• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.133-136
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• 1999

Many researches on the identification of a system have been carried out using a least square method, an adaptive filter, and so on. However, it is difficult to apply these methods in a nonlinear system. In the case of a nonlinear system, it is known that the signal compression method is able to estimate uncertain parameters of linear element in a nonlinear system because it is able to separate linear element and nonlinear element in a nonlinear system. However, the signal compression method cannot be applied to a motion simulator because actuators of the simulator is single-rod cylinders which includes expansion and compression dynamic properties. Therefore, this paper proposes a modified signal compression method which is able to estimate uncertain parameters of the motion simulator dynamics. The dynamic properties of this system are identified by separating expansion and compression properties when applying the signal compression method. And then, the identified parameters are applied to design a sliding mode controller for the simulator. The performance of the designed sliding mode controller is evaluated experimentally.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.16 no.4
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• pp.401-406
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• 2003

This paper deals with stress analysis of single-lap adhesive joints which have uncertain material properties. Basically, material properties have a certain amount of scatter and such uncertainties can affect the performance of joints. In this paper, the convex modeling is introduced to consider such uncertainties in calculating peel and shear stress of adhesive joints and the results are compared with those from the Monte Carlo simulation. Numerical results show that stresses increase when uncertainties considered, which indicates that such uncertainties should not be ignored for estimation of structural safety. Also, the results obtained by the convex modeling and the Monte Carlo simulation show good agreement, which demonstrates the effectiveness of convex modeling.

• Journal of the Korea institute for structural maintenance and inspection
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• v.11 no.4
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• pp.138-146
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• 2007

Geotechnical performance at the soft ground is strongly dependent on the properties of the soil beneath and adjacent to the structure of interest. These soil properties can be described using deterministic and/or probabilistic models. Deterministic models typically use a single discrete descriptor for the parameter of interest. Probabilistic models describe parameters by using discrete statistical descriptors or probability distribution density functions. The consolidation process depends on several uncertain parameters including the coefficients of consolidation and coefficients of permeability in vertical and horizontal directions. The implication of this uncertain parameter in the design of prefabricated vertical drains for soil improvement is discussed. A sensitivity analysis of the degree of consolidation and calculation of settlements to these uncertain parameters is presented for clayey deposits.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.6
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• pp.93-101
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• 2007

In general, geotechnical properties have many uncertain aspects, thus probabilistic analysis have been used to consider these aspects. It is, however, quite difficult to select an appropriate target probability for a certain structure or construction process. In this study, minimum expected cost design method based on probabilistic analysis is suggested for design of vertical drains generally used to accelerate consolidation in soft clayey soils. A sensitivity analysis is performed to select the most important uncertain parameters for the design of vertical drains. Monte Carlo simulation is used in sensitivity analysis and probabilistic analysis. Total expected cost, defined as the sum of initial cost and expected additive cost, varies widely with variation of input parameters used in design of vertical drain systems. And probability of failure to get the minimum total expected cost varies under the different design conditions. A minimum value of total expected cost is suggested as a design value in this study. The proposed design concept is applicable to unit construction process because this approach is to consider the uncertainties using probabilistic analysis and uncertainties of geotechnical properties.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.4
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• pp.240-250
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• 2015

The development of the control algorithms for under-actuated systems is important. Decoupled sliding mode control has been successfully employed to control under-actuated systems in a decoupling manner with the use of sliding mode control. However, in such a control scheme, the system functions must be known. If there are uncertainties in those functions, the control performance may not be satisfactory.In this paper, the direct adaptive fuzzy sliding mode control is employed to control a class of under-actuated uncertain systems which can be regarded as a combination of several subsystems with one same control input. By using the hierarchical sliding control approach, a sliding control law is derived so as to make every subsystem stabilized at the same time. But, since the system considered is assumed to be uncertain, the sliding control law cannot be readily facilitated. Therefore, in the study, based on Lyapunov stable theory a fuzzy compensator is proposed to approximate the uncertain part of the sliding control law. From those simulations, it can be concluded that the proposed compensator can indeed cope with system uncertainties. Besides, it can be found that the proposed compensator also provide good robustness properties.

