• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.994-996
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• 1998

In this paper, the standard Dole, Glover, Khargoneker, and Francis (abbr. : DGKF 1989) $H_{\infty}$ controller $(H_{\infty}C)$ is extended to the nonlinear feedback linearization-$H_\infty$-based sliding mode controller (NFL-$H_\infty$-based SMC). A stability proof of the closed-loop stability is done by a Lyapunov function candidate using an addition form of the sliding surface vector and the estimation error.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.463-465
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• 1998

In this paper, we consider the problem of robust stability of large-scale uncertain linear systems with time-varying delays. The considered uncertainties are both unstructured uncertainty which is only known its norm bound and structured uncertainty which is known its structure. Based on Lyapunov stability theorem and $H_{\infty}$ theory. we present uncertainty upper bound that guarantee the robust stability of systems. Especially, robustness bound are obtained directly without solving the Lyapunov equation. Finally, we show the usefulness of our results by numerical example.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.265-270
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• 2001

In this paper, a robust controller is proposed to control a robot manipulator which is governed by highly nonlinear dynamic equations. The controller is computationally efficient since it does not require the dynamic model or parameter values of a robot manipulator. It, however, requires uncertainty bounds which are derived by using properties of revolute joint robot dynamics. The stability of the robot with the controller is proved by using Lyapunov's direct method. The results of computer simulations also show that the robot system is stable, and has excellent trajectory tracking performance.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.7
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• pp.29-36
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• 1998

In this paper we propose a control law using a Lyapunov-like function that makes stable the systems which have mis-matched uncertainties. The existing control law using a Lyapunov-like function, which gives global saymptotic stability, is designed under the assumption of a targetsystem to be stable locally. But we broaden here the class of target systems by designing the control law which can give uniform ultimate boundedness to even the systems not satisfing the locally asymptotic stability. And we also show that the control law giving global asymptotic stability can be designed more systematically through using the uniform ultimate boundedness.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.5
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• pp.29-34
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• 2002

This study presents the process of the continuous-time system identification for unknown nonlinear systems. The Radial Basis Function(RBF) error filtering identification model is introduced at first. This identification scheme includes RBF network to approximate unknown function of nonlinear system which is structured by affine form. The neural network is trained by the adaptive law based on Lyapunov synthesis method. The identification scheme is applied to engine and the performance of RBF error filtering Identification model is verified by the simulation with a three-state engine model. The simulation results have revealed that the values of the estimated function show favorable agreement with the real values of the engine model. The introduced identification scheme can be effectively applied to model-based nonlinear control.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.5
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• pp.615-621
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• 1999

In this paper, we consider the robust stability of uncertain linear systems with time-delay in the time domain. The considered uncertainties are both the unstructured uncertainty which is only Known its norm bound and the structured uncertainty which is known its structured. Based on Lyapunov stability theorem and{{{{ { H}_{$\infty$ } }}}} theory known as Strictly Bounded Real Lemma (SBRL), we present new conditions that guarantee the robust stability of system. Also, we extend this to multiple time-varying delays systems and large-scale systems, respectively. Finally, we show the usefulness of our results by numerical examples.

• Journal of Ocean Engineering and Technology
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• v.19 no.5 s.66
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• pp.58-64
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• 2005

In this paper, a feedback linearizing anti-sway control law, using a 2-D model for container cranes, is investigated. The equations of motion are first derived from Lagrange's equation. Then, by substituting the sway dynamics into the trolley dynamics, a reduction of variables from three (trolley, hoist, sway) to two (trolley, hoist) is pursued. The anti-sway control law is designed based on the Lyapunov stability theorem. The proposed control law guarantees the uniform asymptotic stability of the closed-loop system. The simulation results of the derived control law, using MATLAB/Simulink, are compared with those of the sliding mode control law, noted in previous literature. Also, experimental results using a 3-D pilot crane are provided.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.2
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• pp.376-382
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• 2011

This paper proposes delay-dependent stability conditions of the fuzzy Markovian jumping Hopfield neural networks of neutral type with time-varying delays. By constructing a suitable Lyapunov-Krasovskii's (L-K) functional and utilizing Finsler's lemma, new delay-dependent stability criteria for the systems are established in terms of linear matrix inequalities (LMIs) which can be easily solved by various effective optimization algorithms. A numerical example is given to illustrate the effectiveness of the proposed methods.

• 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.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.16 no.3
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• pp.67-73
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• 2002

This paper presents a sliding mode observer and Controller far the state estimation and the dynamic stabilization of the magnetic levitation systems. The proposed striding mode observer is constructed by means of Lyapunov stability theorem to decrease the observer error, and the sliding rode controller is designed by a linear combination of the equivalent and nonlinear control input for the estimated states. The feasibilities of the suggested design method are illustrated with the simulation results.