• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.11
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• pp.990-998
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• 2007

Adaptive output feedback control technique using Neural Networks(NN) is proposed for uncertain nonlinear Multi-Input Multi-Output(MIMO) systems. Modified Dynamic Inversion Model(MDIM) is introduced to decouple uncertain nonlinearities from inversion-based control input. MDIM consists of approximated dynamic inversion model and inversion model error. One NN is applied to compensate the MDIM of the system. The output of the NN augments the tracking controller which is based upon a filtered error approximation with online weight adaptation laws which are derived from Lyapunov's direct method to guarantee tracking performance and ultimate boundedness. Several numerical results are illustrated in the simulation of Van der Pol system and unmanned helicopter with model uncertainties.

• Journal of the Earthquake Engineering Society of Korea
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• v.24 no.2
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• pp.87-93
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• 2020

Seismic responses due to the dynamic coupling between a primary structure and secondary system connected to a structure are analyzed in this study. The seismic responses are compared based on dynamic coupling criteria and according to the error level in the natural frequency, with the recent criteria being reliant on the error level in the spectral displacement response. The acceleration responses and relative displacement responses of a primary structure and a secondary system for a coupled model and two different decoupled models of two degrees-of-freedom system are calculated by means of the time integration method. Errors in seismic responses of the uncoupled models are reduced with the recent criteria. As the natural frequency of the secondary system increases, error in the natural frequency decreases, but seismic responses of uncoupled models can be underestimated compared to that of coupled model. Results in this paper can help determine dynamic coupling and predict uncoupled models' response conservatism.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.641-645
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• 1996

Ball screws are used in the feeding system for transmission of driving force. The friction effect between bed and table, which can affect in accuracyin one dimension feeding and describe the dynamic feeding error, could be simplified as a specific model through experiments. The experiments for dynamic feeding errors were performed om tje NC lathe eith a ball screw. The errors in feeding were measured with respect to the variances of feed, spindle speed and motor current for feeding. A rotary encoder and a current sensor were installed with NC lathe.

• Environmental and Resource Economics Review
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• v.9 no.2
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• pp.373-391
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• 2000

This paper investigates the existence of a long-run relationship between world oil price and consumer price index for Korea during 1983~1999. The cointegration and error correction modelling approaches have been applied. Empirical results suggest that there exists a long-run relationship among world oil prices. consumer prices, M2 and a production gap variable. The dynamic behavior of the relationship has been investigated by estimating a error correction model, in which the error correction term have been found significant. The error correction model has also been found to be robust as it satisfy almost all relevant diagnostic tests.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.323-326
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• 1996

In a simple system, the control schemes work well provided that the characteristic of the plant or the coefficients are known and fixed. But the condition is not met in the system like satellite, for example, varying over time and the coefficients of dynamic system change due to disturbance, etc, and the better precise model is required to control the given dynamic system well. Conversely, the fixed controller make the unmodel dynamic system with a wide class of modelling error be stable within the error tolerance limits. Also, a robust model reference adaptive control scheme is designed for the plant, paying attention to the derivation of the appropriate parametric model and the design of the normalizing signal to guarantee that it has the desired properties.

• Transactions of the Korean Society of Mechanical Engineers
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• v.10 no.1
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• pp.157-163
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• 1986

A method to improve the Finite Elements Model and to identify structure stiffness damages utilizing measured dynamic characteristics is suggested. In order to show the effectiveness of the proposed method, a sample structure is adopted and tested. It is found that; (1) the Finite Elements Model can be improved with experimentally obtained dynamic characteristics satisfactorily and (2) the test results are also very helpful to search the stiffness damaged part of the sample structure via plotting the error matrix[E], especially it is aboved that the weighted error matrix is very effective to detect even the stiffness changes are relatively small.

• Communications for Statistical Applications and Methods
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• v.29 no.6
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• pp.695-708
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• 2022

Recently, several studies have been conducted using state space model. In this study, a dynamic linear model with state space model form is applied to stock data. The monthly returns for 135 Korean stocks are fitted to a dynamic linear model, to obtain an estimate of the time-varying 𝛽-coefficient time-series. The model formula used for the return is a capital asset pricing model formula explained in economics. In particular, the transition equation of the state space model form is appropriately modified to satisfy the assumptions of the error term. k-shape clustering is performed to classify the 135 estimated 𝛽 time-series into several groups. As a result of the clustering, four clusters are obtained, each consisting of approximately 30 stocks. It is found that the distribution is different for each group, so that it is well grouped to have its own characteristics. In addition, a common pattern is observed for each group, which could be interpreted appropriately.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2000.05a
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• pp.6-10
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• 2000

In this paper a methodology for designing a controller based on inverse dynamics for speed control of DC motors is presented. The proposed controller consists of a low-pass prefilter the inverse dynamic model of a system and the PI controller. The low-pass prefilter prevents high frequency effects from the inverse dynamic model. The model is characterized by a nonlinear friction model. The PI controller regulates the error between the set-point and the system output which is caused by modeling error disturbances and variations f parameters. The parameters of the model and the PI controller are optimized offlinely by genetic algorithm. The experimental results on a DC motor system illustrate the performance of the proposed controller.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.6
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• pp.524-532
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• 2002

This paper presents a new in-flight alignment method for an SDINS under large initial heading error. To handle large heading error, a new attitude error model is introduced. The attitude errors are divided into heading error and leveling errors using a newly defined horizontal frame. Some navigation error dynamic models are derived from the attitude error model for indirect feedback filtering of the in-flight alignment system. A Kalman filter with Position measurement is designed to estimate navigation errors as the indirect feedback filter Simulation results show that the proposed in-flight alignment method reduces the heading error very quickly from more than 40deg to about 5deg so as to apply a refined navigation filter. The total alignment process including leveling mode and navigation mode in addition to the proposed one allows large initial values not only in heading error but also in leveling errors.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1990.10a
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• pp.79-84
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• 1990

The modal parameter estimations of linear multi-degree-of-freedom structural dynamic systems are carried out in time domain. For this purpose, the equation of motion is transformed into the autoregressive and moving average model with auxiliary stochastic input (ARMAX) model. The parameters of the ARMAX model are estimated by using the sequential prediction error method. Then, the modal parameters of the system are obtained thereafter. Experimental results are given for a 3-story building model subject to ground exitations.