• 한국기계연구소 소보
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• s.19
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• pp.81-92
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• 1989

This paper presents a simple identification method of the actual kinematic parameters for the robot with parallel joints. It is known that Denavit-Hartenberg's coordinate system is not useful for nearly parallel joints. In this paper, the coordinate frames are reassigned to model the kinematic parameter between nearly parallel joints by four parameters. The proposed identification method uses a straight ruler about 1m long. A robot hand is placed by using a teaching pendant at the prescribed points on the ruler, and corresponding error function is defined. The identified kinematic parameters which make the error function zero are obtained by iterative least square error method based on the singular value decomposition. In the compensation of joint angles, only the position is considered because the usual applications of robot do not require a precise orientation control.

• Proceedings of the KIPE Conference
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• 2002.11a
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• pp.49-52
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• 2002

This paper presents neural load torque observer that used to deadbeat load torque observer and regulation of the compensation gain by parameter estimator. As a result, the response of PMSM follows that of the nominal plant. The load torque compensation method is compose of a neural deadbeat observer. To reduce of the noise effect, the post-filter, which is implemented by MA process, is adopted. The parameter compensator with RLSM (recursive least square method) parameter estimator is adopted to increase the performance of the load torque observer and main controller. The parameter estimator is combined with a high performance neural torque observer to resolve the problems. As a result, the proposed control system becomes a robust and precise system against the load torque and the parameter variation. A stability and usefulness, through the verified computer simulation, are shown in this paper.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.540-543
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• 1997

In this paper, a precise trajectory tracking method for mobile robot using a vision system is presented. In solving the problem of precise trajectory tracking, a hierarchical control structure is used which is composed of the path planer, vision system, and dynamic controller. When designing the dynamic controller, non-ideal conditions such as parameter variation, frictional force, and external disturbance are considered. The proposed controller can learn bounded control input for repetitive or periodic dynamics compensation which provides robust and adaptive learning capability. Moreover, the usage of vision system makes mobile robot compensate the cumulative location error which exists when relative sensor like encoder is used to locate the position of mobile robot. The effectiveness of the proposed control scheme is shown through computer simulation.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.3
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• pp.188-195
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• 2004

This paper presents neural load torque observer that is used to deadbeat load torque observer and gain compensation by parameter estimator As a result, the response of the PMSM(permanent magnet synchronous motor) follows that nominal plant. The load torque compensation method is composed of a neural deadbeat observer To reduce the noise effect, the post-filter implemented by MA(moving average) process, is adopted. The parameter compensator with RLSM (recursive least square method) parameter estimator is adopted to increase the performance of the load torque observer and main controller The parameter estimator is combined with a high performance neural load torque observer to resolve the problems. The neural network is trained in on-line phases and it is composed by a feed forward recall and error back-propagation training. During the normal operation, the input-output response is sampled and the weighting value is trained multi-times by error back-propagation method at each sample period to accommodate the possible variations in the parameters or load torque. As a result, the proposed control system has a robust and precise system against the load torque and the Parameter variation. A stability and usefulness are verified by computer simulation and experiment.

• Journal of Power Electronics
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• v.8 no.4
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• pp.354-362
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• 2008

This paper presents neural load torque compensation method which is composed of a deadbeat load torque observer and gains compensation by a parameter estimator. As a result, the response of the PMSM (permanent magnet synchronous motor) obtains better precision position control. To reduce the noise effect, the post-filter is implemented by a MA (moving average) process. The parameter compensator with an RLSM (recursive least square method) parameter estimator is adopted to increase the performance of the load torque observer and main controller. The parameter estimator is combined with a high performance neural load torque observer to resolve problems. The neural network is trained in online phases and it is composed by a feed forward recall and error back-propagation training. During normal operation, the input-output response is sampled and the weighting value is trained multi-times by the error back-propagation method at each sample period to accommodate the possible variations in the parameters or load torque. As a result, the proposed control system has a robust and precise system against load torque and parameter variation. Stability and usefulness are verified by computer simulation and experiment.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.4
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• pp.708-715
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• 2010

