• Communications of the Korean Mathematical Society
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• v.17 no.1
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• pp.155-163
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• 2002

The purpose of this paper is to establish discrete versions of the well-known Lyapunov's stability theorem and LaSalle's invariance theorem for a non-autonomous discrete dynamical system. Our proofs for these theorems are constructive in the sense that they are made by explicitly building a Lyapunov function for the system. A comparison between non-autonomous discrete dynamical systems and continuous dynamical systems is conducted.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.420-420
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• 2000

In this paper, we propose an adaptive controller using RBFN(radial basis function network) for robot manipulators The structure of the proposed controller consists of a RBFN and VSC-1 ike control. RBFN is used in order to approximate かon system, and VSC-like control to guarantee robustness On the basis of the Lyapunov stability theorem, we guarantee the stability for the total system. And the learning law of RBFN is established by the Lyapunov method, Finally, we apply the proposed controller to tracking control for a 2 link SCARA type robot manipulator.

• Journal of Power Electronics
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• v.17 no.4
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• pp.983-990
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• 2017

This paper proposes a model predictive control based on the discrete Lyapunov function to improve the performance of power electronic converters. The proposed control technique, based on the finite control set model predictive control (FCS-MPC), defines a cost function for the control law which is determined under the Lyapunov stability theorem with a control error compensation. The steady state and dynamic performance of the proposed control strategy has been tested under a single phase AC/DC voltage source rectifier (S-VSR). Experimental results demonstrate that the proposed control strategy not only offers global stability and good robustness but also leads to a high quality sinusoidal current with a reasonably low total harmonic distortion (THD) and a fast dynamic response under linear loads.

• International Journal of Aeronautical and Space Sciences
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• v.9 no.2
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• pp.71-78
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• 2008

New formation flight controller for unmanned aerial vehicles is proposed. A behavioral decentralized control approach called formation geometry center control is adopted. Trajectory tracking as well as formation geometry keeping are the purpose of the formation flight, and therefore two controllers are designed: a trajectory tracking controller for reference trajectory tracking, and a position controller for formation geometry keeping. Each controller is designed using Lyapunov stability theorem to guarantee the asymptotic stability. Formation flight controller is finally obtained by combining the trajectory tracking controller and the formation geometry keeping controller using a weighting parameter that depends on the relative distance error between unmanned aerial vehicles. Numerical simulations are performed to validate the performance of the proposed controller.

• Journal of Multimedia Information System
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• v.8 no.2
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• pp.131-142
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• 2021

This paper traces the process of constructing a new one-dimensional chaotic map, and will provide a simple application in color image encryption. The use of Sarkovskii's theorem will make it possible to determine the existence of chaos and restrict all conditions to ensure the existence of this new sequence. In addition, the sensitivity to initial conditions will be proved by Lyapunov's index value. Similarly, the performance of this new chaotic map will be illustrated graphically and compared with other chaotic maps most commonly used in cryptography. Finally, a humble color image encryption application will show the power of this new chaotic map.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.9
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• pp.1461-1467
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• 2001

This paper proposes a new approach for the ant-swing control of overhead cranes. The proposed control consists of a model-based anti-swing control scheme and a practical path planning scheme. The anti-swing control scheme is designed based on the Lyapunov stability theorem; the proposed control does not require the usual constraints of small load mass, small load swing, slow hoisting speed, and small hoisting distance, but guarantees asymptotic stability while keeping all internal signals bounded. The path planning scheme is designed based on the concepts of minimum-time control and anti-swing control; the proposed path planning generates near-minimum-time trajectories independently of hoisting speed and distance. The effectiveness of the proposed control is shown by computer simulation.

• Journal of applied mathematics & informatics
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• v.32 no.5_6
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• pp.807-816
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• 2014

The asymptotic behavior of solutions of Lyapunov type matrix Volterra integro differential equation, in which the coefficient matrices are not stable, is studied by the method of reduction.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.2
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• pp.92-97
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• 2000

The Lyapunov stability theorem is used to derive a control law that can be used to control the spacing between vehicles in a platoon. A third order system is adopted to model the vehicle and power-train dynamics. In addition, the concept of

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.720-723
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• 1999

For that the attitude control performance test of the satellite, dynamic analysis of satellite structure performed in reference with KOREASAT, and the equation of motion of rigid bodies was derivated. For attitude stability, Lyapunov's stability theorem and state space expression were applied to dynamic equation of satellite. To prove efficiency of our method, simulations are performed and result are shown.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.11
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• pp.1033-1039
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• 2007

In this paper, we design a terminal sliding mode controller based on self-recurrent wavelet neural network (SRWNN) for the second-order nonlinear systems with model uncertainties. The terminal sliding mode control (TSMC) method can drive the tracking errors to zero within finite time in comparison with the classical sliding mode control (CSMC) method. In addition, the TSMC method has advantages such as the improved performance, robustness, reliability and precision. We employ the SRWNN to approximate model uncertainties. The weights of SRWNN are trained by adaptation laws induced from Lyapunov stability theorem. Finally, we carry out simulations for Duffing system and the wing rock phenomena to illustrate the effectiveness of the proposed control scheme.