• Structural Engineering and Mechanics
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• v.20 no.6
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• pp.713-726
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• 2005

Based on the improved first order Taylor interval expansion, a new interval analysis method for the static or dynamic response of the structures with interval parameters is presented. In the improved first order Taylor interval expansion, the first order derivative terms of the function are also considered to be intervals. Combining the improved first order Taylor series expansion and the interval extension of function, the new interval analysis method is derived. The present method is implemented for a continuous beam and a frame structure. The numerical results show that the method is more accurate than the one based on the conventional first order Taylor expansion.

• Earthquakes and Structures
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• v.3 no.6
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• pp.805-820
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• 2012

An enhanced and efficient methodology is proposed for evaluating the robustness of an uncertain structure with passive dampers. Although the structural performance for seismic loads is an important design criterion in earthquake-prone countries, the structural parameters such as storey stiffnesses and damping coefficients of passive dampers are uncertain due to various factors or sources, e.g. initial manufacturing errors, material deterioration, temperature dependence. The concept of robust building design under such uncertain structural-parameter environment may be one of the most challenging issues to be tackled recently. By applying the proposed method of interval analysis and robustness evaluation for predicting the response variability accurately, the robustness of a passively controlled structure can be evaluated efficiently in terms of the so-called robustness function. An application is presented of the robustness function to the design and evaluation of passive damper systems.

• Journal of Ocean Engineering and Technology
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• v.11 no.4
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• pp.169-179
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• 1997

This paper presents a discrete-time sliding mode control of an autonomous underwater vehicle with parameter uncertainties and long sample interval based on discrete variable structure system. Although conventional sliding mode montrol techniques are robust to system uncertainties, in the case of the system with long sample interval, the sliding control system reveals chattering phenomenon and even makes the system unstable. This paper considers the AUV which acquires position informations from a surface ship through an acoustic telemetry system with a certain discrete interval. The control system is designed on the basis of a Lyapunov function and a sufficient condition of the switching gain to make the system stable is give. Each component of the switching gain can be determined separately one another. The controller is robust to the uncertainties, and reaching condition of the control system is satisfied for any initial condition. This control law is a generalized form of the discrete sliding mode control and reduce the chattering problem considerably. Motion control of the AUV in the vertical plane shows the effectiveness of the proposed technique.

• Journal of Power Electronics
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• v.13 no.1
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• pp.139-160
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• 2013

In this paper, an intelligent robust control system (IRCS) for precision tracking control of permanent-magnet synchronous motor (PMSM) servo drives is proposed. The IRCS comprises a recurrent wavelet-based interval type-2 fuzzy-neural-network controller (RWIT2FNNC), an RWIT2FNN estimator (RWIT2FNNE) and a compensated controller. The RWIT2FNNC combines the merits of a self-constructing interval type-2 fuzzy logic system, a recurrent neural network and a wavelet neural network. Moreover, it performs the structure and parameter-learning concurrently. The RWIT2FNNC is used as the main tracking controller to mimic the ideal control law (ICL) while the RWIT2FNNE is developed to approximate an unknown dynamic function including the lumped parameter uncertainty. Furthermore, the compensated controller is designed to achieve $L_2$ tracking performance with a desired attenuation level and to deal with uncertainties including approximation errors, optimal parameter vectors and higher order terms in the Taylor series. Moreover, the adaptive learning algorithms for the compensated controller and the RWIT2FNNE are derived by using the Lyapunov stability theorem to train the parameters of the RWIT2FNNE online. A computer simulation and an experimental system are developed to validate the effectiveness of the proposed IRCS. All of the control algorithms are implemented on a TMS320C31 DSP-based control computer. The simulation and experimental results confirm that the IRCS grants robust performance and precise response regardless of load disturbances and PMSM parameters uncertainties.

• Structural Engineering and Mechanics
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• v.29 no.5
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• pp.469-488
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• 2008

Finite element methods have often been used for structural analyses of various mechanical problems. When finite element analyses are utilized to resolve mechanical systems, numerical uncertainties in the initial data such as structural parameters and loading conditions may result in uncertainties in the structural responses. Therefore the initial data have to be as accurate as possible in order to obtain reliable structural analysis results. The typical finite element method may not properly represent discrete systems when using uncertain data, since all input data of material properties and applied loads are defined by nominal values. An interval finite element analysis, which uses the interval arithmetic as introduced by Moore (1966) is proposed as a non-stochastic method in this study and serves a new numerical tool for evaluating the uncertainties of the initial data in structural analyses. According to this method, the element stiffness matrix includes interval terms of the lower and upper bounds of the structural parameters, and interval change functions are devised. Numerical uncertainties in the initial data are described as a tolerance error and tree graphs of uncertain data are constructed by numerical uncertainty combinations of each parameter. The structural responses calculated by all uncertainty cases can be easily estimated so that structural safety can be included in the design. Numerical applications of truss and frame structures demonstrate the efficiency of the present method with respect to numerical analyses of structural uncertainties.

