• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.1
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• pp.77-84
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• 1998

This paper describes a control system design for the transmission STATCOM by applying a no-linear state feedback, and the performance analysis of the control system by simulations and scaled-model experiments. A mathematical model for the STATCOM was derived using a 3-phase equivalent circuit and a perturbation state equation with respect to a typical operating point. A transfer function to describe the dynamics of STATCOM was derived by considering nonlinear state feedback. A controller design was completed by analyzing the feedback system stability with root locus method. The performance analysis of the conceived control system was verified by simulations with the EMTP and experiments with scaled model, assuming that the STATCOM is connected to an 154kV transmission system. The results show that the conceived control system has excellent performance to control the reactive power of the transmission system.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.11
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• pp.990-998
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• 2007

Adaptive output feedback control technique using Neural Networks(NN) is proposed for uncertain nonlinear Multi-Input Multi-Output(MIMO) systems. Modified Dynamic Inversion Model(MDIM) is introduced to decouple uncertain nonlinearities from inversion-based control input. MDIM consists of approximated dynamic inversion model and inversion model error. One NN is applied to compensate the MDIM of the system. The output of the NN augments the tracking controller which is based upon a filtered error approximation with online weight adaptation laws which are derived from Lyapunov's direct method to guarantee tracking performance and ultimate boundedness. Several numerical results are illustrated in the simulation of Van der Pol system and unmanned helicopter with model uncertainties.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.9
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• pp.1147-1153
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• 1999

The attitude control of a double inverted pendulum with a periodical disturbance at link top is dealt in this paper. The proposed system is consisted of the double inverted pendulum and a disturbing link; a triple inverted pendulum with two motors. The lower link is hinged on the plate to free for rotation in the vertical plane. The upper link is connected to the lower link through a DC motor. The DC motor is used to control the posture of the pendulum by adjusting the position of the upper link. The periodical disturbance can be generated by the additional like attached at the end of link 2 through another DC motor, which is the modeling of a posture for a biped supporting with one leg. The motor for the joint simulates the knee joint(or hip joint) and the disturbance for the legs moving in air. The algorithm for controlling the proposed inverted pendulum which is regarded as a virtual double inverted pendulum with a periodic disturbance, is consisted of a state feedback control and a fuzzy logic controller connected in parallel. The fuzzy controller keeps the center of gravity of the biped within the specified range through the nonlinear feedback compensator. The state feedback control takes over the role to maintain a desired posture regardless the disturbance at the link top. Simulations with a mathematical model and experiments are conducted to show the validity of the proposed controller.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.7
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• pp.1706-1715
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• 1996

The decision feedback equalizer(DFE) received recent attention since it can compensate for channels with severe intersymbol interference(ISI) without as much noise enhancement as the linear equalizer(LE). In this paper, we propose a new DFE which can icrease the performance of DFE further by using error feedback. The performance increase is achieved by reducing correlation of error signal, which cannot be reduced by the feedforward or feedback filter. Hardware complexity for the proposed approcach is minimal since it requires only additional few taps to the conventional DFE. Based on theoretical analysis and computer simulations, the proposed approach is shown to be much more effective than the conventional DFE, especially for channels with large ISI.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.3
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• pp.41-49
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• 2010

Two promising control candidates have been selected to test the sinusoidal reference tracking performance for a brush-type polishing machine having strong nonlinearities and disturbances. The controlled target system is an oscillating mechanism consisting of a common positioning stage of one degree-of-freedom with a screw and a ball nut driven by a servo motor those can be obtained commercially. Beside the strong nonlinearity such as stick-slip friction, the periodic contact of the polishing brush and the work piece adds an external disturbance. Selected control candidates are a Sliding Mode Control (SMC) and a variant of a feedback linearization control called Smooth Robust Nonlinear Control (SRNC). A SMC and SRNC are selected since they have good theoretical backgrounds, are suitable to be implemented in a digital environment and show good disturbance and modeling uncertainty rejection performance. It should be also noted that SRNC has a nobel approach in that it uses the position information to compensate the stickslip friction. For both controllers analytical and experimental studies have been conducted to show control design approaches and to compare the performance against the strong nonlinearity and the disturbances.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.6
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• pp.1379-1386
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• 2005

For efficient welding it is necessary to maintain stability of the welding process and control the shape of the welding bead. The welding quality can be controlled by monitoring important parameters, such as, the Arc Voltage, Welding Current and Welding Speed during the welding process. Welding systems use either a vision sensor or an Arc sensor, both of which are unable to control these parameters directly. Therefore, it is difficult to obtain necessary bead geometry without automatically controlling the welding parameters through the sensors. In this paper we propose a novel approach using fuzzy logic and neural networks for improving welding qualify and maintaining the desired weld bead shape. Through experiments we demonstrate that the proposed system can be used for real welding processes. The results demonstrate that the system can efficiently estimate the weld bead shape and remove the welding detects.