• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.8
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• pp.771-775
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• 2001

In this paper, in order to control uncertain missile autopilot, an adaptive fuzzy control(AFC) scheme via parallel distributed compensation(PDC) is developed for the multi-input/multi -output plants represented by the Takagi-Sugeno(T-S) fuzzy model. Moreover adaptive law is designed so that the plant output tracks the stable reference model(SRM). From the simulations results, we can conclude that the suggested scheme can effectively solve the control problems of uncertain missile systems based on T-S fuzzy model.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.3
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• pp.252-258
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• 1997

This paper presents neural networks for hybrid position/force control which is a type of position and force control for robot manipulators. The performance of conventional hybrid position/force control is excellent in the case of the exactly-known dynamic model of the robot, but degrades seriously as the uncertainty of the model increases. Hence, the neural network control scheme is presented here to overcome such shortcoming. The introduced neural term is designed to learn the uncertainty of the robot, and to control the robot through uncertainty compensation. Further more, the learning rule of the neural network is derived and is shown to be effective in the sense that it requires neither desired output of the network nor error back propagation through the plant. The proposed scheme is verified through the simulation of hybrid position/force control of a 6-dof robot manipulator.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.9
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• pp.530-536
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• 2002

In this paper, a new torque ripple compensator is proposed. The proposed torque ripple compensator utilizes only speed information, so it can be easily applied to an existing motor drive system by including the algorithm. The stability analysis is discussed. From the discussion, the proper gain selection method, which makes the compensator stable and fast convergent, is also presented. The experimental results are presented and show the torque ripple reduction capability of the proposed scheme.

• Journal of Power Electronics
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• v.11 no.5
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• pp.751-758
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• 2011

This paper presents an effective robust predictive control scheme for the active power filter (APF) using a smith-predictor based current regulator, which show superior features when compared to proportional-integral (PI) controllers in terms of an enhanced closed-loop bandwidth and an improved current tracking accuracy. A moving average filter (MAF) is implemented using a field programmable gate array (FPGA) for signal pre-processing to eliminate the switching ripple contamination. An adaptive linear neural network (ADALINE) is used for individual harmonic estimation to achieve selective compensation purpose. The effectiveness and validity of the devised control algorithm are confirmed by extensive simulation and experimental results.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2146-2148
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• 2003

This paper present a modified repetitive control scheme for an optical storage system to track a periodic reference signal with dynamic change in period. Periodic disturbances can be adequately attenuated using the concept of repetitive control, provided the period is know. An optical storage system supports various speeds. To deal with time varying periodic disturbances, an proposed repetitive controller is turned based on repetitive control to change sampling frequency to follow the change of reference Period. A modified repetitive control scheme is proposed and implement on experimental set up of a optical disk driver.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1343-1345
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• 2005

In this paper, control schemes are proposed for a propulsion system(Converter/Inverter) of the TTX(Tilting Train express). In developed traction converter, unity power factor control, compensation method of dc link voltage have been applied. Output current of converter contains harmonics ripple at twice input ac line frequency, which causes a ripple in the dc link voltage so that control scheme is developed in inverter system to reduce the pulsating torque current. At low speed region, vector control scheme is applied and slip frequency control is adopted at high speed region. The performance of propulsion system will be verified by simulation and prototype experimental results.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.657-660
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• 2003

Control of multi-link robot arms is a very difficult problem because of the highly nonlinear dynamics. Decentralized control scheme is developed for control of robot manipulators based on RBF(Radial Basis Function) Neural Networks. RBF Neural Networks is used to approximate the coupling forces among the joints, coriolis force, centrifugal force, gravitational force, and frictional force. The compensation controller is also proposed to estimate the bound of approximation error so that the chattering effect of the control effort can be reduced. The proposed scheme does not require an accurate manipulator dynamic, and it is proved that closed-loop system is asymptotic stable despite the gross robot parameter variations. Numerical simulations for two-link robot manipulator are included to show the effectiveness of controller.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.784-786
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• 2010

Implementation possibility of inline dispersion management (DM) using bi-end schemes, which consist of one single mode fiber (SMF) and two dispersion compensating fiber (DCF) placed at front and rear of SMF, respectively, is investigated for compensating total dispersion accumulated in a span of WDM transmission links. It is confirmed that if net residual dispersion (NRD) is decided to be ${\pm}10\;ps/nm$ then bi-end scheme is effective to compensate for WDM channels with wide launching power range.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.2_2
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• pp.193-198
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• 2022

In this paper, we introduce the improved control method are communicated between a master and a slave robot in the teleoperation systems. When the master and slave robots are located in different places, time delay is unavoidable under the network environment and it is well known that the system can become unstable when even a small time delay exists in the communication channel. The time delay may cause instability in teleoperation systems especially if those systems include haptic feedback. This paper presents a control scheme based on the estimator with virtual master model in teleoperation systems over the network. As the behavior of virtual model is tracking the one of master model, the operator can control real master robot by manipulating the virtual robot. And LQG/LTR scheme was adopted for the compensation of un-modeled dynamics. The approach is based on virtual master model, which has been implemented on a robot over the network. Its performance is verified by the computer simulation and the experiment.

• Journal of Mechanical Science and Technology
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• v.16 no.8
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• pp.1053-1063
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• 2002

This paper presents a robust nonlinear controller for a f degree of freedom (DOF) parallel manipulator in the task space coordinates. The proposed control strategy requires information on orientations and translations in the task space unlike the joint space or link space control scheme. Although a 6 DOF sensor may provide such information in a straightforward manner, its cost calls for a more economical alternative. A novel indirect method based on the readily available length information engages as a potential candidate to replace a 6 DOF sensor. The indirect approach generates the necessary information by solving the forward kinematics and subsequently applying alpha-beta-gamma tracker With the 6 DOF signals available, a robust nonlinear task space control (RNTC) scheme is proposed based on the Lyapunov redesign method, whose stability is rigorously proved. The performance of the proposed RNTC with the new estimation scheme is evaluated via experiments. First, the results of the estimator are compared with the rate-gyro signals, which indicates excellent agreement. Then, the RNTC with on-line estimated 6 DOF data is shown to achieve excellent control performance to sinusoidal inputs, which is superior to those of a commonly used proportional-plus-integral-plus-derivative controller with a feedforward friction compensation under joint space coordinates and the nonlinear controller under task space coordinates.