• Journal of applied mathematics & informatics
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• v.31 no.1_2
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• pp.247-262
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• 2013

In this paper, using the time scale calculus theory, we first discuss the permanence of a $n$-species competition system with feedback control on time scales. Based on the permanence result, by the Lyapunov functional method, we establish sufficient conditions for the existence and uniformly asymptotical stability of almost periodic solutions of the considered model. The results of this paper is completely new. An example is employed to show the feasibility of our main result.

• Journal of the Korean Mathematical Society
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• v.37 no.5
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• pp.835-847
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• 2000

We investigate various ${\Phi}$(t)-stability of comparison differential equations and we obtain necessary and/or sufficient conditions for the asymptotic and uniform asymptotic stability of the differential equations x'=f(t, x).

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.197-200
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• 1996

This paper considers feedback error learning neural networks for robot manipulator control. Feedback error learning proposed by Kawato [2,3,5] is a useful learning control scheme, if nonlinear subsystems (or basis functions) consisting of the robot dynamic equation are known exactly. However, in practice, unmodeled uncertainties and disturbances deteriorate the control performance. Hence, we presents a robust feedback error learning scheme which add robustifying control signal to overcome such effects. After the learning rule is derived, the stability is analyzed using Lyapunov method.

• International Journal of Control, Automation, and Systems
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• v.2 no.1
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• pp.68-75
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• 2004

In this paper, an estimator with an appropriate adaptive law for updating parameters is designed and analyzed based on the Lyapunov theory. The adaptive law is designed so that the estimation model follows the parameterized plant model. Using the proposed estimator, the parameters of the T-S fuzzy model can be estimated by observing the behavior of the system and it can be a basis for indirect adaptive fuzzy control.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1267-1271
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• 2003

This paper proposes an indirect adaptive fuzzy controller for general SISO nonlinear systems. No a priori information on bounding constants of uncertainties including reconstruction errors and optimal fuzzy parameters is needed. The control law and the update laws for fuzzy rule structure and estimates of fuzzy parameters and bounding constants are determined so that the Lyapunov stability of the whole closed loop system is guaranteed. The computer simulation results for an inverted pendulum system show the performance of the proposed robust adaptive fuzzy controller.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.04a
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• pp.431-438
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• 2004

This study is on control-gain estimation of energy dissipation control algorithms. Velocity feedback, bang-bang, and energy dissipation control algorithms are proposed based on the Lyapunov stability theory and their performances are evaluated and compared. Saturation problem is considered in the design of the velocity feedback and energy dissipation control algorithms, and chattering problem in bang-bang control is solved by using boundary layer. Numerical results show that the proposed control algorithms can dissipate the structural energy induced by wind loads efficiently, and thus provide good control performance.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2002.03a
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• pp.475-482
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• 2002

This paper provides the systematic procedure to determine the weighting matrices of optimal controllers considering structural energy. Optimal controllers consist of LQR and ILQR. The weighting matrices are needed first in the conventional optimal control design strategy. However, they are in general dependent on the experienced knowledge of controll designers. Applying the Lyapunov function to the total structural energy and using the contrition that its derivative is negative, we can determine the weighting matrices without difficulty. It is proven that the control efficiency is achieved well for LQR and ILQR.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2863-2866
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• 2003

In nonlinear control fields, for irregular nonlinear systems, control form which consists of approximate tracking control law and exact tracking control law and which switches between two laws has been proposed recently. In this thesis, we design new switching control law which connect approximate linearization control law and exact linearization control law by fuzzy rules for irregular nonlinear system, ball and beam system. Fuzzy switching controller designed by fuzzy concept is proved that designed scheme overcomes singularities of irregular system, improves unstability problem of switching procedure, and has more efficient control value through simulation. Stability of fuzzy control system proved by Lyapunov's stability theorems.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.4
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• pp.788-792
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• 2010

The problem of delay-dependent and parameter-dependent robust stability condition for discrete-time uncertain singular systems with polytopic uncertainty and interval time-varying delay is considered. A new robust stability condition based on parameter-dependent Lyapunov function is derived in terms of LMI (linear matrix inequality). Moreover, the proposed robust stability condition is a general condition for both singular and non-singular systems. A numerical example is presented to demonstrate the effectiveness of the proposed method.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.429-432
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• 1998

This paper is to design stable fuzzy controller so as to control chaotic nonlinear systems effectively via fuzzy control system and Parallel Distributed Compensation (PDC) design. To design fuzzy control system, nonlinear systems are represented by Takagi-sugeno(TS) fuzzy models. The PDC is employed to design fuzzy controllers from the TS fuzzy models. The stability analysis and control design problems is to find a common Lyapunov function for a set of linear matrix inequalitys(LMIs). The designed fuzzy controller is applied to Rossler system. The simulation results show the effectiveness of our controller.