• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.672-674
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• 2004

Many nonlinear controllers for the power system are based on nonlinear models involving the power angle as an element of the state, and therefore the reference value for the power angle is needed. As this reference value is not generally available, it is difficult to apply such nonlinear control methods in practice. To deal with this problem, we present an input-output feedback linearizing control scheme by selecting the output as a combination of the squared voltage and the relative frequency. It is shown that the internal dynamics are locally stable with controllable damping, and that the frequency remains bounded for all time. Simulations illustrate the effectiveness of the proposed method.

• Proceedings of the KIEE Conference
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• 2001.07b
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• pp.1049-1051
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• 2001

This paper proposes a new control strategy of multifunctional uninterruptible power supply(UPS) with the performance of active power filter which compensate the harmonics and reactive power. To improve the transient response for the effective compensation in active power filter mode, it is considered that a simple and precise calculation method of the compensation reference current for the harmonics and reactive power compensation. So a novel closed-loop control strategy is used to calculate the reference current. And the current regulated instantaneous voltage control scheme is used in back-up power mode. The system model and control algorithm are described and analyzed, and the system performance is verified by the simulation results.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.570-572
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• 2005

This paper is proposed adaptive hybrid artificial intelligent(HAI) controller for high performance of induction motor drive. The design of this algorithm based on fuzzy-neural network(FNN) controller that is implemented using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive FNN controller is evaluated by analysis for various operating conditions. The results of experiment prove that the proposed control system has strong high performance and robustness to parameter variation, and steady-state accuracy and transient response.

• Proceedings of the KIEE Conference
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• 2004.04a
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• pp.143-146
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• 2004

This paper is proposed adaptive fuzzy-neural network(FNN) controller for speed control of induction motor drive. The design of this algorithm based on FNN controller that is implemented using fuzzy control and neural network. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive FNN controller is evaluated by analysis for various operating conditions.

• Proceedings of the KIEE Conference
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• 2002.04a
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• pp.79-81
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• 2002

This paper develops a adaptive fuzzy controller based fuzzy logic control for high performance speed controller in permanent magnet synchronous motor(PMSM) drives. In the proposed system, fuzzy control is used to implement the direct controller as well as the adaptation mechanism. The operation of the direct fuzzy controller and the fuzzy logic based adaptation mechanism is studied. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive fuzzy controller is evaluated by simulation for various operating conditions. The validity of the proposed adaptive fuzzy controller is confirmed by performance results for PMSM drive system.

• Journal of Ocean Engineering and Technology
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• v.8 no.2
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• pp.131-140
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• 1994

Dynamics of AUV has heavy nonlinearities and many unknown parameters due to its bluff shape and low cruising speed. Intelligent algorithms, therefore, are required to overcome these nonlinearities and unknown system dynamics. Several identification techniques have been suggested for the application of control of underwater vehicles during last decade. This paper applies the neural network to identification and motion control problem of AUVs. Nonlinear dynamic systems of an AUV are identified using feedforward neural network. Simulation results show that the learned neural network can generate the motion of AUV. This paper, also, suggest an adaptive control scheme up-dates the controller weights with reference model and feedforward neural network using error back propagation.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.1
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• pp.61-66
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• 2002

A fuzzy control strategy is described which is utilized to control the joint angle and tip deflection in single flexible manipulator. In this paper, an existing model for a single flexible manipulator is used for the initial development of an FLC. One FLC is designed to govern the joint angle of the manipulator as it is rotated from one position to another, and the second FLC is designed to attenuate the tip deflection which result from joint angle body motion. Reference Trajectory Command is an important method to reduce vibration in flexible beam. This paper presents a very simple command control shaping which eliminates multiple mode residual vibration in a flexible beam combined parallel fuzzy controller. The effectiveness of proposed scheme is demonstrated through computer simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.9
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• pp.1479-1485
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• 2016

This paper presents DC voltage recovery time improvement method in DC link of High Voltage Direct Current (HVDC) with offshore wind farm. The wind farm should be satisfied Low Voltage Ride Through(LVRT) control strategy when grid faults occur. The LVRT control strategy indicates actions which have to be executed according to the voltage dip ratio and the fault duration. However, The LVRT control strategy makes between wind farm and power system through DC Link voltage when grid fault occurs. The de-loading scheme is one of the method to control the DC voltage. But de-loading scheme need to long DC voltage recovery time. Thus, this paper proposes an improved de-loading scheme and we analysis DC voltage and active power reference through a simulation.

• Proceedings of the KIEE Conference
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• 1997.07a
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• pp.44-46
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• 1997

The intrinsic simplicity, ruggedness, and simple power electronic drive requirement of a switched reluctance motor (SRM) make it a viable use for many commercial adjustable speed applications. However, higher torque ripple is one of the few disadvantages of the SRM drives. This paper describes the robust control scheme that permits the phase torque flatted by adaptive reference model.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.10
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• pp.53-58
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• 1992

This paper presents a decentralized model reference adaptive control scheme for an interconnected linear system composed of a number of single-input single-output subsystems in which outgoing interactions pass through the measurement channel and are subjected to bounded external disturbances. The scheme can treat the unknown strength of interactions as well as uncertainties in subsystem dynamics, and allows for the case when the relative degree of each decoulped subsystem does not exceed two.