• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.6
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• pp.77-83
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• 2003

This paper deals with a position control problem of a hydraulic proportional position control system using a nonlinear friction compensation control. As nonlinear friction, stiction and coulomb friction forces are considered and modeled as deadzone and external disturbance respectively. In order to compensate this nonlinearities, we designed the controller which is the adaptive friction compensator using discrete time Model Reference Adaptive Control method in this paper. Digital Signal Processing board is employed for data acquisition and manipulation. The experimental results show that response is slow and steady-state error cannot be compensated properly without friction compensation but this compensator is effective to obtain fast response and good steady-state response.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.888-893
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• 2005

Since inertial sensor errors which increase with time are caused by initial orientation error and sensor errors(accelerometer bias and gyro drift bias), the accuracy of these devices, while still improving, is not adequate for many of today's high-precision, long-duration sea, aircraft, and long-range flight missions. This paper presents a navigation error compensation scheme for Strap-Down Inertial Navigation System(SDINS) using star tracker. To be specific, SDINS error model and measurement equation are derived, and Kalman filter is implemented. Simulation results show the boundedness of position and attitude errors.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.9
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• pp.941-946
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• 2011

The Loran-C, a radio navigation system based on TDOA measurements is enhanced to eLoran using TOA measurements instead of TDOA measurements. Many error factors such as PF, SF, ASF, clock errors and unknown biases are included in eLoran TOA measurements. Because these error factors can cause failure in eLoran navigation algorithm, these errors must be compensated for high accuracy eLoran navigation results. Compensation of ASF and unknown biases are difficult to calculate, while the others such as PF and SF are relatively easy to eliminate. In order to compensate all errors in eLoran TOA measurements, a simple GPS aided bias compensation method is suggested in this paper. This method calculates the bias as the difference of TOA measurement and the range between eLoran transmitters and the receiver whose position is determined using GPS. The real data measured in Europe are used for verification of suggested method and navigation algorithm.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.679-681
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• 1995

In this paper, a friction compensation scheme using a fuzzy logic is presented. For the precision positioning and tracking control, the proper friction compensation is essential. Friction compensation schemes based on velocity and controlling input or desired velocity, have limitations because the compensation values are fixed. In this paper, a fuzzy friction compensation scheme adjusts the compensation value depending on the velocity and the position error. The proposed fuzzy friction compensator is implemented in a linear positioning system. The performance is illustrated by simulations and experiments.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.806-807
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• 2011

This paper presents a new sensorless controller used with both the classical sliding mode observer(SMO) and the rate of current change in order to a reduced torque ripple for switched reluctance motor (SRM) sensorless drives. The new sensorless scheme consists of a sliding mode observer (SMO)-based position sensorless approach for high speeds along with a low-resolution discrete the rate of current change for low speeds and standstill. The new position estimation resets between the SMO and the low-resolution of current change according to the speed sign and the position error difference between the SMO and the low-resolution rate of current change. The simulation results show the robustness of this new high performance sensorless control approach with the hybrid sensorless control topology.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.12
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• pp.1007-1013
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• 2016

This paper presents the development of a magneto-optical encoder for higher precision and smaller size. In general, optical encoders can have very high precision based on the position information of the slate, while their sizes tend to be larger due to the presence of complex and large components, such as an optical module. In contrast, magnetic encoders have exactly the opposite characteristics, i.e., small size and low precision. In order to achieve encoder features encompassing the advantages of both optical and magnetic encoders, i.e., high precision and small size, we designed a magneto-optical encoder and developed a method to detect absolute position, by compensating for the error of the hall sensor using the linear table compensation method. The performance of the magneto-optical encoder was evaluated through an experimental testbed.

• The Transactions of the Korean Institute of Power Electronics
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• v.12 no.6
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• pp.449-455
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• 2007

Position information is very important when driving the Permanent Magnet Synchronous Motor(PMSM). Generally, resolver is used to obtain exact position information. However, it generates periodic position errors due to the transformer ratio difference and excitation signal distortion. When the vector control is done with the position information that includes position error, torque ripple is generated from time to time. This paper proposes the solution through analysis of above problem. Also, it's validity is verified by simulation and experiment.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.560-562
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• 2006

In this paper, Correct problem in dead reckoning system and proposed about position error revision techniques of mobile robot to use RFID tag for position awareness. With the dead reckoning system, as the accumulation of error are unavoidable because of accumulation of informations as the time passage, so it is impossible to get correct information about posture, including torrent direction, movement distance, etc. As one of compensation method, the suggested method is that after selecting special area (corridor), compensate absolute location information by arranging two line of RFID tag along two side of corridor. Through this suggested method, it could be used when robot wants to move in limited areas.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.3
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• pp.293-301
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• 2019

Based on accurate image processing technology, a system for measuring displacement in ${\mu}m$ for drive error (position error, straightness error, flatness error) at a distance using parallel light and image sensor is developed, and a system for applying this technology development to a large 3D rapid prototyping machine and compensating in real time is developed to dramatically reduce the range of measurement error and enable intelligent 3D production of high quality products.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.2
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• pp.152-160
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• 2001

Six degrees of freedom measurement systems are required in many fields: Precision machine control. precision assembly, vibration analysis, and so on. This paper presents a new six degrees of freedom measurement system utilizing typical features of a diffraction grating. It is composed of a laser source, three position sensitive detectors, a diffraction grating target, and several optical components. Six degrees of freedom displacement is calculated kinematically from the coordinates of diffracted rays on the detectors. Optical measurement error was caused by the fact that a laser source had a Gaussian intensity distribution. This error was analyzed and compensated using simple equations. The performance of the compensation equation was verified in the experiment. The experimental results showed that the compensation equation could reduce the optical measurement error remarkably and the error in six degrees of freedom measurement less than $\pm$10$\mu$m for translation and $\pm$0.012$^{\circ}$for rotation.