• The Transactions of the Korean Institute of Electrical Engineers D
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• 제51권1호
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• pp.39-42
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• 2002

For the purpose of modeling EEG signal which has nonstationary and nonlinear dynamic characteristics, this paper propose a state feedback real time recurrent neural network model. The state feedback real time recurrent neural network is structured to have memory structure in the state of hidden layers so that it has arbitrary dynamics and ability to deal with time-varying input through its own temporal operation. For the model test, Mackey-Glass time series is used as a nonlinear dynamic system and the model is applied to the prediction of three types of EEG, alpha wave, beta wave and epileptic EEG. Experimental results show that the performance of the proposed model is better than that of other neural network models which are compared in this paper in some view points of the converging speed in learning stage and normalized mean square error for the test data set.

• Journal of the Korean Society for Precision Engineering
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• 제23권7호
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• pp.152-158
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• 2006

The objective of this work is to develop the knee joint model for representing various pendulum motions and quantifying the spasticity. Knee joint model included the extension and flexion muscles. The joint moment consists of both the active moment from the stretch reflex and the passive moment from the viscoelastic joint properties. The stretch reflex was modeled as nonlinear feedback of muscle length and the muscle lengthening velocity, which is Physiologically-feasible. Moreover, we modeled the spastic reflex as having dynamic threshold to account far the various pendulum trajectories of spastic patients. We determined the model parameters of three patients who showed different pendulum trajectories through minimization of error between experimental and simulated trajectories. The simulated joint trajectories closely matched with the experimental ones, which show the proposed model can predict pendulum motions of patients with different spastic severities. The predicted muscle force from spastic reflex appeared more frequently in the severe spastic patient, which indicates the dynamic threshold relaxes slowly in this patient as is manifested by the variation coefficient of dynamic threshold. The proposed method provides prediction of muscle force and intuitive and objective evaluation of spasticity and it is expected to be useful in quantitative assessment of spasticity.

• The KIPS Transactions:PartC
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• 제10C권6호
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• pp.711-716
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• 2003

We propose a new Interet time synchronization model using danamic linear model and introduce the characteristics of internet transmission delays. SNTP(Simple Network Time Protocol) has been widely used as a time synchronization method on the Internet. While SNTP provides a very simple usage, SNTP may not provide the stable services, since SNTP does not consider the several essential error factors. In order to overcome the instabitily of SNTP, we analyze the process of time estimation of SNTP and find the difference between forward transmission delay and backward transmission delay operates the main error on the estimation of an time offset.

• The Transactions of the Korean Institute of Electrical Engineers
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• 제39권12호
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• pp.1306-1316
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• 1990

A controller using a multilayer neural network is proposed to the dynamic control of a PUMA 560 robot arm. This controller is developed based on an error back-propagation (BP) neural network. Since the neural network can model an arbitrary nonlinear mapping, it is used as a commanded feedforward torque generator. A Proportional Derivative (PD) feedback controller is used in parallel with the feedforward neural network to train the system. The neural network was trained by the current state of the manipulator as well as the PD feedback error torque. No a priori knowledge on system dynamics is needed and this information is rather implicitly stored in the interconnection weights of the neural network. In another experiment, the neural network was trained with the current, past and future positions only without any use of velocity sensors. Form this thim window of position values, BP network implicitly filters out the velocity and acceleration components for each joint. Computer simulation demonstrates such powerful characteristics of the neurocontroller as adaptation to changing environments, robustness to sensor noise, and continuous performance improvement with self-learning.

• Proceedings of KOSOMES biannual meeting
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• 해양환경안전학회 2004년도 춘계학술발표회
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• pp.7-11
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• 2004

Maritime safety and marine environmental protection are the most important topic in marine society. But, so many marine accidents rave been occurred with the development of marine transportation industry. On the other side, ship is being operated under a highly dynamic environment and many factors are related with ship's collision Nowadays, the increasing tendency to the human errors of ship's collision is remarkable, and the investigation of the human errors has been heavily concentrated. This study analysed on the human errors of ship's collision related to the negligence of lookout and classified basic error type using GEMS(Generic Error Modeling System) dynamic model.

