• Progress in Medical Physics
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• v.8 no.1
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• pp.75-82
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• 1997

The human physiological systems are so complex and irregular dynamics. Dynamics of peripheral blood vessel, in particular, have quite sensitive and complex. Before, the linear analytic method have been used to analyze the system. But, the method have many problems to predict the following results. In the other hand, the nonlinear analytic method, chaotic time series analysis method, is suitable for measuring complex, vary system. In this study, the scalar data of the blood flow of peripheral blood vessel of rabbits, in accordance with injection of glucose, was obtained and redefined as multi-dimensional vectors, with time-series analytic methods. This study also intended to confirm that the peripheral blood flow is chaotic dynamics and evaluate the availability of non-linear analytic method. As a result, the existing FFT, and mean could show the difference of blood flow of peripheral blood vessel by injection of glucose, but the nonlinear analytic method could show the definite difference. The hemodynamics is a chaotic phenomenon.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.5
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• pp.442-450
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• 2002

In measuring EEG, which is widely used for studying brain function, EEG is frequently mixed with noise and artifact. In this study, the signals relevant to the artifact were distracted by applying ICA to EEG signal. First, each independent component which was assumed to be the source was separated by applying ICA to EEG which involved artifact relevant to the eye movement of a normal person. Next, the signal which was assumed to be artifact was removed from the separated 18 independent components, and the nonlinear analysis method such as correlation dimension and the Iyapunov exponent was applied to each reconstructed EEG signal and the original signal including artifact in order to find meaningful difference between the two signals and infer the anatomical localization of its source and distribution. This study shows it is possible not only to analyze the brain function visually and spatially for visually complex EEG signal, but also to observe its meaningful change through the quantitative analysis of EEG by means of the nonlinear analysis.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.595-602
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• 2009

Fuzzy rules, which represent the behavior of their system, are sensitive to fuzzy clustering techniques. If the classification abilities of such clustering techniques are improved, their systems can work for the purpose more accurately because the capabilities of the fuzzy rules and parameters are enhanced by the clustering techniques. Thus, this paper proposes a new hierarchically structured clustering algorithm that can enhance the classification abilities. The proposed clustering technique consists of two clusters based on correlationship and statistical characteristics between data, which can perform classification more accurately. In addition, this paper uses difference data sets to reflect the patterns and regularities of the original data clearly, and constructs multiple fuzzy systems to consider various characteristics of the differences suitably. To verify effectiveness of the proposed techniques, this paper applies the constructed fuzzy systems to the field of time series prediction, and performs prediction for nonlinear time series examples.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.9
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• pp.445-456
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• 2005

We propose a fast and accurate fluid solver of the Wavier-Stokes equations for the physics-based fluid simulations. Our method utilizes the solution of the Stokes equation as an initial guess for the velocity of the nonlinear term in the Wavier-Stokes equations. By guessing the initial velocity close to the exact solution of the given nonlinear differential equations, we can develop remarkably accurate and stable fluid solver. Our solver is based on the implicit scheme of finite difference methods, that makes it work well for large time steps. Since we employ the ADI method, our solver is also fast and has a uniform computation time. The experimental results show that our solver is excellent for fluids with high Reynolds numbers such as smoke and clouds.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.6
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• pp.208-216
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• 1996

This paper presents a decentralized control scheme for interconnected systems with unmodeled nonlinearities and interactions using a neural coordinator. The interactions due to the interconnection and the unmodeled nonlinearity associated with each subsystem are represented by the deviations from linearized states of decomposed subsystems. the decentralized controller is composed of local controllers and a neural coordinator. The local controller for each subsystem is derived from linearized local system parameters y linear optimal control theory. the neural cooridnator generates a corrective control signal to cancel the effect of deviation sthrough the backpropagation learning with the rrors obtained form the difference of the local system outputs and reference model outputs. the reference model consists of the part of local system without deviations. The effectiveness of the proposed control scheme is demonstrated by simulation studies.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.271-274
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• 1997

This paper presents an adaptive quantization of image sequences using the Radial Basis Function Network(RBFN) which classifies interframe image blocks. The clssification algorithm consists of two steps. Blocks are classified into NA(No Activity), SA(Small Activity), VA(Verical Activity), and HA(Horizontal Activity) classes according to edges, image activity and AC anergy distribution. RBFN is trained using the classification results of the above algorithm, which are nonlinear classification features are acquired from the complexity and variability of difference blocks. Simulation result shows that the the adaptive quantization using the RBFN method produced better results better results than that of the sorting and MLP methods.

