• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.2
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• pp.136-143
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• 2004

This paper presents three algorithms of repetitive controller for compensation of the repeatable runout in hard disk drive. The basic theory of the repetitive controller and the analysis of the disturbance in hard disk drive are introduced. The tracking controller is designed in order to design the "plug-in type" repetitive controller. Design of the repetitive controller is considered as the design of the filter, determination of gain and design of additional compensation for the various types. Specially, trade-off relationship between stability and performance is important for the design. The three kinds of "plug-in type" repetitive controllers are designed, simulated and experimented. Performance and characteristic of them are compared with the analysis of the experimental results.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.263-266
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• 1998

This paper propose a prefilter type inverse control algorithm using chaotic neural networks. Since the chaotic neural networks show robust characteristics in approximation and adaptive learning for nonlinear dynamic system, the chaotic neural networks are suitable for controlling robotic manipulators. The structure of the proposed prefilter type controller compensate velocity of the PD controller. To estimate the proposed controller, we implemented to the Cartesian space control of three-axis PUMA robot and compared the final result with recurrent neural network(RNN) controller.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.4
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• pp.184-191
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• 2001

This paper proposes a prefilter type velocity compensating control system using modified chaotic neural networks for the trajectory control of robotic manipulator. Since the structure of modified chaotic neural networks(MCNN) and neurons have highly nonlinear dynamic characteristics, MCNN can show the robust characteristics for controlling highly nonlinear dynamics like robotic manipulators. For its application, the trajectory controller of the three-axis robot manipulator is designed by MCNN. The MCNN controller acts as the compensator of the PD controller. Simulation results show that learning error decrease drastically via on-line learning and the performance is excellent. The MCNN controller showed much better control performance and shorter calculation time compared to the RNN controller, Another advantage of the proposed controller could by attached to conventional robot controller without hardware changes.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.822-828
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• 2018

AC-DC conversion is a necessary for the systems that require DC source. This conversion has been done via rectifiers based on controlled or uncontrolled semiconductor switches. Advances in the power electronics and microprocessor technologies allowed the use of Pulse Width Modulation (PWM) rectifiers. In this paper, dq-axis current and DC link voltage of three-phase PWM rectifier are controlled by using type-2 fuzzy neural network (T2FNN) controller. For this aim, a simulation model is built by MATLAB/Simulink software. The model is tested under three different operating conditions. The parameters of T2FNN is updated online by using back-propagation algorithm. The results obtained from both T2FNN and Proportional + Integral + Derivate (PID) controller are given for three operating conditions. The results show that three-phase PWM rectifier using T2FNN provides a superior performance under all operating conditions when compared with PID controller.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.568-576
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• 1998

In this thesis discuss with a flexible robotic finger design and controller which is used for the micro flexible robotic finger. So, miniaturization, precision, controller for the control of grasping force and actuator were needed. And, even if we develop a new actuator and controller, in order to use on real system, we must considerate of a many side problem. In a force control of micro flexible finger for grasping an object, the fingertip's vibration was more important task of accuracy control. And, controller were adopt the PD/PI mixed type fuzzy controller. The controller were consist of two part, one is a PD type fuzzy controller for increase the rising time response, the other is a PI type fuzzy controller for decrease of steady-state error. Especially, in a PD type fuzzy controller, we used only seven rules. And, for a PI controller, we adopt a reset factor for the control of input values. so, we have overcome the exceed of controller's input range. For the estimate of ontroller's utility and usefulness, we have experiment and computer simulation of three cases. First, we consider of unit force grasping control for a task object, which is 0.03N. Second, bounding grasping force control which is add to a sinusoidal force on the unit force. At this cases the task force is (0.03+0.01 sin wt N). And consider of following of rectangular forces.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.951-958
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• 2013

This paper proposes the controller design for a stability improvement of an on-board battery charger. The system is comprised of a power factor correction (PFC) circuit and phase shift full-bridge DC-DC converter. The PFC circuit performs the control of the DC-link voltage and the input power factor. The DC-DC converter regulates the voltage and the current in the battery using the DC-link voltage. This paper proposes the design method of PI controller for the PFC circuit using a small signal model. The analysis and design of a type-three controller for the DC-DC converter is also presented. A simulation and experiment has been performed on the on-board battery charger and their results are presented to verify the validity of the proposed system.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.651-653
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• 1998

This thesis propose the prefilter type control strategies using modified chaotic neural networks #or the trajectory control of robotic manipulator. Since the structure of chaotic neural networks and neurons, chaotic neural networks can show the robust characteristics for controlling highly nonlinear dynamics like robotic manipulators. For its application, the trajectory controller of the three-axis PUMA robot is designed by CNN. The CNN controller acts as the compensator of the PD controller. Simulation results show that learning error decrease drastically via on- line learning and the performance is excellent. The CNN controller have much better controllability and shorter calculation time compared to the RNN controller. Another advantage of the proposed controller could be attached to conventional robot controller without hardware changes.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.1
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• pp.40-47
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• 2004

This paper proposes a three-axis coupling controller designed to improve the contouring accuracy in machining of 3D nonlinear contours. The proposed coupling controller is based on an innovative 3D contour error model and a PID control law. The novel contour error model provides almost exact calculation of contour errors in real-time for arbitrary contours and can be integrated with any type of existing interpolator. In the proposed method, three axes of motion are coordinated by the proposed coupling controller along with a proportional controller for each axis. The proposed contour error model and coupling controller are evaluated through computer simulations. The simulation results show that the proposed 3-axis coupling controller with the new contour error model substantially can improve the contouring accuracy by order of magnitude compared with the existing uncoupled controllers in high-speed machining of nonlinear contours.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1375-1381
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• 2007

In this paper, we propose a linear modeling and identical PD controller design scheme for the three-pole hybrid-type AMB recently developed in the laboratory, which consists of three permanent magnets, providing bias flux, three Hall diodes, measuring rotor displacements, and ring type permanent magnet bearing, stabilizing in axial and tilting directions. Along the three physical coordinates formed by three poles, we introduce the redundant coordinate system and three identical decoupled controllers to construct linear model. The experiments are also carried out in order to verify the effectiveness of proposed controller in stabilizing the transient and steady state response of rotor.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.7
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• pp.106-112
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• 2000

The purpose of this paper is to study on the control of the engine idle speed under sudden A/C load which is one of the most severe disturbances on engines. Three types of the closed-loop controller are developed for the stable engine idle speed control. The input of the controller is an error of rpm. The output of the controller is an ISCV duty cycle. The anticipation delay is considered to deal with the delay time of the air mass in engine. The PID, Fuzzy and PID-type Fuzzy controllers with the anticipation delay have improved the engine idle speed condition more than current ECU map table under the A/C load.