• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.6
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• pp.1-6
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• 2000

In this paper, the problem of the stability analysis for linear neutral delay-differential systems with nonlinear perturbations is investigated. Using Lyapunov second method, a new delay-dependent sufficient condition for asymptotic stability of the systems in terms of linear matrix inequalities (LMIs), which can be easily solved by various convex optimization algorithms, is presented. A numerical example is given to illustrate the proposed method.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.496-498
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• 2005

This paper presents intelligent digital redesign method of global approach for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent the complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also by using the power series, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs).

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.62.4-62
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• 2001

In this paper, we propose a delay-dependent guaranteed cost controller design method for uncertain linear systems with time delay. The uncertainty is norm bounded and time-varying. A quadratic cost function is considered as the performance measure for the given system. Based on the Lyapunov method, sufficient condition, which guarantees that the closed-loop system is asymptotically stable and the upper bound value of the closed-loop cost function is not more than a specied one, is derived in terms of Linear Matrix Inequalities(LMIs) that can be solved sufficiently. A convex optimization problem can be formulated to design a guaranteed cost controller, which minimizes the upper bound value of the cost function. Numerical examples show the activeness of the proposed method.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.4
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• pp.1-10
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• 2000

This paper deals with an H$_{\infty}$ output feedback control problem for linear systems with commensurate time delay in both state and input variables. The proposed output feedback controller also has commensurate time delay terms in the controller state. The controller can be synthesized based on the solution of the linear matrix inequalities(LMI) which can be easily solved using the convex optimization method. In order to demonstrate the efficacy of the proposed method, numerical examples are presented.

• ETRI Journal
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• v.31 no.1
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• pp.86-88
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• 2009

In this letter, we consider an m-node tandem queue (queues in series) with a Poisson arrival process and either deterministic or non-overlapping service times. With the assumption that each node has a finite buffer except for the first node, we show the non-increasing convex property of stationary waiting time with respect to the finite buffer capacities. We apply it to an optimization problem which determines the smallest buffer capacities subject to probabilistic constraints on stationary waiting times.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.3
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• pp.86-92
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• 1998

This paper deals with an output feedback H control problem for linear time ivariant systems with state delay. The proposed output feedback controller is represented by the lower linear fractional transformation of alinear time invariant system and a delay operator. Sufficient conditions for the existence of the output feedback controller are given in the form of linear matrix inequalities which are less conservative than those for the existence of a rational output feedback controler. We also present a numerical example to demonstrate the efficacy of the proposed method.of the proposed method.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.4
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• pp.83-100
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• 2008

We propose a new aggressive formulation of cross-efficiency in Data Envelopment Analysis(DEA). In the traditional aggressive formulation, the efficiency score of a test DMU is maximized as the first goal while an average of efficiency scores of peer DMUs is minimized as the second goal. The proposed model replaces the second goal with the minimization of the best efficiency score of peer DMUs. We showed the model is a quasi-convex optimization problem, and for a solution method we developed a bisection method whose computational complexity is polynomial-time. We tested the model on 200 randomly generated DEA problems, and compared it with the traditional model in terms of various criteria. The experimental results confirmed the effectiveness and usefulness of the proposed model.

• East Asian mathematical journal
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• v.5 no.1
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• pp.95-110
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• 1989

In a general variance component model, nonnegative quadratic estimators of the components of variance are considered which are invariant with respect to mean value translaion and have minimum bias (analogously to estimation theory of mean value parameters). Here the minimum is taken over an appropriate cone of positive semidefinite matrices, after having made a reduction by invariance. Among these estimators, which always exist the one of minimum norm is characterized. This characterization is achieved by systems of necessary and sufficient condition, and by a cone restricted pseudoinverse. In models where the decomposing covariance matrices span a commutative quadratic subspace, a representation of the considered estimator is derived that requires merely to solve an ordinary convex quadratic optimization problem. As an example, we present the two way nested classification random model. An unbiased estimator is derived for the mean squared error of any unbiased or biased estimator that is expressible as a linear combination of independent sums of squares. Further, it is shown that, for the classical balanced variance component models, this estimator is the best invariant unbiased estimator, for the variance of the ANOVA estimator and for the mean squared error of the nonnegative minimum biased estimator. As an example, the balanced two way nested classification model with ramdom effects if considered.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.11
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• pp.2103-2108
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• 2011

In this paper, the problem of passivity analysis for neural networks with time-varying delays and norm-bounded parameter uncertainties is considered. By constructing a new augmented Lyapunov functional, a new delay-dependent passivity criterion for the network is established in terms of LMIs (linear matrix inequalities) which can be easily solved by various convex optimization algorithms. Two numerical example are included to show the effectiveness of proposed criterion.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.9
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• pp.1809-1814
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• 2009

In this paper, the problem of stability analysis for neural networks with discrete and distributed time-varying delays is considered. By constructing a new Lyapunov functional, a new delay-dependent stability criterion for the network is established in terms of LMIs (linear matrix inequalities) which can be easily solved by various convex optimization algorithms. Two numerical example are included to show the effectiveness of proposed criterion.