• Journal of Institute of Control, Robotics and Systems
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• v.9 no.6
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• pp.478-488
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• 2003

A guidance scheme that is suitable for controlling the aircraft flight path is proposed. The concept of miss distance which is commonly used in the missile guidance laws, and Lyapunov stability theorem are effectively combined to obtain the aircraft's trajectory-tracking guidance law. Guidance commands are given in terms of speed and flight path angles, but they perfectly reflect any position and velocity errors between real aircraft trajectory and reference one. The proposed guidance law is easily integrated into the existing flight control system. The new guidance law was extensively tested with various mission scenarios and the fully nonlinear 6-DOF aircraft model. Furthermore, the new guidance law was compared with previous guidance schemes in nonlinear simulation. Results from the numerical simulation show that the proposed guidance law yields better performance than previous ones.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.315-317
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• 2006

In this paper, we design a terminal sliding mode controller based on neural network for nonlinear systems with uncertainties. Terminal sliding mode control (TSMC) method can drive the tracking errors to zero within finite time. Also, TSMC has the advantages such as improved performance, robustness, reliability and precision by contrast with classical sliding mode control. For the control of nonlinear system with uncertainties, we employ the self-recurrent wavelet neural network(SRWNN) which is used for the prediction of uncertainties. The weights of SRWNN are trained by adaptive laws based on Lyapunov stability theorem. Finally, we carry out simulations to illustrate the effectiveness of the proposed control.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.226-228
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• 2006

This paper is concerned with an Adaptive Fuzzy Sliding Mode Control(AFSMC) that the fuzzy systems are used to approximate the unknown functions of nonlinear system. In the adaptive fuzzy system, we adopt the adaptive law to approximate the dynamics of the nonlinear plant and to adjust the parameters of AFSMC. The stability of the suggested control system is proved via Lyapunov stability theorem, and convergence and robustness properties are demonstrated. The simulation results demonstrate that the performance is improved and the system also exhibits stability.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1287-1292
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• 1999

In large-scale systems, we frequently encounter the time-delay and the uncertainty, and these should be considered in the design of controller because these are the source of the degradation of the system performance and instability of system. In this paper, we consider the robust stability of the linear large scale systems with the uncertainties and the time-delays. The considered uncertainties are both structured uncertainty and the unstructured uncertainty. Also, the considered time-delays are time-varying having finite time derivative limits. Based on the Lyapunov theorem and the linear matrix inequality(LMI) technique, we present two sufficient conditions that guarantee the robust stability of the system. The conditions are expressed as the LMI forms which can be easily checked their feasibility by using the well-known LMI control toolbox. Finally, we show by two examples that our results are less conservative than the previous results.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.161-163
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• 2005

This paper is concerned with an Adaptive Fuzzy Sliding Mode Control(AFSMC) that the fuzzy systems are used to approximate the unknown functions of nonlinear system. In the adaptive fuzzy system. we adopt the adaptive law to approximate the dynamics of the nonlinear plant and to adjust the parameters of AFSMC. The stability of the suggested control system is proved via Lyapunov stability theorem. and convergence and robustness properties are demonstrated. The simulation results demonstrate that the performance is improved and the system also exhibits stability.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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• pp.42-47
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• 2014

This paper investigates an adaptive approximation design problem for the tracking control of output-constrained non-affine pure-feedback systems. To satisfy the desired performance without constraint violation, we employ a barrier Lyapunov function which grows to infinity whenever its argument approaches some limits. The main difficulty in dealing with pure-feedback systems considering output constraints is that the system has a non-affine appearance of the constrained variable to be used as a virtual control. To overcome this difficulty, the implicit function theorem and mean value theorem are exploited to assert the existence of the desired virtual and actual controls. The function approximation technique based on adaptive neural networks is used to estimate the desired control inputs. It is shown that all signals in the closed-loop system are uniformly ultimately bounded.

• 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.

• Journal of Mechanical Science and Technology
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• v.14 no.11
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• pp.1225-1231
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• 2000

This paper proposes a V-shaped Lyapunov function approach for the model-based control of flexible-joint robots, in which a new model-based nonlinear control scheme is designed based on a V-shaped Lyapunov function. The proposed control guarantees global asymptotic stability for link trajectory control while keeping all internal signals bounded. Since joint flexibility is used as a control parameter, the proposed control is not restricted by the degree of joint flexibility and be applied to flexibility-joint, partly-flexibility, or rigid-joint robots without modification. the effectiveness of the proposed control has been by computer simulation.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.377-380
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• 1992

This paper proposes a novel direct adaptive pole placement control algorithm which can be applied to continuous time nonminimum phase systems. The algorithm is based on Lyapunov's direct method. By introducing an auxiliary signal, a minimal error model is constructed in state space. Using the error model an estimation law is obtained via Lyapunov's second stability theorem. The global stability of the overall system is established.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.435-438
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• 2002

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 serial link robot dynamics. The stability of the robot with the controller is proved by Lyapunov theory. The results of computer simulations show that the robot system is stable, and has excellent trajectory tracking performance.