• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.131-134
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• 2003

In this paper, we consider the problem of finding the stability region in state space for uncertain linear systems with input saturation. For stability analysis, two Lyapunov functions are chosen. One is for the lineal region and the other is for the saturated legion. Piecewise Lyapunov functions are obtained by solving successive linear matrix inequalites(LMIs) relaxations. A sufficient condition for robust stability is derived in the form of stability region of initial conditions. A numerical example shows the effectiveness of the proposed method.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1998.10a
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• pp.239-244
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• 1998

The environment of the access network service market is characterized by uncertain demand and various competing alternative technologies. In Korea, despite the introduction of competition, dominant Public Network Operator(PNO) still leads the market. Therefore, the decision of PNO has a great impact on the access network evolution. In this paper, we propose an model which aims to reduce risks and both investment and operating costs, to cope with the uncertain demand and technology evolution. We expect this model to provide a tool analyze risks and evaluate various strategies on the network evolution.

• Bulletin of the Korean Mathematical Society
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• v.48 no.4
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• pp.725-736
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• 2011

By using the Lyapunov functional method, stochastic analysis, and LMI (linear matrix inequality) approach, the mean square exponential stability of an equilibrium solution of uncertain stochastic Hopfield neural networks with delayed is presented. The proposed result generalizes and improves previous work. An illustrative example is also given to demonstrate the effectiveness of the proposed result.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.469-471
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• 1999

In this paper, a dynamic output feedback controller design technique for robust decentralized stabilization of uncertain large-scale systems is presented. Based on the Lyapunov method, a sufficient condition for robust stability, is derived in terms of three linear matrix inequalities(LMIs). The solutions of the LMIs can be easily obtained using efficient convex optimization techniques.

• Journal of the Korean Operations Research and Management Science Society
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• v.8 no.1
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• pp.31-40
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• 1983

An uncertain dynamic evolving process has been a continuing challenge to decision problems. The dynamic random variable (drv) changes which characterize such a process are very important for the decision-maker in selecting a course of action in a world that is perceived as uncertain, complex, and dynamic. Using this subjective point prediction algorithm based on a modified recursive filter, the decision-maker becomes to have periodically changing plausible points with the passage of time.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.1
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• pp.9-12
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• 2005

This paper presents an LMI-based method to design sliding mode observers for a class of uncertain systems. Using LIs we derive an existence condition of a sliding mode observer guaranteeing a stable sliding motion. And we give explicit formulas of the observer gain matrices. We also consider sliding mode observer design problems under an α-stability constraint or an LQ performance bound constraint. Finally, we give a numerical design example.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.710-713
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• 1996

This paper deals with the fault detection problem in uncertain linear multivariable systems having both model mismatch and noise. A robust detection presented by Kwon et al.(1994) for SISO systems has been here extended to the multivariable systems are derived. The model mismatch includes here linearization error as well as undermodelling. Comparisons are made with alternative fault detection method which do not account noise. The new method is shown to have good performance.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.3
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• pp.164-169
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• 2001

This paper considers the problem of robust stabilization and disturbance attenuation for a class of uncertain singularly perturbed systems with norm-bounded nonlinear uncertainties. It is shown that the state feedback gain matrices can be determined to guarantee the stability of the closed-loop system for all $\varepsilon$$\in$(0, $\infty$). Based on this key result and some standard Riccati inequality approaches for robust control of singularly perturbed systems, a constructive design procedure is developed.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.57-61
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• 1989

An adaptive control scheme is presented for uncertain systems whose uncertaintiy bounds are expressed as a linear combination of unknown functions of special form. Both the states and the parameter estimate errors of the closed-loop system are proven to be bounded. The regulation errors can be made sufficiently small by adjusting the design parameters. An application of the proposed method to the position control of a simple pendulum is given.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.589-591
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• 1999

In this paper, we consider the robust pole assignment for linear system with time-varying uncertainty. The considered uncertainty is an unstructured uncertainty. Based on Lyapunov stability and linear matrix inequality technique, we present a condition that guarantees the robust pole assignment inside a circular disk and the robust stability of uncertain linear systems. Finally, we show the usefulness of our results by an example.