• Journal of Korean Society on Water Environment
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• v.22 no.5
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• pp.856-864
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• 2006

For estimating the minimum discharge to maintain a river, low flow analysis is required and long term runoff records are needed for the analysis. However, runoff data should be estimated to run a hydrologic model for ungaged river basin. For the reason, parameter estimation is crucial to simulate rainfall-runoff events for those basins using Tank model. In this study, only runoff data recorded for dry season are used for parameter estimation, which is different to other methods based on runoff data recorded for wet and dry seasons. The Harmony Search algorithm is used to determine the optimum parameters for Tank model. The coefficient of determination ($R^2$) is served as the objective function in the Harmony Search. In cases that recorded data are insufficient, the recording interval is changed and Empirical CDF is adopted to analyze the estimated parameters. The suggested method is applied to Yongdam dam, Soyanggang dam, Chungju dam and Seomjingang dam basins. As results, the higher $R^2s$ are obtained when the shorter recording interval, the better recorded data quality, and the more rainfall events recorded along with certain rainfall amount is. Moreover, when the total rainfall is higher than the certain amount, $R^2$ is high. Considering the facts found from this study for the low flow analysis, it is possible to estimate the parameters for Tank model properly with the desired confidence level.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.1
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• pp.20-27
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• 1987

The hierarchical approach method is proposed to sperate each different time scale sub-systems from linear time invariant multi-parameter singular perturbation systems. By means of this proposal, the original multi-parameter singular perturbation systems is completely separated into independent subsystems with each different time scale. It is also investigated that the controllability of the system is invariant. And this paper applies singular perturbation methods to the minimum control effort problem for linear time invariant systems with constrained controls. Also near-optimum control theory, which is based on dividing the total time interval with the time scales respectively, is proposed. As a result, the time scale separation method is show to be particularly useful in a near optimum design which can be otained through a decentralized control structure.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.129-132
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• 2001

she purpose of this paper is to propose an approach to suppress the vibration of three-mass inertia system based on the LMI theory. and confirm its validity through simulations under the condition of parameter variation. First, the existing $H_{\infty}$ servo problem is modified to a structure to which the LMI theory can be applied by virtue of the interval model principle. By adopting this structure, we can divide given specifications fur the vibration suppression problem into $H_2$and $H_{\infty}$ performance criteria. The results of simulation for the three-mass inertia system show that the proposed design approach is quite effective.

• Communications for Statistical Applications and Methods
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• v.21 no.6
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• pp.521-528
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• 2014

A stochastic Gompertz diffusion model for tumor growth is a topic of active interest as cancer is a leading cause of death in Korea. The direct maximum likelihood estimation of stochastic differential equations would be possible based on the continuous path likelihood on condition that a continuous sample path of the process is recorded over the interval. This likelihood is useful in providing a basis for the so-called continuous record or infill likelihood function and infill asymptotic. In practice, we do not have fully continuous data except a few special cases. As a result, the exact ML method is not applicable. In this paper we proposed a method of parameter estimation of stochastic Gompertz differential equation via Markov chain Monte Carlo methods that is applicable for several data structures. We compared a Markov transition data structure with a data structure that have an initial point.

• Journal of Animal Reproduction and Biotechnology
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• v.34 no.3
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• pp.166-172
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• 2019

Heart rate is a relatively simple and non-invasive method that is used as an important physiological indicator in many studies and has a close relationship with heart structure and function, cardiovascular disease and sudden cardiac death. In general, appropriately low heart rate during resting means effective heart function and cardiovascular fitness; heart rate at recovery is an important indicator of health and disease condition. We found a beagle dog (Dog_1) with a high heart rate in the previous preliminary experiment. Therefore, purpose of this study was to compare the heart rate response of the Dog_1 with the control group during 12 weeks of interval exercise, to evaluate the structural and functional abnormalities of the heart and to verify the applicability of exercise program. Heart rate was checked during 12 weeks of interval exercise, and after the exercise was over, imaging examination and hematological and serum biochemistry were performed. As a result, Dog_1 (165.6 ± 1.5) showed significantly higher heart rate in low intensity session of interval exercise than control group (133.3 ± 0.5, p < 0.01). In addition, Dog_1 (181.2 ± 1.4) showed significantly higher heart rate than control group (155.1 ± 0.9) in high intensity session (p < 0.01). The heart rate (30 sec, 60 sec) during recovery state was higher in Dog_1 (30 sec: 156.8 ± 4.0, 60 sec: 166.8 ± 5.8) than in the control group (30 sec: 111.2 ± 2.5, 60 sec: 104.0 ± 5.1, p < 0.01). The results of the imaging examination of Dog_1 with high heart rate confirmed that the heart had no functional and structural abnormalities. All beagles with the interval exercise program did not show maladjustment, and in the hematological and serum biochemistry results, all the parameter were within the reference range. If the interval exercise program of this study is used in the future, it is expected to be used as an important basic data to achieve the purpose of health, welfare, and physical fitness improvement of dogs.