• International Journal of Reliability and Applications
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• v.5 no.2
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• pp.59-74
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• 2004

There are many uncertain parameters associated with vibration components. Their physical parameters, the machining quality of vibration components, and the applied load acting on them are all uncertain. As a result, the natural frequency and the fatigue limits are also uncertain variables. In this paper, we express these parameters of vibration components and the frequency zone of resonance through interval models; this way, the robust reliability of the vibration components is defined. The robust reliability model measures and assesses the reliability of vibration components. The robust reliability of a cantilever beam is evaluated as an example. The results show that this method is reasonable for robust reliability analysis of vibration components because it does not require a large amount of failure data, it avoids the evaluation of the probability density function, and the computation is simple.

• Structural Engineering and Mechanics
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• v.16 no.3
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• pp.327-340
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• 2003

Variations in system parameters due to uncertainties of parameters may result in system performance deterioration and create system internal stability problems. Uncertainties in structural modeling of structures are often considered to ensure that the control system is robust with respect to response errors. So the uncertain concept plays an important role in the analysis and design of the engineering structures. In this paper, the active control of the intelligent structures with the uncertainties is studied and a new method for analyzing the robustness of systems with the uncertainties is presented. Firstly, the system with uncertain parameters is considered as the perturbation of the system with deterministic parameters. Secondly, the feedback control law is designed on the basis of deterministic system. Thirdly, perturbation analysis and robustness analysis of intelligent structures with uncertainties are discussed when the feedback control law is applied to the original system and perturbed system. Combining the convex model of uncertainties with the finite element method, the analysis theory of the robustness of intelligent structures with the uncertainties can be developed. The description and computation of the robustness of intelligent structures with uncertain parameters is obtained. Finally, a numerical example of the application of the present method is given to show the validity of the method.

• Proceedings of the SAREK Conference
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• 2006.06a
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• pp.369-374
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• 2006

Quantification of infiltration rate is an important issue in HVAC system design. The infiltration in buildings depends on many uncertain parameters that vary with significant magnitude and hence, the results from standard deterministic simulation approach can be unreliable. The authors utilize uncertainty analysis In predicting the airflow rates. The paper presents relevant uncertain parameters such as meteorological data, building parameters (leakage areas of windows, doors, etc.), etc. Uncertainties of the aforementioned parameters are quantified based on available data from literature. Then, the Latin Hypercube Sampling (LHS) method was used for the uncertainty propagation. The LHS is one of the Monte Carlo simulation techniques that is suited for our needs. The CONTAMW was chosen to simulate infiltration phenomena in a residential apartment that is typical of residential buildings in Korea. It will be shown that the uncertainty propagating through this process is not negligible and may significantly influence the prediction of the airflow rates.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.3
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• pp.280-289
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• 2008

This paper presents design of the quantitative feedback control system of the three axes hydraulic road simulator with respect to the dummy wheel for uncertain multiple input-output(MIMO) feedback systems. This simulator has the uncertain parameters such as fluid compressibility, fluid leakage, electrical servo components and nonlinear mechanical connections. This works have reproduced the random input signal to implement the real road vibration's data in the lab. The replaced $m^2$ MISO equivalent control systems satisfied the design specifications of the original $m^*m$ MIMO control system and developed the mathematical method using quantitative feedback theory based on schauder's fixed point theorem. This control system illustrates a tracking performance of the closed-loop controller with low order transfer function G(s) and pre-filter F(s) having the minimum bandwidth for parameters of uncertain plant. The efficacy of the designed controller is verified through the dynamic simulation with combined hydraulic model and Adams simulator model. The Matlab simulation results to connect with Adams simulator model show that the proposed control technique works well under uncertain hydraulic plant system. The designed control system has satisfied robust performance with stability bounds, tracking bounds and disturbance. The Hydraulic road simulator consists of the specimen, hydraulic pump, servo valve, hydraulic actuator and its control equipments

• Journal of the Korean Data and Information Science Society
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• v.18 no.3
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• pp.689-696
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• 2007

This paper considers a Bayesian approach to determine an optimal PM policy with random maintenance quality. Thus, we assume that the quality of a PM action is a random variable following a probability distribution. When the failure time is Weibull distribution with uncertain parameters, a Bayesian approach is established to formally express and update the uncertain parameters for determining an optimal PM policy. Finally, the numerical examples are presented for illustrative purpose.

