• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.200-200
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• 2000

Highly nonlinear dynamical systems are easily identified using neural networks. When disturbances are included in the learning data set Int system modeling, modeling process will be poorly performed. Since the radial basis functions in the radial basis function network(RBFN) are centered at the points specified by the weights, RBF networks are robust for approximating the process including the narrow-band disturbances deviating significantly from the regular signals. To exclude(filter) these disturbances, a robust algorithm for system identification, based on the RBFN, is proposed. The performance of system identification excluding disturbances is investigated and compared with the one including disturbances.

• Journal of Welding and Joining
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• v.33 no.6
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• pp.13-20
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• 2015

Many automotive companies are endeavoring to improve the quality of resistance spot welding by updating body-in-white (BIW) production line with adaptive control spot welding system to compensate the process disturbances such as gap, electrode wear, oxidized surfaces, poor fit up and adhesive etc. Most of the commercial adaptive weld controllers require proper "Initial Welding Schedule" or "Reference weld" to achieve compensation in welding parameters during real time welding. In this study, the compensation of a commercial adaptive weld controller had been observed and analyzed thoroughly for various process disturbances to find optimal initial welding schedule. It was observed that 90 percent of the expulsion current in constant current control as reference welding schedule conferred the maximum button diameter in adaptive control welding. Finally, effects of each disturbance in combined field disturbances system with adaptive control had also been confirmed with the design of experiment (DOE) by minitab(R)16 for combined disturbances situation and suitability of optimum initial weld current had also established with real body part validation test.

• Journal of the Korean Statistical Society
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• v.23 no.1
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• pp.33-38
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• 1994

The OLS-estimator of the distribance variance in the linear regression model is shown to be asymptotically unbiased when the disturbances are MA(1)-process or particular s-th autocorrelated AR(s)-process.

• Korea-Australia Rheology Journal
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• v.14 no.2
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• pp.57-62
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• 2002

The sensitivity of the final filament to the ongoing sinusoidal disturbances has been Investigated in the viscoelastic spinning using frequency response method. Amplification ratios or gains of the spinline cross-sectional area at the take-up to any disturbances show resonant peaks along the frequency regime, where the frequencies at theme points directly correspond to the imaginary parts of the successive leading eigenvalues from the linear stability analysis. As shown in Jung et al. (1999) and Lee et al (2001), the sensitivity results on the effect of various process conditions such as spinline cooling and fluid viscoelasticity, obtained by dynamic transient simulation have been corroborated in this study. That is, increasing spinline cooling makes the system less sensitive to disturbances, thus stabilizes the spinning. Also, an increasing viscoelasticity for extension-thickening fluids decreases the sensitivity of the spinning. i.e., stabilizing the system, where, as it increases the sensitivity of the spinning of extension-thinning fluids. Furthermore, it has been found in the present study that the inertia force as one of secondary forces causes the system to be more stabile or less sensitive to process disturbances.

• Communications for Statistical Applications and Methods
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• v.4 no.1
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• pp.111-117
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• 1997

The ordinary least squares estimator $S^2$ for the variance of the disturbances is considered in the linear regression model with sutocorrelated disturbances. It is proved that the OLS-estimator of disturbance variance is asymptotically unbiased and weakly consistent, when the distrubances are generated by an MA(q) process. In particular, the asymptotic unbiasedness and consistency of $S^2$ is satisfied without any restriction on the regressor matrix.

• 한국해양학회지
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• v.21 no.3
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• pp.131-135
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• 1986

Conversion of energy from potential to kinetic form is considered when a step-like initial disturbance is released to reach a final steady state. For small amplitute disturbances, linearization can be made and it is proved analytically that the conversion factor (ratio of generated kinetic to loss in potential energies) asymptotically approaches to 1/3 as the horizontal scale of disturbances becomes large.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2001.05a
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• pp.145-151
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• 2001

An extension of interaction matrix formulation to the problem of system and disturbance identification for a plant that is corrupter by both process and output disturbances is presented. With only an assumed upper bound on the order of the system and an assumed upper bound on the number of disturbance frequencies, it is shown that both the disturbance-free model and disturbance effect can be recovered exactly from disturbance-corrupted input-output data without direct measurement of the periodic disturbances. The rich information returned by the identification can be used by a performance-oriented model-based loaming or repetitive control system to eliminate unwanted periodic disturbances.

• Journal of the Korean Statistical Society
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• v.24 no.2
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• pp.507-518
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• 1995

The ordinary least squares based estiamte $S^2$ of the disturbance variance is considered in the linear regression model when the disturbances follow the first-order moving-average process. It is shown that $S^2$ is weakly consistent estimate for the disturbance varaince without any restriction on the regressor matrix X. Also, simple exact bounds on the relative bias of $S^2$ are given in finite sample sizes.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.4
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• pp.409-416
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• 2007

A momentum type actuator produces force and torque disturbances as well as its designed control torque. These disturbances are ones of the largest disturbance sources inside the spacecraft, which deteriorate the pointing stability of the high precision spacecraft. The measurement and analysis of actuator disturbances are therefore imperative for such a spacecraft, and thus a three dimensional torque measurement table has been developed for that purpose. The data acquired from the measurement table are processed in the frequency domain and displayed in the power spectral density(PSD). Through this process, disturbance model parameters are obtained and used for the attitude stability simulation. The process has been adopted for the disturbance measurement of the reaction wheel, and the validity of measurements and parameter identification procedure is verified.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.4
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• pp.66-72
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• 2021

Since the behavior of an autonomous underwater vehicle (AUV) is influenced by disturbances and moments that are not accurately known, the depth control law of AUVs must have the ability to track the input signal and to reject disturbances simultaneously. Here, we proposed robust tracking control for controlling the depth of an AUV. An augmented closed-loop system is represented by an error dynamic equation, and we can easily show the asymptotic stability of the overall system by using a Lyapunov function. The robust tracking controller is consisted of the internal model of the command signal and a state feedback controller, and it has the ability to track the input signal and reject disturbances. The closed-loop control system is robust to parameter uncertainties. Simulation results showed the control performance of the robust tracking controller to be better than that of a P + PD controller.