• Journal of the Semiconductor & Display Technology
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• 제3권2호
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• pp.41-46
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• 2004

This paper proposes a robust discrete time Kalman filter (RDKF) for the dynamic compensation of nonlinearity in a homodyne laser interferometer for high-precision displacement measurement and in real-time. The interferometer system is modeled to reduce the calculation of the estimator. A regulator is applied to improve the robustness of the system. An estimator based on dynamic modeling and a zero regulator of the system was designed by the authors of this study. For real measurement, the experimental results show that the proposed interferometer system can be applied to high precision displacement measurement in real-time.

• Journal of Astronomy and Space Sciences
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• 제26권3호
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• pp.317-328
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• 2009

Relative dynamic models of satellites which describe the relative motion between two satellites is fundamental for research on the formation flying. The accuracy of various linearized or nonlinear models of relative motion is analyzed and compared. A 'Modeling Error Index (MEI)' is defined for evaluating the accuracy of models. The accuracy of the relative dynamic models in various orbit circumstance are obtained by calculating the modeling error with various eccentricities of the chief orbit and distances between the chief and the deputy. It is found that the modeling errors of the relative dynamic models have different values according to the eccentricity, J2 perturbation, and the distance between satellites. Since the evaluated accuracy of various models in this paper means the error of dynamic models of the formation flying, the results of this paper are very useful for choosing the appropriate relative model of the formation flying mission.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 한국퍼지및지능시스템학회 2004년도 추계학술대회 학술발표 논문집 제14권 제2호
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• pp.211-216
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• 2004

In this thesis, we present the Takagi-Sugeno-Kang (TSK) fuzzy model based adaptive controller and adaptive identification for a general class of uncertain nonlinear dynamic systems. We use an estimated model for the unknown plant model and use this model for designing the controller. The hybrid adaptive control combined direct and indirect adaptive control based on TSK fuzzy model is constructed. The direct adaptive law can be showed by ignoring the identification errors and fails to achieve parameter convergence. Thus, we propose an TSK fuzzy model based hybrid adaptive (HA) law combined of the tracking error and the model ins error to adjust the parameters. Using a Lyapunov synthesis approach, the proposed hybrid adaptive control is proved. The hybrid adaptive law (HA) is better than the direct adaptive (DA) method without identifying the model ins error in terms of faster and improved tracking and parameter convergence. In order to show the applicability of the proposed method, it is applied to the inverted pendulum system and the performance is verified by some simulation results.

• The Transactions of the Korean Institute of Electrical Engineers A
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• 제48권10호
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• pp.1279-1286
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• 1999

In conventional GPS/DR integration schemes, the GPS position (or pseudo-range) information is used in calibrating DR sensors. In those schemes, however, an inaccurate calibration may degrade the position accuracy when the GPS measurement is not available. This paper presents a new integration scheme where the GPS velocity information is used in calibrating DR sensors. Also proposed is a new error model of DR sensors for calibrating the bias error and the tilt error in dynamic environments. The proposed model makes it possible that the errors of both the DR sensor parameters and the velocity are calibrated using the GPS carrier-based velocity(or the pseudo-range rate) measurement while the DR position error is calibrated using the GPS position measurement. Since the DR sensors are calibrated accurately, the positioning accuracy is drastically improved when the GPS measurements are unavailable.

• Journal of the Korean Society for Precision Engineering
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• 제21권2호
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• pp.130-137
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• 2004

A dynamic model of railway reducer is developed by the lumped parameter method. The model accounts for shafts, bearings flexibilities, gyroscopic effects and the force couplings among the transverse and torsion motions due to gearing. Vibration/noise analysis as well as strength of gear teeth, and bearing life are considered. Excitation forces of railway reduction are considered as the mass unbalance of the rotors, misalignment and a function of gear transmission error which comes from the modified tooth surface. A campbell diagram, in which the excitation sources caused by the mass unbalance of the rotors, misalignment and the transmitted errors of the gearing are considered, shows that, at the operating speed, there are not the critical speed. The program which can be used to analyze and predict vibration/noise characteristics by mass unbalance, misalignment and gear transmission error of railway reduction is developed with this system model.