• Industrial Engineering and Management Systems
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• v.15 no.2
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• pp.156-172
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• 2016

Complex and uncertain issues in supply chain result in integrated decision making processes in supply chains. So decentralized (distributed) decision making (DDM) approach is considered as a crucial stage in supply chain planning. In this paper, an uncertain DDM through coordination mechanism is addressed for a multi-product supply chain planning problem. The main concern of this study is comparison of DDM approach with centralized decision making (CDM) approach while some parameters of decision making are assumed to be uncertain. The uncertain DDM problem is modeled through fuzzy mathematical programming in which products' demands are assumed to be uncertain and modeled using fuzzy sets. Moreover, a CDM approach is customized and developed in presence of fuzzy parameters. Both approaches are solved using three fuzzy mathematical optimization methods. Hence, the contribution of this paper can be summarized as follows: 1) proposing a DDM approach for a multi-product supply chain planning problem; 2) Introducing a coordination mechanism in the proposed DDM approach in order to utilize the benefits of a CDM approach while using DDM approach; 3) Modeling the aforementioned problem through fuzzy mathematical programming; 4) Comparing the performance of proposed DDM and a customized uncertain CDM approach on multi-product supply chain planning; 5) Applying three fuzzy mathematical optimization methods in order to address and compare the performance of both DDM and CDM approaches. The results of these fuzzy optimization methods are compared. Computational results illustrate that the proposed DDM approach closely approximates the optimal solutions generated by the CDM approach while the manufacturer's and retailers' decisions are optimized through a coordination mechanism making lasting relationship.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.18 no.3
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• pp.291-302
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• 2005

Due to the importance of the parameter in structural response, the uncertain elastic modulus was located at the center of stochastic analysis, where the response variability caused by the uncertain system parameters is pursued. However when we analyze the so-called stochastic systems, as many parameters as possible must be included in the analysis if we want to obtain the response variability that can reach a true one, even in an approximate sense. In this paper, a formulation to determine the statistical behavior of in-plane structures due to multiple uncertain material parameters, i.e., elastic modulus and Poisson's ratio, is suggested. To this end, the polynomial expansion on the coefficients of constitutive matrix is employed. In constructing the modified auto-and cross-correlation functions, use is made of the general equation for n-th moment. For the computational purpose, the infinite series of stochastic sub-stiffness matrices is truncated preserving required accuracy. To demons4rate the validity of the proposed formulation, an exemplary example is analyzed and the results are compared with those obtained by means of classical Monte Carlo simulation, which is based on the local averaging scheme.

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.54-67
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• 2003

In this paper, a novel estimation technique for a robust adaptive control scheme is presented for a class of uncertain nonlinear systems with a general set of uncertainty. For a class of introduced more extended semi-strict feedback forms which generalize the systems studied in recent years, a novel estimation technique is proposed to estimate the states of the fully nonlinear unmodeled dynamics without stringent conditions. With the introduction of powerful functions, the estimation error can be tuned to a desired small region around the origin via the estimator parameters. In addition, with some effective functions, a modified adaptive backstepping for dynamic uncertainties is presented to drive the output to an arbitrarily small region around the origin by an appropriate choice of the design parameters. With our proposed schemes, we can remove or relax the assumptions of the existing results.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1210-1215
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• 1990

This paper deals with the fault diagnosis problem in uncertain linear systems having undermodelling, linearization errors and noise inputs. The new approach proposed in this paper uses an appropriate test variable and the difference between system parameters which are estimated by the least squares method to locate the fault. The singular value decomposion is used to decouple the correlation between the estimated system parameters and to observe the trend of parameter changes. Some simulations applied to aircraft ergines show good allocation of the fault even though the system model has significant uncertainties. The feature of the approach is to diagnose the uncertain system through simple parameter operations and not to need complex calculations in the diagnosis procedure as compared with other methods.

• Interaction and multiscale mechanics
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• v.1 no.1
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• pp.103-121
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• 2008

This paper presents an optimization-based method for computing a minimal bounding ellipsoid that contains the set of static responses of an uncertain braced frame. Based on a non-stochastic modeling of uncertainty, we assume that the parameters both of brace stiffnesses and external forces are uncertain but bounded. A brace member represents the sum of the stiffness of the actual brace and the contributions of some non-structural elements, and hence we assume that the axial stiffness of each brace is uncertain. By using the $\mathcal{S}$-lemma, we formulate a semidefinite programming (SDP) problem which provides an outer approximation of the minimal bounding ellipsoid. The minimum bounding ellipsoids are computed for a braced frame under several uncertain circumstances.