In Strapdown Inertial Navigation System, alignment accuracy is the most important factor to determine the performance of navigation. However by an existing self-alignment method, it takes a long time to acquire the alignment accuracy that we want. So, to attain the desired alignment accuracy in as little as $\bigcirc$ minutes, we have developed the precise multi-position alignment method. In this paper, it is proposed a inertial measurement matching transfer alignment method among alignment methods to minimize the alignment error in a short time. It is based on a mixed velocity-DCM matching method be suitable to the operating environment of vertical launching system. The compensation methods to reduce misalign error, especially azimuth angle error incurred by measurement time-delay error and body flexure error are analyzed and evaluated with simulation. This simulation results are finally confirmed by experimentations using FMS(Flight Motion Simulator) in Lab and the integration test to follow the fire control mission.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.7
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• pp.609-614
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• 2005

Parallel manipulators have been used for a variety of applications, including the motion simulators and mechanism for precise machining. Since the ball screws used for linear motion of legs of the Stewart-Gough type parallel manipulator provide wider contact areas than revolute joints, parallel manipulators are usually more affected by frictional forces than serial manipulators. In this research, the method for detecting the frictional forces arising in the parallel manipulator using the gravitational force is proposed. First, the reference trajectories are computed from the dynamic model of the parallel manipulator assuming that it is subject to only the gravitational force without friction. When the parallel manipulator is controlled so that the platform follows the computed reference trajectory, this control force for each leg is equal to the friction force arising in each leg. It is shown that control performance can be improved when the friction compensation based on this information is added to the controller for position control of the moving plate of a parallel manipulator.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1051-1054
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• 2003

For micro-weighing, null balance method is widely used in the precision industrial fields, such as biomedicine, semiconductor, chemistry and so on. In order to obtain high resolution and large measurement range simultaneously, the mechanism should be analyzed and optimized. However, large measurement error can be generated according to the mass loading position and this error is called as a corner loading error. The corner loading error is caused by the parallelism error of a Roberval mechanism used to minimize it. The corner loading error is one of the most dominant error sources that should be removed. It is possible to design that the mechanism has no corner loading error theoretically, but the mechanism of the micro weighing device is very difficult to be realized as original design due to assembling and manufacturing error. For the required specification of the device, the precise manufacturing technique under a few $\mu\textrm{m}$ is required for the realization of the design. In this paper, the effects of the parallelism error are analyzed by using Lagrange method and verified by experiment. Also, the compensation mechanism is proposed and the corner loading error is reduced by restoring tile parallelism.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.2
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• pp.189-198
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• 1997

This paper presents development of a practical tool deflection compensation system in order to reduce the machining error from the tool deflection compensation system in order to reduce the machining error from the tool deflection in the end-milling process. The devised system is a tool adapter which includes 1-axes force sensor for detecting tool deflection and 2-axes tool tilting device for adjusting tool position through computer interface on line process. Experimental in investigations for typical shaped workpieces representing various end milling situations are performed to verify the ability of the system to suppress the surface errors due to tool deflections. With the system, it is possible to get precise machining surface without any excessive machining error due to increased cutting force in more productive machining conditions.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.1
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• pp.99-107
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• 2014

In this paper, a landmark based localization system using a Kinect sensor is proposed and evaluated with the implemented system for precise and autonomous navigation of low cost robots. The proposed localization method finds the positions of landmark on the image plane and the depth value using color and depth images. The coordinates transforms are defined using the depth value. Using coordinate transformation, the position in the image plane is transformed to the position in the body frame. The ranges between the landmarks and the Kinect sensor are the norm of the landmark positions in body frame. The Kinect sensor position is computed using the tri-lateral whose inputs are the ranges and the known landmark positions. In addition, a new matching method using the pin hole model is proposed to reduce the mismatch between depth and color images. Furthermore, a height error compensation method using the relationship between the body frame and real world coordinates is proposed to reduce the effect of wrong leveling. The error analysis are also given to find out the effect of focal length, principal point and depth value to the range. The experiments using 2D bar code with the implemented system show that the position with less than 3cm error is obtained in enclosed space($3,500mm{\times}3,000mm{\times}2,500mm$).