• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.527-535
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• 2012

This paper reports the active vibration control of plates using positive position feedback controller (PPF). The equations of motion of the plate under force and moment pairs were derived and the equations of PPF controllers were formulated. The effect of the parameters - gain and damping ratio - of the PPF controllers on the open loop transfer function was investigated mainly in terms of the system stability. Increasing the gain of the PPF controller tuned at a mode, the magnitude of the open loop transfer function is increased at all frequencies without changing the phase behavior. The increase of the damping ratio of the PPF controller leads to decrease the magnitude of the open loop transfer function and to modify its phase characteristics to be more stable. Two PPF controllers connected in parallel, Each PPF controller is tuned at the $1^{st}$ and $2^{nd}$ modes, respectively. Their parameters were determined to remain the system to be stable based on the results of the parametric study. A significant reduction in vibration at the 2 modes can be obtained.

• The Transactions of the Korean Institute of Power Electronics
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• v.15 no.3
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• pp.226-234
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• 2010

This paper proposes an improved feed-forward controller that calculates the gain value by estimating the changed boost inductance in practical operating condition of transformer. The boost inductance is estimated by the measurement of input current and voltage. The estimated boost inductance is optimized by the least square method. The proposed feed-forward controller can be achieved the robust control through the gain value calculating the estimated boost inductance despite of the changed condition of transformer and can minimize the interference phenomenon by reducing the harmonics of input current. The validity of proposed technique is verified through the simulation and experiment.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.705-709
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• 1995

The objective of this study is to design a multi-layer neural network which controls the position of excavator's attachment. In this paper, a dynamic controller has been developed based on an error back-propagation(BP) neural network. Since the neural network can model an arbitrary nonlinear mapping, it was used as a commanded feedforward input generator. A PD feedback controller is used in parallel with the feedforward neural network to train the system. The neural network was trained by the current state of the excavator as well as the PD feedback error. By using the BP network as a feedforward controller, no a priori knowledge on system dynamics is need. Computer simulation results demonstrate such powerful characteristics of the proposed controller as adaptation to changing environment, robustness to disturbancen and performance improvement with the on-line learning in the position control of excavator attachment.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.5
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• pp.46-55
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• 2000

This paper presents a direct adaptive control of robot system using chaotic neural networks and PD controller. The chaotic neural networks have robust nonlinear dynamic characteristics because of the sufficient nonlinearity in neuron itself, and the additional self-feedback and inter-connecting weights between neurons in same layer. Since the structure and the learning method are not appropriate for applying in control system, this neural networks have not been applied. In this paper, a modified chaotic neural networks is presented for dynamic control system. To evaluate the performance of the proposed neural networks, these networks are applied to the trajectory control of the three-axis PUMA robot. The structure of controller consists of PD controller and chaotic neural networks in parallel for conforming the stability in initial learning phase. Therefore, the chaotic neural network controller acts as a compensating controller of PD controller.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.6
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• pp.56-66
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• 1998

This paper investigates a neuro-controller combined in parallel with a conventional linear controller of PID type in order to control nonminimum phase systems more efficiently. The objective is to minimize overall position errors as well as to maintain small undershooting. A costfunction is proposed with two conflict objectives. The neuro-controller is trained off-line with evolutionary programming(EP) in such a way that it becomes optimal by minimizing the given cost function through global evaluation based on desired control performance during the whole training time interval. However, it is not easy to find an optimal solution which satisfies individual objective simultaneously. With the concept of Pareto optimality and EP, we train the proposed controller more effectively and obtain a valuable set of optimal solutions. Simulation results show the efficacy of the proposed controller in a viewpoint of improvement of performance of a step response like fast settling time and small undershoot or overshoot compared with that of a conventional linear controller.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.4
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• pp.383-392
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• 2012

