• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.454-457
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• 1997

As in most industrial processes, the dynamic characteristics of an electric power system are subject to changes. Amongst those effects which cause the system to be uncertain, faults on transmission lines are considered. For the stabilization of the power system, we present an indirect adaptive control method, which is capable of tracking a sudden change in the effective reactance of a transmission line. As the plant dynamics are nonlinear, an input-output feedback linearization method equipped with nonlinear damping terms is combined with an identification algorithm which estimates the effect of a fault. The stability of the resulting adaptive nonlinear system is investigated.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.333-336
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• 1997

In this paper, we present a nonlinear dynamic controller for position tracking of brushless dc motors. In constructing the controller, a backstepping-type approach is used under the condition of full state information, while an adaptive controller is adopted for parameter uncertainty throughout the entire electromechanical system. The nonlinear dynamic controller using the adaptive learning technique approach is shown to drive the state variables of system to the desired ones asymptotically and whose effectiveness is also sown via computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.57-60
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• 2003

We have proposed the adaptive noise reduction algorithm using the MDFT. The algorithm proposed use the linear prediction coefficients of the AR method based on Sign algorithm that is the modified LMS instead of the least mean square(LMS). The signals with a random noise tracking performance are examined through computer simulations and confirmed that the high speed adaptive noise reduction processing system is realized with rapid convergence.

• 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 Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.185-188
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• 1998

In this paper, we propose a feedback adaptive controller which need not adjustment of the scale factor. Numerical examples are included to illustrate the procedure of a adaptive control and to show the performance of the control system. We can observe that the output of control system, converges toward the reference of response.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.889-894
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• 1993

This paper presents a robust adaptive control scheme based on the Lyapunov design for robot manipulators subjected to inertial parameter uncertainties and bounded torque disturbances. The scheme is a modified version of the adaptive computed torque method which adopts a dead zone into the adaptation mechanism so as to avoid parameter drifts by disturbances. It is shown via stability analysis and computer simulations that all the signals in the overall adaptive system are bounded and tracking errors lie within a prespecified bound.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.428-433
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• 1993

An analytic solution approach to the time-varying obstacle avoidance problem is pursued. We use the view-time concept, especially the adaptive view-time. First. we introduce the adaptive view-time and analyze its properties. Next, we propose a view-time based motion planning method. The proposed method is applied and simulated for the collision-free motion planning of a 2 DOF robot manipulator. We simulate the robot motion under several different view-time systems. Generally, the motion planning with the adaptive view-time systems has some advantages over that with the fixed view-time systems.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.277-282
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• 1994

Convergence of the state error e to zero in adaptive systems is shown using the uniqueness of solutions and the existence of a Lyapunov function in which the adaptation laws are constructed. Results in the paper are general, and therefore applicable to any adaptive control of a linear/nonlinear, time-varying or distributed-parameter system. Since the approach taken in the paper does not require the boundedness of the derivative of the state error e for all t .geq. 0, it is particularly useful in the adaptive control of infinite dimensional systems.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1233-1236
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• 1996

Attitude Control System for a Hydrofoil type catamaran in wave is designed using a Decentralized Adaptive Control technique which is announced already by authors. This automatic attitude control system is designed for its good seaworthiness and for robustness on the variation of center of gravity. The performance is compared with a PID controller and the results show that the Decentralized Adaptive controller has better stability on the variation of the center of gravity.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.331-334
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• 1996

It is a well-known problem that the adaptive control has a poor transient response. In order to improve this problem, the scheme that model-reference adaptive control (MRAC) uses the genetic algorithm (GA) in the search for parameters is proposed. Use genetic algorithm (GA) in the searching for controller's parameters set and conventional gradient method for fine tuning. And show the reduction of the oscillations in transient response comparing with the conventional MRAC.