• Journal of Mechanical Science and Technology
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• 제17권4호
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• pp.484-491
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• 2003

For most of linear time-varying (LTV) systems, it is difficult to design time-varying controllers in analytic way. Accordingly, by approximating LTV systems as uncertain linear time-invariant, control design approaches such as robust control have been applied to the resulting uncertain LTI systems. In particular, a robust control method such as quantitative feedback theory (QFT) has an advantage of guaranteeing the frozen-time stability and the performance specification against plant parameter uncertainties. However, if these methods are applied to the approximated linear. time-invariant (LTI) plants with large uncertainty, the resulting control law becomes complicated and also may not become ineffective with faster dynamic behavior. In this paper, as a method to enhance the fast dynamic performance of LTV systems with bounded time-varying parameters, the approximated uncertainty of time-varying parameters are reduced by the proposed QFT parameter-scheduling control design based on radial basis function (RBF) networks.

• 한국정밀공학회지
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• 제17권12호
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• pp.176-184
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• 2000

TDC(Time Delay Control) deals with the time-varying system parameters, unknown dynamics and unexpected disturbances using time delay. TDC can be divided into two separate parts: an auxiliary controller and a servo controller. The two controllers can be designed independently. The auxiliary controller is used to reduce sensitivity to parameter variations, nonlinear effects, and other disturbances. The servo controller is to reduce the error between the desired command and output. We propose the model-following time delay controller with modified error feedback controller. This was applied to follow the desired reference model for the uncertain time-varying overhead crane. The model generates the damped-out swinging motion trajectory to suppress the swinging motion caused by the acceleration and the deceleration of crane transportation. The control performance was evaluated through simulations. The theoretical results indicate that this control method shows excellent performance to an overhead crane with the uncertain time-varying parameters.

• Structural Engineering and Mechanics
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• 제46권1호
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• pp.19-37
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• 2013

The optimum design of base isolation system considering model parameter uncertainty is usually performed by using the unconditional response of structure obtained by the total probability theory, as the performance index. Though, the probabilistic approach is powerful, it cannot be applied when the maximum possible ranges of variations are known and can be only modelled as uncertain but bounded type. In such cases, the interval analysis method is a viable alternative. The present study focuses on the bounded optimization of base isolation system to mitigate the seismic vibration effect of structures characterized by bounded type system parameters. With this intention in view, the conditional stochastic response quantities are obtained in random vibration framework using the state space formulation. Subsequently, with the aid of matrix perturbation theory using first order Taylor series expansion of dynamic response function and its interval extension, the vibration control problem is transformed to appropriate deterministic optimization problems correspond to a lower bound and upper bound optimum solutions. A lead rubber bearing isolating a multi-storeyed building frame is considered for numerical study to elucidate the proposed bounded optimization procedure and the optimum performance of the isolation system.

• 한국농공학회논문집
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• 제49권6호
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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.

• Structural Engineering and Mechanics
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• 제29권5호
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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.

• Structural Engineering and Mechanics
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• 제88권4호
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• pp.301-309
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• 2023

In this paper, a new modified conjugate gradient (MCG) method is presented which is based on a new gradient regularizer, and this method is used to identify the dynamic load on airfoil structure without and with considering random structure parameters. First of all, the newly proposed algorithm is proved to be efficient and convergent through the rigorous mathematics theory and the numerical results of determinate dynamic load identification. Secondly, using the perturbation method, we transform uncertain inverse problem about force reconstruction into determinate load identification problem. Lastly, the statistical characteristics of identified load are evaluated by statistical methods. Especially, this newly proposed approach has successfully solved determinate and uncertain inverse problems about dynamic load identification. Numerical simulations validate that the newly developed method in this paper is feasible and stable in solving load identification problems without and with considering random structure parameters. Additionally, it also shows that most of the observation error of the proposed algorithm in solving dynamic load identification of deterministic and random structure is respectively within 11.13%, 20%.

• 한국해양공학회지
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• 제11권1호
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• pp.36-43
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• 1997

Weld bead shape is an important measure for evaluation of weld quality. Many welding parameters have influence on the weld bead shape. The quantitative relationship between welding parameters and bead shape, however, is not determined yet because of their high complexity and many unknown factors. Fuzzy expert system is an advanced expert system which uses fuzzy rules and approximate reasoning. It is a vert useful tool for welding technology because is can process rationally the uncertain and inexact information such as the welding information. In this paper, the empirical and the qualitative relationship between welding parameters and bead shape are analyzed and represented by fuzzy rules. They are converted to the quantitative relationship by use of approximate reasoning of fuzzy expert system. Weld bead shape is estimated from the welding parameters using fuzzy expert system. The result of comparison between measured values of weld bead by welding experiments and the estimates values by fuzzy expert system shows a good consistancy.

• Structural Engineering and Mechanics
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• 제70권1호
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• pp.81-96
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• 2019

In this paper, a hybrid uncertain model is applied to system reliability based design optimization (RBDO) of trusses. All random variables are described by random distributions but some key distribution parameters of them which lack information are defined by variation intervals. For system RBDO of trusses, the first order reliability method, as well as monotonicity analysis and the branch and bound method, are utilized to determine the system failure probability; and Improved (${\mu}+{\lambda}$) constrained differential evolution (ICDE) is employed for the optimization process. System reliability assessment of several numerical examples and system RBDO of different truss structures are proposed to verify our results. Moreover, the effect of different classes of interval distribution parameters on the optimum weight of the structure and the reliability index are also investigated. The results indicate that the weight of the structure is increased by increasing the uncertainty level. Moreover, it is shown that for a certain random variable, the optimum weight is more increased by the translation interval parameters than the rotation ones.

• Structural Engineering and Mechanics
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• 제75권4호
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• pp.519-527
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• 2020

Dynamic analysis of a vehicle-track coupling system is important to structural design, damage detection and condition assessment of the structural system. Deterministic analysis of the vehicle-track coupling system has been extensively studied in the past, however, the structural parameters of the coupling system have uncertainties in engineering practices. It is essential to treat the parameters of the vehicle-track coupling system with consideration of uncertainties. In this paper, a method for predicting the bounds of the vehicle-track coupling system responses with uncertain parameters is presented. The uncertain system parameters are modeled as fuzzy variables instead of conventional random variables with known probability distributions. Then, the dynamic response functions of the coupling system are transformed into a component function based on the high dimensional representation approximation. The Lagrange interpolation method is used to approximate the component function. Finally, the bounds of the system's dynamic responses can be predicted by using Monte Carlo method for the interpolation polynomials of the Lagrange interpolation function. A numerical example is introduced to illustrate the ability of the proposed method to predict the bounds of the system's dynamic responses, and the results are compared with the direct Monte Carlo method. The results show that the proposed method is effective and efficient to predict the bounds of the system's dynamic responses with fuzzy variables.

• 한국지능시스템학회논문지
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• 제17권2호
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• pp.185-189
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• 2007

본 연구에서는 T-S 퍼지시스템으로 모델된 불확실한 시변 파라메터를 갖는 비선형 시스템의 고장검출 시스템 설계법을 제안한다. 이를 위하여 퍼지시스템에 대한 소인수 분해를 정의하고 좌 소인수를 이용하여 오차발생기를 설계한다. 오차발생기의 출력으로부터 고장검출을 판정하는 검출기준을 제시한다. 제시된 방법의 효용성을 입증하기 위하여 역도립 진자시스템에 적용하여 컴퓨터 모의실험을 수행한다.