This paper reports the active vibration control of plates using a positive position feedback(PPF) controller with moment pair actuators. The equations of motion of the plates under a force and moment pairs are derived and the equations of PPF controllers are formulated. The numerical active control system is then achieved. The effect of the parameters - gain and damping ratio - of the PPF controllers on the open loop transfer function was investigated mainly in terms of the system stability. Increasing the gain of the PPF controller tuned at a mode, the magnitude of the open loop transfer function is increased at all frequencies without changing the phase behavior. The increase of the damping ratio of the PPF controller leads to decrease the magnitude of the open loop transfer function and to modify its phase characteristics, ie, system stability. Based on the behavior of the gain and the damping ratio of the controller, PPF controller for reduction of the plate vibration can be achieved. Two PPF controllers are designed with their connection in parallel to control the two modes simultaneously. Each PPF controller is tuned at the $1^{st}$ and $2^{nd}$ modes, respectively. Their parameters were determined to remain the system to be stable based on the results of the parametric study. A significant reduction in vibration at the tuned modes can be obtained.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.1
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• pp.8-17
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• 2002

This paper suggests that the immune algorithm can effectively be used in tuning of a PID controller. The artificial immune network always has a new parallel decentralized processing mechanism for various situations, since antibodies communicate to each other among different species of antibodies/B-cells through the stimulation and suppression chains among antibodies that form a large-scaled network. In addition to that, the structure of the network is not fixed, but varies continuously. That is, the artificial immune network flexibly self-organizes according to dynamic changes of external environment (meta-dynamics function). However, up to the present time, models based on the conventional crisp approach have been used to describe dynamic model relationship between antibody and antigen. Therefore, there are some problems with a less flexible result to the external behavior. On the other hand, a number of tuning technologies have been considered for the tuning of a PID controller. As a less common method, the fuzzy and neural network or its combined techniques are applied. However, in the case of the latter, yet, it is not applied in the practical field, in the former, a higher experience and technology is required during tuning procedure. In addition to that, tuning performance cannot be guaranteed with regards to a plant with non-linear characteristics or many kinds of disturbances. Along with these, this paper used immune algorithm in order that a PID controller can be more adaptable controlled against the external condition, including moise or disturbance of plant. Parameters P, I, D encoded in antibody randomly are allocated during selection processes to obtain an optimal gain required for plant. The result of study shows the artificial immune can effectively be used to tune, since it can more fit modes or parameters of the PID controller than that of the conventional tuning methods.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.4
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• pp.283-290
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• 2022

This study proposes a voltage control scheme in a synchronous reference frame to improve the dynamic characteristics of double-conversion UPSs. UPSs need to control positive and negative sequence voltage, so that positive and negative sequence extractors are generally used to obtain each sequence of the voltage and current. Voltage and current controllers for each sequence are implemented. However, the extractor causes considerable delay, and the delay restricts the control performance, especially for the current controller. To improve the dynamics of the current controller, the proposed scheme adopts a unified current controller without separating positive and negative sequences. By using discrete-time current controller, the control bandwidth can be extended significantly so that negative sequence current can be controlled. To enhance the performance, an additional feed-forward technique for output voltage regulation is proposed. The validity of the proposed controller is verified by experiments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.3
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• pp.1255-1262
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• 2012

Look into the nuclear power plant of Wolsong currently, it is controlled in order to required operating pressure with PI controller. PI controller has a simple structure and satisfy design requirements to gain setting. However, It is difficult to control without changing the gain from produce changes in parameters such as loss of the valves and the pipes. To solve these problems, the dynamic change of the PI controller gain, or to compensate for the PI controller output is desirable to configure the controller. The aim of this research and development in the parameter variations can be controlled to a stable controller design which is reduced an error and a vibration. Proposed PI/NN control techniques is the PI controller and the neural network controller that combines a parallel and the neural network controller part is compensated output of the controller for changes in the parameters were designed to be robust. To directly evaluate the controller performance can be difficult to test in real processes to reflect the characteristics of the process. Therefore, we develope the simulator model using the real process data and simulation results when compared with the simulated process characteristics that showed changes in the parameters. As a result the PI/NN controller error and was confirmed to reduce vibrations.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.1
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• pp.40-47
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• 2002

This paper describes a re-adhesion control method for the Korean High-Speed Train (KHST) with parallel induction motor drive. To keep a traction efficiency and to improve vehicle maintenance, the adhesion characteristics between wheel and rail are analyzed. Also the re-adhesion controller is designed as the subsystem of induction motor vector control. In order to verify performance of the proposed control techniques, the simulation is executed by train model and a downscaled re-adhesion control simulator is utilized. Both simulation and running test results show that good re-adhesion characteristics are obtained.