• Computational Structural Engineering : An International Journal
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• v.1 no.2
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• pp.81-87
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• 2001

A framework for reliability analysis of structural components and systems under conditions of statistical and model uncertainty is presented. The Bayesian parameter estimation method is used to derive the posterior distribution of model parameters reflecting epistemic uncertainties. Point, predictive and bound estimates of reliability accounting for parameter uncertainties are derived. The bounds estimates explicitly reflect the effect of epistemic uncertainties on the reliability measure. These developments are enhance-ments of second-moment uncertainty analysis methods developed by A. H-S. Ang and others three decades ago.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.521-528
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• 2005

The evaluation process of rock mass properties intrinsically contains some uncertainty due to the inhomogeneity of rock mass and the measurement error. Although various empirical methods for the determination of rock mass properties were suggested, there is no way of integrating various information on rock mass properties except averaging. For these reasons, this research introduces evidence theory which can model epistemic uncertainty and yield reasonable rock mass properties through combining various information such as empirical equations, in-situ test results, and so on. Through the application of evidence theory to the real site investigation and in situ experiment results, an interval of deformation modulus, cohesion and friction angle of rock mass were obtained. The ratios between lower and upper bound of those properties ranges from 1.6 to 3.6. Numerical analyses of circular hole using the properties for TYPE-2 rock mass were carried out. The magnitude or size of plastic region and radial displacement in case of lower bound properties is about 4 times larger than that of upper bound properties.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.498-503
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• 1993

In this paper, a robust and reliable H$_{\infty}$ control problem is considered for linear uncertain systems with time-varying norm-bounded uncertainty in the state matrix, which performs well despite of actuator outages. Using linear static state feedback and the quadratic stabilization with H$_{\infty}$-norm bound, a robust and reliable H$_{\infty}$ controller is obtained that stabilizes the plant and guarantees an H$_{\infty}$-norm bound constraint on disturbance attenuation for all admissible uncertainties and normal state as well as faulty state of actuators. It provides a sufficient condition for robust and reliable stabilization with H$_{\infty}$-norm bound. Reliability is guaranteed provided actuator outages only occur within a prespecified subset of actuators.tors.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.1
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• pp.31-35
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• 1999

In this paper, we consider the robust pole assignment and the upper bound of quadratic cost function for the linear systems with time-varying uncertainy. The considered uncertainties are both the norm bounded unstructured case and the structured case that has the matrix polytope type uncertain structure. We derve conditions that guarantee the robust pole assignment inside a disk in the L.H.P. and the robust stability. Also, we derive the upper bound of quadratic cost for thil pole assigned systems. Finally, we show the usefulness of our results by an example.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.115-122
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• 2011

Adaptive arrays suffer from severe performance degradation when there are errors in the steering vector. The DCRCB (doubly constrained robust Capon beamformer) overcomes such a problem, introducing a spherical uncertainty set of the steering vector together with a norm constraint. However, in the standard DCRCB, it is a difficult task to determine the bound for the uncertainty, the radius of the spherical set, such that a near best solution is obtained. A novel beamforming method is presented which has no difficulty of the uncertainty bound setting, employing a recursive search for the steering vector. Though the basic idea of recursive search has been known, the conventional recursive method needs to set a parameter for the termination of the search. The proposed method terminates it by using distances to the signal subspace, without the need for parameter setting. Simulation demonstrates that the proposed method has better performance than the conventional recursive method and than the non-recursive standard DCRCB, even the one with the optimum uncertainty bound.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.332-332
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• 2000

In this paper, a novel sliding mode control with uncertainty adaptation is produced by introducing a virtual state. Because upper bounds of the uncertainty is difficult to know, we estimate these upper bound by using the simple adaptation law and design the novel sliding mode controller. The nominal controller is used the optimal controller to minimize cost function.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.6
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• pp.424-428
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• 2016

A simple new sufficient condition for asymptotic stability of the positive linear time-varying discrete-time systems, with unstructured time-varying uncertainty in delayed states, is established in this paper Compared with previous results that cannot be applied to time-varying systems; the time-varying system and delay time are considered simultaneously in this paper. The proposed conditions are compared with suitable conditions for the typical discrete-time systems. The considerations are illustrated by numerical examples of previous work.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.270-270
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• 2000

Input delay is frequently encountered in the practical systems since measurement delay and computational delay can be represented by input delay. In this viewpoint, this paper deals with the robust control problem of input delayed systems with structured uncertainty. Robust stability conditions are provided in terms of linear matrix inequalities(LMIs) and it is shown that the proposed conditions can give less conservative maximum bound of input delay guaranteeing robust stability.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.348-351
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• 1995

This note proposes a robust LQR method for systems with structured real parameter uncertainty based on Riccati equation approach. Emphasis is on the reduction of design conservatism in the sense of quadratic performance by utilizing the uncertainty structure. The class of uncertainty treated includes all the form of additive real parameter uncertainty, which has the multiple rank structure. To handle the structure of uncertainty, the scaling matrix with block diagonal structure is introduced. By changing the scaling matrix, all the possible set of uncertainty structures can be represented. Modified algebraic Riccati equation (MARE) is newly proposed to obtain a robust feedback control law, which makes the quadratic cost finite for an arbitrary scaling matrix. The remaining design freedom, that is, the scaling matrix is used for minimizing the upper bound of the quadratic cost for all possible set of uncertainties within the given bounds. A design example is shown to demonstrate the simplicity and the effectiveness of proposed method.

• Journal of Advanced Navigation Technology
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• v.23 no.6
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• pp.577-583
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• 2019

A dynamic system is called positive if any trajectory of the system starting from non-negative initial states remains forever non-negative for non-negative controls. In this paper, we consider the new stability condition for the positive time-varying linear discrete interval systems with time-varying delay and unstructured uncertainty. The delay time is considered as time-varying within certain interval having minimum and maximum values and the system is subjected to nonlinear unstructured uncertainty which only gives information on uncertainty magnitude. The proposed stability condition is an improvement of the previous results which can be applied only to time-invariant systems or had no consideration of uncertainty, and they can be expressed in the form of a very simple inequality. The stability conditions are derived using the Lyapunov stability theory and have many advantages over previous results using the upper solution bound of the Lyapunov equation. Through numerical example, the proposed stability conditions are proven to be effective and can include the existing results.