• International Journal of Safety
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• v.1 no.1
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• pp.1-6
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• 2002

It is important to control the high accurate position and force to prevent unexpected accidents by a robot manipulator. Direct-drive robots are suitable to the position and force control with high accuracy, but it is difficult to design a controller because of the system's nonlinearity and link-interactions. This paper is concerned with the study of the stabilization force control of direct-drive robots. The proposed algorithm is consists of the feedback controllers and the neural networks. After the completion of learning, the outputs of feedback controllers are nearly equal to zero, and the neural networks play an important role in the control system. Therefore, the optimum adjustment of control parameters is unnecessary. In other words, the proposed algorithm does not need any knowledge of the controlled system in advance. The effectiveness of the proposed algorithm is demonstrated by the experiment on the force control of a parallelogram link-type robot.

• Journal of Electrical Engineering and Technology
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• v.10 no.2
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• pp.529-538
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• 2015

Due to the high efficiency and compact mechanical structure, direct drive variable speed generators are used for power conversion in wind turbines. The wind energy conversion system (WECS) considered in this paper consists of a permanent magnet synchronous generator (PMSG), uncontrolled rectifier, dc-dc boost converter controlled with maximum power point tracking (MPPT) and adaptive hysteresis controlled voltage source inverter (VSI). For high utilization of the converter's power capability and stabilizing voltage and power flow, constant DC-link voltage is essential. Step and search MPPT algorithm which senses the rectified voltage ($V_{DC}$) alone and controls the same is used to effectively maximize the output power. The adaptive hysteresis band current control is characterized by fast dynamic response and constant switching frequency. With MPPT and adaptive hysteresis band current control in VSI, the DC link voltage is maintained constant under variable wind speeds and transient grid currents respectively.

• International Journal of Control, Automation, and Systems
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• v.4 no.1
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• pp.113-123
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• 2006

In this paper, an improved direct torque control (DTC) method for sensorless matrix converter drives is proposed which enables to minimize torque ripple, to obtain unity input power factor, and to achieve good sensorless speed-control performance in the low speed operation, while maintaining constant switching frequency and fast torque dynamics. It is possible to combine the advantages of matrix converters with the advantages of the DTC strategy using space vector modulation and a flux deadbeat controller. To overcome the phase current distortion by the non-linearity of a matrix converter drive, the simple non-linearity compensation method using PQR power theory are presented in the proposed scheme. Experimental results are shown to illustrate the feasibility of the proposed strategy.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.411-413
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• 1992

This paper proposes a simple and high performance hybrid position/force control of robots based on disturbance compensation by using the disturbance observer in task coordinate space. The disturbance observer linealizes system of robot manipulators in task coordinate space and realizes acceleration control. To realize the strict acceleration control, the disturbance observer whose input is a position signal by simple computation, works as if it were a disturbance detector. The inverse kinematics can be simplified, because the disturbance observer in task coordinate space compensates not only the disturbance but also the error due to the simplification of the inverse kinematics. The new strategy is applied to a three-degrees-of freedom direct drive robot. The robust and simple hybrid position/force control is realized experimentally.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.3 s.174
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• pp.653-660
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• 2000

The automatization by industrial robot of today is merely rely on to the simple position repeating works, but requirements of research and development to the force control which would adapt positively to various restriction or contacting works to environment. In this paper, a learning control algorithm using, neural networks is proposed for the position and force control by a direct-drive robot. The proposed controller is the feedback controller to which the learning function of neural network is added on to and has a character of improving controller's efficiency by learning. The effectiveness of the proposed algorithm is demonstrated by the experiment on the hybrid position and force control of a parallelogram link robot with a force sensor.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.836-839
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• 2003

A pneumatic servo valve which is widely applied in industrial field. And It is consist of force motor, spool ＆ sleeve and servo controller. In this study. we developed the force motor which is consume to low power for a pneumatic servo valve. We could reduce the number of turn of the solenoid by using ferromagnetic permanent magnet and took different direction of each other using one coil instead of two coil. we modeled a system consisting of various electro-mechanical subsystems. The appropriateness of the model was verified by simulation. The simulation model resolved the motion of spool, the winding current and the magnetic force. Also, we calculated the displacement and velocity of the spool, flux contour line, b vector. flux density. flux linkage, back EMF etc.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.884-889
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• 1990

In this paper, a new hybrid position control algorithm for the direct drive arm is proposed. The proposed control is composed of discrete feedforward component and continuous feedback component. The discrete component is the nominal torque which approximately compensates the strong nonlinear coupling torques between the links, while the continuous control is a modified version of sliding mode control which is known to have a robust property to the disturbances of system. For the proposed control law, we give sufficient condition which guarantees the bounded tracking error in spite of the modeling errors, and the efficiency of the proposed algorithm is demonstrated by the numerical simulation of a three link manipulator position control with payloads and parameter errors.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.3
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• pp.76-85
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• 1998

In this paper, a fuzzy tuning method of a control gain in the discrete-time repetitive controller is proposed for precise tracking control of a system whose reference signal is repetitive. The control gain is modified by fuzzy rules which use the magnitude and the variation ofthe maximum output error in the previous repetitive period. The proposed method is applied to a direct drive 2-axis SCARA-type robot and, it is illustratedby computer simulations and real-time experimentation that better performance can be obtained that the fixed gain-based repetitive controller.

• Journal of Magnetics
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• v.19 no.3
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• pp.273-281
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• 2014

This paper presents an innovative design for a low-speed, direct-drive, axial-flux permanent-magnet (AFPM) generator with a coreless stator and rotor that is intended for application to small wind turbine power generation systems. The performance of the generator is evaluated and optimized by means of comprehensive 3D electromagnetic finite element analysis. The main focus of this study is to improve the power output and efficiency of wind power generation by investigating the electromagnetic and structural features of a coreless AFPM generator. The design is validated by comparing the performance achieved with a prototype. The results of our comparison demonstrate that the proposed generator has a number of advantages such as a simpler structure, higher efficiency over a wide range of operating speeds, higher energy yield, lighter weight and better power utilization than conventional machines. It would be possible to manufacture low-cost, axial-flux permanent-magnet generators by further developing the proposed design.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.133-135
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• 1997

In this paper, a fuzzy tuning discrete-time repetitive control is suggested for a robot manipulator. Real-time implementation of this type of repetitive controller is also performed for a 2 link direct drive robot by using a real-time control system which consists of a real-time OS(Spectra), a single board computer, a communication board and an analog input/output board. First, it is shown that the tracking error is effectively reduced by discrete-time repetitive control. Second, the convergence performance is shown to be much improved by the suggested controller using real-time experimentations.