• Journal of the Korean Society for Precision Engineering
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• v.19 no.6
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• pp.70-76
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• 2002

Effectiveness of corrective machining algorithm is verified experimentally in this paper by performing corrective machina work practically to single side and double sides hydrostatic tables. Lapping is applied as machining method. Machining information is calculated from measured motion errors by applying the algorithm, without information on rail profile. It is possible to acquire 0.13$\mu$m of linear motion error, 1.40arcsec of angular motion error in the case of single side table, and 0.07$\mu$m of linear motion error, 1.42arcsec of angular motion error in the case of double sides table. The experiment is performed by an unskilled person after he experienced a little of preliminary machining training. Experimental results show that corrective machining algorithm is very effective, and anyone can improve the accuracy of hydrostatic table by using the algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.2
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• pp.184-191
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• 2003

A parallel manipulator has high stiffness and all the joint errors on the device are not accumulated at the end -effector unlike a serial manipulator. These are the reasons why the parallel manipulator has been widely used in many fields of industry. In the parallel manipulator, it is very important to predict the exact pose of the end-effector when we want to control the end-effector motion. Installation errors have to be determined in order to predict and control the actual position and pose of the end-effector. This paper presents an algorithm to find the whole 36 joint error components with joint clearance errors and measurement errors considered, when a link length measurement sensor is used and data more than 36 times are acquired for 36 different configurations. A simulation test using this algorithm is performed with a Matlab program which uses the Levenberg-Marquardt method that is known to be efficient for non-linear optimization.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2001.10a
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• pp.91-96
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• 2001

This paper presents a neural net based nonlinear adaptive controller for an autonomous underwater vehicle (AUV). AUV's dynamics are highly nonlinear and their hydrodynamic coefficients vary with different operational conditions, so it is necessary for the high performance control system of an AUV to have the capacities of learning and adapting to the change of the AUV's dynamics. In this paper a linearly parameterized neural network is used to approximate the uncertainties of the AUV's dynamics, and a sliding mode control is introduced to attenuate the effects of the neural network's reconstruction errors and the disturbances of AUV's dynamics. The presented controller is consist of three parallel schemes; linear feedback control, sliding mode control and neural network. Lyapunov theory is used to guarantee the asymptotic convergence of trajectory tracking errors and the neural network's weights errors. Numerical simulations for motion control of an AUV are performed to illustrate to effectiveness of the proposed techniques.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.1
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• pp.10-16
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• 2004

There are a lot of roots of errors in a motion of the optical pick-up actuator being one of the most significantcomponents in a CD-ROM drive. Most of the studios recently performed have a tendency to seek for the causes from an actuator itself. This paper presents dynamic characteristics of an actuator affected by the motion of a feeding deck. The feeding system is modeled as a rigid body with eight degree-of-freedom. Using Largrange's equation, we derive linear equations of motion with respect to the rectangular coordinate. We found that the ranges of the natural frequencies of a feeding deck and the actuator are close to each other. The time responses are also computed by the Newmark method and Runge-Kutta method. The result show that it is important effect to consider feeding deck in modeling and designing an optical pick-up.

• Journal of Integrative Natural Science
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• v.12 no.1
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• pp.14-19
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• 2019

In this paper, we propose a system for controlling the brightness of street lights by predicting pedestrian paths, identifying the position of pedestrians with motion sensing sensors and obtaining motion vectors based on past walking directions, then predicting pedestrian paths through the route prediction smart street lighting system. In addition, by using motion vector data, the pre-treatment process using linear interpolation method and the fuzzy system and neural network system were designed in parallel structure to increase efficiency and the rough set was used to correct errors. It is expected that the system proposed in this paper will be effective in securing the safety of pedestrians and reducing light pollution and energy by predicting the path of pedestrians in the detection of movement of pedestrians and in conjunction with smart street lightings.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.3
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• pp.285-291
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• 2011

The error motion of a machine tool spindle directly affects the surface errors of machined parts. The error motions of the spindle are not desired errors in the three linear direction motions and two rotating motions. Those are usually due to the imperfect of bearings, stiffness of spindle, assembly errors, external force or unbalance of rotors. The error motions of the spindle have been needed to be decreased to desired goal of spindle's performance. The level of error motion is needed to be estimated during the design and assembly process of the spindle. In this paper, the estimation method for the five degree of freedom (5 D.O.F) error motions of the spindle is suggested. To estimate the error motions of the spindle, waviness of shaft and bearings, external force model was used as input data. And, the estimation models are considering geometric relationship and force equilibrium of the five degree of the freedom. To calculate error motions of the spindle, not only imperfection of the shaft, bearings, such as rolling element bearing, hydrostatic bearing, and aerostatic bearing, but also driving elements such as worm, pulley, and direct driving motor systems, were considered.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.103-107
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• 2006

At present, most efforts tend to develop a INS which is only based linear accelerometers, because of the low cost micro-machining gyroscopes lack of the accuracy needed for precise navigation application and possible achieving the required levels of precise for micro-machining accelerometer. Although it was known in theory that a minimum of six accelerometers are required for a complete description of a rigid body motion, and any configuration of six accelerometers (except for a "measure zero " set of six-accelerometer schemes) will work. Studies on the feasible configuration of GF-INS indicate that the errors of angular velocity resolved from the six accelerometers scheme are diverged with time or have multi solutions. The angular velocity errors are induced by the biases together with the position vectors of the accelerometers, therefore, in order to treat with the problem just mentioned, researchers have been doing many efforts, such as the extra three accelerometers or the magnetometers may be taken as the reference information, the extended Kalman filter (EKF) involved to make the angular velocity errors bound and be estimated, and so on. In this paper, the typical configurations of GF-INS are introduced; for each type GF-INS described, the solutions to the angular velocity and the specific force are derived and the characteristic is indicated; one of the corresponding extend Kalman filters are introduced to estimate the angular errors; parts of the simulation results are presented to verify the validity of the equations of angular velocity and specific force and the performance of extend Kalman filter.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.92-97
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• 2002

There are a lot of roots of errors in an motion of the optical pick-up actuator being one of the most significant components in a CD-ROM drive. Most of the studies recently performed have a tendency to seek for the causes from an actuator itself. This paper present the dynamic characteristics of an actuator affected by the motion of a feeding deck. The feeding system is modeled as a rigid body with eight degree-of-freedom. Using Largrange's equation, we derive the linear equations of motion with respect to the rectangular coordinate. We found the fact that the ranges of the natural frequencies of a feeding deck and an actuator are close to each other. And the time responses are also computed by the Newmark method and Runge-Kutta method.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.2033-2036
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• 2004

A novel approach to estimate the real time moving trajectory of an object is proposed in this paper. The object position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Kalman filter and neural networks are utilized. Since the Kalman filter needs to approximate a non-linear system into a linear model to estimate the states, there always exist errors as well as uncertainties again. To resolve this problem, the neural networks are adopted in this approach, which have high adaptability with the memory of the input-output relationship. Kohonen Network(Self-Organized Map) is selected to learn the motion trajectory since it is spatially oriented. The superiority of the proposed algorithm is demonstrated through the real experiments.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.12
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• pp.1379-1387
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• 2011

A PID-feedforward controller and Robust Internal-loop Compensator (RIC) based on reinforcement learning using random variable sequences are provided to auto-tune parameters for each controller in the high-precision position control of PMLSM (Permanent Magnet Linear Synchronous Motor). Experiments prove the well-tuned controller could be reduced up to one-fifth level of tracking errors before learning by reinforcement learning. The RIC compared to the PID-feedforward controller showed approximately twice the performance in reducing tracking error and disturbance rejection.