulation. In addition, numerical simulation is conducted with an AUV model in lawn-mowing survey mode to illustrate the error convergence of the hybrid navigation System for initial position error.

• 전력전자학회논문지
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• 제27권6호
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• pp.481-488
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• 2022

This study proposes compensation methods for the initial position error and torque ripple in vector control of two-phase hybrid stepping motors. Stepping motors have an asymmetrical structure due to misalignment, such as the eccentricity generated by the manufacturing and assembly process. When vector control is applied using the position information measured by an incremental encoder attached to the rotor shaft of such stepping motors, the following problems occur. First, an initial position error occurs during the forced excitation process for the initial rotor position alignment. Second, torque ripple corresponding to the mechanical rotation frequency is generated. In this study, these non-ideal phenomena that occur in vector control of the stepping motor are analyzed, and compensation methods are proposed to eliminate them. The validity of the proposed initial position error and torque ripple compensation methods is verified through experiments on a two-phase hybrid stepping motor drive system.

• Journal of information and communication convergence engineering
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• 제1권4호
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• pp.189-193
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• 2003

A new algorithm is presented for adaptive notch filtering of narrow band or sine signals for embedded among broad band noise. The notch filter is implemented as a constrained infinite impulse response filter with a minimal number of parameters, Based on the recursive prediction error (RPE) method, the algorithm has the advantages of the fast convergence, accurate results and initial estimate of filter coefficient and its covariance is revealed. A convergence criterion is also developed. By using the information of the noise-to-signal power, the algorithm can self-adjust its initial filter coefficient estimate and its covariance to ensure convergence.

• 전자공학회논문지B
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• 제30B권8호
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• pp.54-63
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• 1993

This paper proposes a method for improving the performances of the neural network for optimization by an optimal estimation of initial states. The optimal initial state that leads to the global minimum is estimated by using the stochastic approximation. And then the update rule of Hopfield model, which is the high speed deterministic algorithm using the steepest descent rule, is applied to speed up the optimization. The proposed method has been applied to the tavelling salesman problems and an optimal task partition problems to evaluate the performances. The simulation results show that the convergence speed of the proposed method is higher than conventinal Hopfield model. Abe's method and Boltzmann machine with random initial neuron output setting, and the convergence rate to the global minimum is guaranteed with probability of 1. The proposed method gives better result as the problem size increases where it is more difficult for the randomized initial setting to give a good convergence.

• 통합자연과학논문집
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• 제6권1호
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• pp.53-56
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• 2013

We are interested in the rate of convergence of solutions of 2D Navier-Stokes equations in a smooth bounded domain as the viscosity tends to zero under Navier friction condition. If the initial velocity is smooth enough($u{\in}W^{2,p}$, p>2), it is known that the rate of convergence is linearly propotional to the viscosity. Here, we consider the rate of convergence for nonsmooth velocity fields when the gradient of the corresponding solution of the Euler equations belongs to certain Orlicz spaces. As a corollary, if the initial vorticity is bounded and small enough, we obtain a sublinear rate of convergence.

• 대한전기학회논문지:전력기술부문A
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• 제48권5호
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• pp.629-635
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• 1999

A second-order iterative learning control algorithm with feedback is proposed in this paper, in which a feedback term is added in the learning control scheme for the enhancement of convergence speed and robustness to disturbances or system parameter variations. The convergence proof of the proposed algorithm is givenl, and the sufficient condition for the convergence of the algorithm is provided. And it also includes the discussions about the convergence performance of the algorithm when the initial condition at the beginning of each iteration differs from the previous value of the initial. Simulation results show the validity and efficiency of the proposed algorithm.

• 한국통신학회논문지
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• 제22권2호
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• pp.325-333
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• 1997

In fractral decoding procedure, the reconstructed image is obtained by iteratively applying the contractive transform to an arbitrary initial image. But this method is not suitable for the fast decoding because convergence speed depends on the selection of initial image. Therefore, the initial image to achieve fast decoding should be selected. In this paper, we propose an initial image estimation that can be applied to various decoding methods. The initial image similar to the original image is estimated by using only the compressed data so that the proposed method does not affect the compression ratio. From the simulation, the PSNR of the proposed initial image is 6dB higher han that of ones iterated output image of conventional decoding with Babaraimage. Computations in addition and multiplication are reduced about 96%. On the other hands, if we apply the proposed initial image to other decoding algorithms, the faster convergence speed is expected.