• Structural Engineering and Mechanics
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• v.32 no.1
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• pp.1-20
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• 2009

The present contribution addresses uncertainty quantification and uncertainty propagation in structural mechanics using stochastic analysis. Presently available procedures to describe uncertainties in load and resistance within a suitable mathematical framework are shortly addressed. Monte Carlo methods are proposed for studying the variability in the structural properties and for their propagation to the response. The general applicability and versatility of Monte Carlo Simulation is demonstrated in the context with computational models that have been developed for deterministic structural analysis. After discussing Direct Monte Carlo Simulation for the assessment of the response variability, some recently developed advanced Monte Carlo methods applied for reliability assessment are described, such as Importance Sampling for linear uncertain structures subjected to Gaussian loading, Line Sampling in linear dynamics and Subset simulation. The numerical example demonstrates the applicability of Line Sampling to general linear uncertain FE systems under Gaussian distributed excitation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.113-118
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• 2009

A designer regards the vibration system as a linear system. However, in real world, nonlinearity of a vibration system should exist caused by various factors like manufacturing conditions or uncertain material properties. So, properties of a spring and a damper which are consisting the vibration system have statistical distribution. Therefore, a designer needs to analyze the statistical nonlinearity in a vibration system. In this paper, $1^{st}$ Taylor series expansion method and univariate dimension reduction method apply to a performance measure of nonlinear vibration system, and compare each result. And then, merits and demerits of each method are discussed. For apply more actual problem, a performance measure population is estimated based on design variable samples like properties of spring or damper.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.1 s.173
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• pp.259-268
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• 2000

Because of their superior mechanical properties to isotropic materials, composite laminated plates are used for many structural applications that require high stiffness-to-weight and strength-to-weight ratios. Composite materials are always subject to a certain amount of scatter in their elastic moduli, but most analyses and designs with the materials are usually conducted by assuming that the material properties are fixed and have no uncertainties. In this paper, a convex modeling approach is introduced to take account of such uncertainties in elastic moduli. It is used with the finite element method to predict the onset of failures in composite laminated plates subject to in-plane loading. Numerical results show that failures begin at the smaller load when the uncertainties of elastic moduli considered and therefore, such uncertainties should be considered at the design stage for the safety and reliability of the structures.

• Structural Engineering and Mechanics
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• v.38 no.4
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• pp.503-516
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• 2011

Uncertainty in concrete properties, including concrete modulus of elasticity and modulus of rupture, are predicted by developing a microstructural homogenization model. The homogenization model is developed by analyzing a concrete representative volume element (RVE) using the finite element (FE) method. The concrete RVE considers concrete as a three phase composite material including: cement paste, aggregate and interfacial transition zone (ITZ). The homogenization model allows for considering two sources of variability in concrete, randomly dispersed aggregates in the concrete matrix and uncertain mechanical properties of composite phases of concrete. Using the proposed homogenization technique, the uncertainty in concrete modulus of elasticity and modulus of rupture (described by numerical cumulative probability density function) are determined. Deflection uncertainty of reinforced concrete (RC) beams, propagated from uncertainties in concrete properties, is quantified using Monte Carlo (MC) simulation. Cracked plane frame analysis is used to account for tension stiffening in concrete. Concrete homogenization enables a unique opportunity to bridge the gap between concrete materials and structural modeling, which is necessary for realistic serviceability prediction.

• International Journal of Aeronautical and Space Sciences
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• v.4 no.2
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• pp.9-16
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• 2003

Piezoelectric materials are widely used to construct smart or adaptive structures. Although extensive efforts have been devoted to the analysis of piezoelectric materials in recent years, most researches have been conducted by assuming that the material properties are fixed and have no uncertainties. Intrinsically, material properties have a certain amount of scatter and such uncertainties can affect the performance of component. In this paper, the convex modeling is used to consider such uncertainties in calculating the crack extension force of piezoelectric material and the results are compared with the one obtained via the Monte Carlo simulation. Numerical results show that crack extension forces increase when uncertainties considered, which indicates that such uncertainties should not be ignored for reliable lifetime prediction. Also, the results obtained by the convex modeling and the Monte Carlo simulation show good agreement, which demonstrates the effectiveness of the convex modeling.