• Proceedings of the KSME Conference
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• 2001.11a
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• pp.515-520
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• 2001

Due to the high power to weight ratio and fast response under heavy load, the hydraulic systems are still applied to the development of many industrial facilities such as heavy duty construction vehicles, aerospace/military weapon actuating systems and motion simulators. Unlike the other actuators, single-rod hydraulic cylinder exhibits a lot different dynamic characteristics between the extending and retracting stroke because of the difference in pressure acting areas. In this research, in order to overcome this nonlinear feature, $H_{\infty}$ optimal controller was designed and implemented with DSP board that was specifically developed for the experiment. From the experimental result, we could confirm that the overall performance of single-rod hydraulic servo system is similar with the results as we expected in the design stage.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.1
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• pp.1-7
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• 2009

As designing PID control on aircraft, we consider a gain scheduling on altitude and velocity. If pitot tube is not installed in the unpowered air vehicle, the control performance is reduced by the difference between ground speed and air speed with a wind considered. In this paper, a simple guidance controller (LOS: Line of Sight) and the wind estimator using Kalman filter are designed. And we minimize the wind effect through the estimator. Finally, we perform the 6-DOF nonlinear simulation with the wind model to verify the performance of the controller with the wind estimator.

• Smart Structures and Systems
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• v.20 no.6
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• pp.683-696
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• 2017

In this study, the reliability of nonlinear ultrasonic modulation based fatigue crack detection is improved using a feature-level data fusion approach. When two ultrasonic inputs at two distinct frequencies are applied to a specimen with a fatigue crack, modulation components at the summation and difference of these two input frequencies appear. First, the spectral amplitudes of the modulation components and their spectral correlations are defined as individual features. Then, a 2D feature space is constructed by combining these two features, and the presence of a fatigue crack is identified in the feature space. The effectiveness of the proposed fatigue crack detection technique is experimentally validated through cyclic loading tests of aluminum plates, full-scale steel girders and a rotating shaft component. Subsequently, the improved reliability of the proposed technique is quantitatively investigated using receiver operating characteristic analysis. The uniqueness of this study lies in (1) improvement of nonlinear ultrasonic modulation based fatigue crack detection reliability using feature-level data fusion, (2) reference-free fatigue crack diagnosis without using the baseline data obtained from the intact condition of the structure, (3) application to full-scale steel girders and shaft component, and (4) quantitative investigation of the improved reliability using receiver operating characteristic analysis.

• Earthquakes and Structures
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• v.22 no.1
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• pp.65-82
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• 2022

This paper presents a structural performance assessment of a historical masonry clock tower both using numerical and experimental process. The numerical assessment includes developing of finite element model with considering different types of soil-structure interaction systems, identifying the numerical dynamic characteristics, finite element model updating procedure, nonlinear time-history analysis and evaluation of seismic performance level. The experimental study involves determining experimental dynamic characteristics using operational modal analysis test method. Through the numerical and experimental processes, the current structural behavior of the masonry clock tower was evaluated. The first five experimental natural frequencies were obtained within 1.479-9.991 Hz. Maximum difference between numerical and experimental natural frequencies, obtained as 20.26%, was reduced to 4.90% by means of the use of updating procedure. According to the results of the nonlinear time-history analysis, maximum displacement was calculated as 0.213 m. The maximum and minimum principal stresses were calculated as 0.20 MPa and 1.40 MPa. In terms of displacement control, the clock tower showed only controlled damage level during the applied earthquake record.