• Bulletin of the Korean Mathematical Society
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• v.38 no.1
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• pp.29-53
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• 2001

This note presents a an indirect adaptive control scheme for first-order continuous-time systems. The estimated plant model is controllable and then the adaptive scheme is free from singularities. The singularities are avoided through a modification of the estimated plant parameter vector so that its associated Sylvester matrix is guaranteed to be nonsingular. That properties is achieved by ensuring that the absolute value of its determinant does not lie below a positive threshold. A modification scheme based on the achievement of a modified diagonally dominant Sylvester matrix of the parameter estimates is also given as an alternative method. This diagonal dominance is achieved through estimates modification as a way to guarantee the controllability of the modified estimated model when a controllability measure of the ‘a priori’ estimated model fails. In both schemes, the use of a hysteresis switching function for the modification of the estimates is not required to ensure the nonsingularity of the Sylvester matrix of the estimates.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.6
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• pp.667-672
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• 2003

In this paper, we propose a systematic method for intelligent digital redesign of a fuzzy-model-based controller for continuous-time nonlinear dynamical systems which may also contain uncertainties. The continuous-time uncertain TS fuzzy model is first constructed to represent the uncertain nonlinear systems. An extended parallel distributed compensation(EPDC) technique is then used to design a fuzzy-model-based controller for both stabilization and tracking. The designed continuous-time controller is then converted to an equivalent discrete-time controller by using an integrated intelligent digital redesign method. This new design technique provides a systematic and effective framework for integration of the fuzzy-model-based control theory and the advanced digital redesign technique for nonlinear dynamical systems with uncertainties. Finally, The single link flexible-joint robot arm is used as an illustrative example to show the effectiveness and the feasibility of the developed design method.

• Communications for Statistical Applications and Methods
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• v.23 no.5
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• pp.423-432
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• 2016

In this paper, we stochastically analyze the continuous time surplus process in a risk model which involves a continuous type investment. It is assumed that the investment of the surplus to other business is continuously made at a constant rate, while the surplus process stays over a given sufficient level. We obtain the stationary distribution of the surplus level and/or its moment generating function by forming martingales from the surplus process and applying the optional sampling theorem to the martingales and/or by establishing and solving an integro-differential equation for the distribution function of the surplus level.

• Bulletin of the Korean Mathematical Society
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• v.60 no.1
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• pp.93-111
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• 2023

In this paper we study a nudging continuous data assimilation algorithm for the three-dimensional Leray-α model, where measurement errors are represented by stochastic noise. First, we show that the stochastic data assimilation equations are well-posed. Then we provide explicit conditions on the observation density (resolution) and the relaxation (nudging) parameter which guarantee explicit asymptotic bounds, as the time tends to infinity, on the error between the approximate solution and the actual solution which is corresponding to these measurements, in terms of the variance of the noise in the measurements.

• Journal of computational fluids engineering
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• v.4 no.2
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• pp.47-56
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• 1999

We developed a computer program to simulate the flow field in the presence of electro-magnetic fields. The steady, two-dimensional conservation equations for mass and momentum were solved simultaneously with Maxwell equations for electro-magnetic fields. Using this program, a numerical analysis was carried out to analyze the fluid flow in the continuous casting mold with electromagnetic brake. The effects of magnetic fields size, nozzle angle and EMBR yoke position on the flow fields in the continuous casting were investigated in the present study. The flow fields with EMBR were compared with those without EMBR. We also investigated the distribution of tracer concentration as a function of time in order to calculate their residence time in the mold with EMBR. By controlling the flow fields properly using EMBR, we can prevent the direct flow impaction on the wall which can give a damage on the mold surface and reduce surface defects of stainless steel sheet products.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1872-1873
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• 2011

This paper presents a discrete-time approximate linear model of the continuous-time pulse-width-modulated linear system, and then, by employing the resultant model, a simple LQ suboptimal control scheme is proposed for a DC-DC step-down buck converter. The proposed scheme effectively regulates the output voltage to the desired level, which is also verified by the numerical simulation.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.10
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• pp.1488-1497
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• 1989

In this paper, a new adaptive control scheme is proposed that uses a special form of rational function-type linear operator in the parameter adaptation and that removes the augmenting signal terms of the control input components. This adaptation scheme is applied to the MRAC of continuous-time, linear time-invariant, minimum-phase plants whose relative degrees are arbitrary. This scheme can be applied without any change of the controller structure to the adaptive systems regardless of the relative degree if it is greater than 1. And this scheme does not require any signal augmentation for arbitrary relative-degree plants if the reference model has no zeros. The asymptotic stability of the adaptive systems controlled by this scheme is shown by a hyper-stability method.

• Food Science and Biotechnology
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• v.14 no.3
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• pp.328-333
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• 2005

Finite difference model and dynamic thermal property evaluation system were developed to estimate convection heat transfer coefficient by modeling temperature-time profile of beef cube in continuous flow sterilizing system. As input parameters of the model, specific heat and thermal conductivity values of beef frankfurter meat were independently measured from 20 to $80^{\circ}C$. Convection heat transfer coefficient was estimated by comparing simulated and measured temperature-time profiles. Actual temperature-time profiles of meat cube were measured at flow rates of 15, 30, and 45 L/min and viscosities from 0 to 15 cp, and mean values of convection heat transfer coefficients ranged from 792 to $2107\;W/m^2{\cdot}K$. Convection heat transfer coefficient increased with increase in flow rate and decreased as viscosity increased.

• International Journal of Aerospace System Engineering
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• v.2 no.1
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• pp.43-46
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• 2015

Aeroelastic gust response analysis plays an important role in design of aircrafts. For gust response analysis, frequency domain aerodynamics method has been typically used with generalized aerodynamic influence coefficient matrices at various reduced frequencies. However, it cannot be applied to the aeroservoelastic analysis, such as gust alleviation control. Time-domain state space (SS) models must be built. It attacks little attention that gust response analysis relies on continuous gust time-domain input signal in terms of its PSD function. The aim the current study is to provide a reduced-order modeling (ROM) method based on CFD to model gust responses for continuous gust responses for continuou gust inputs in time domain. The paper analyzed the gust response of AGARD445.6 wing subjected to the Dryden gust with ROMs and compared the difference between the rigid structure and elastic one. The results demonstrate that structure elastic effect effect should be considered in the design of aircraft.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1209-1223
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• 2022

Blood pressure is one of the key physiological parameters for determining human health, and can prove whether human cardiovascular function is healthy or not. In general, what we call blood pressure refers to arterial blood pressure. Blood pressure fluctuates greatly and, due to the influence of various factors, even varies with each heartbeat. Therefore, achievement of continuous blood pressure measurement is particularly important for more accurate diagnosis. It is difficult to achieve long-term continuous blood pressure monitoring with traditional measurement methods due to the continuous wear of measuring instruments. On the other hand, radar technology is not easily affected by environmental factors and is capable of strong penetration. In this study, by using machine learning, tried to develop a linear blood pressure prediction model using data from a public database. The radar sensor evaluates the measured object, obtains the pulse waveform data, calculates the pulse transmission time, and obtains the blood pressure data through linear model regression analysis. Confirm its availability to facilitate follow-up research, such as integrating other sensors, collecting temperature, heartbeat, respiratory pulse and other data, and seeking medical treatment in time in case of abnormalities.