• Journal of Positioning, Navigation, and Timing
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• v.2 no.2
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• pp.123-130
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• 2013

Autonomous agricultural machines that are operated in small-scale farmland frequently experience turning and changes in direction. Thus, unlike when they are operated in large-scale farmland, the steering control systems need to be controlled precisely so that travel errors can be minimized. This study aims to develop a control algorithm for improving the path tracking performance of a steering system by analyzing the effect of the setting of the waypoint, which serves as the reference point for steering when an autonomous agricultural machine moves along a path or a coordinate, on control errors. A simulation was performed by modeling a 26-hp tractor steering system and by applying the equations of motion of a tractor, with the use of a computer. Path tracking errors could be reduced using an algorithm which sets the waypoint for steering on a travel path depending on the radius of curvature of the path and which then controls the speed and steering angle of the vehicle, rather than by changing the steering speed or steering ratio which are dependent on mechanical performance.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.2 s.95
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• pp.201-210
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• 1999

One of the major limitations of productivity and quality in metal cutting is the machining accuracy of machine tools. The machining accuracy is affected by geometric and thermal errors of the machine tools. Therefore, a key requirement for improving te machining accuracy and product quality is to reduce the geometric and thermal errors of machine tools. This study models geometric error for error analysis and develops on-machine measurement system by which the volumetric erors are measured. The geometric error is modeled using form shaping function(FSF) which is defined as the mathematical relationship between form shaping motion of machine tool and machined surface. The constant terms included in the error model are found from the measurement results of on-machine measurement system. The developed on-machine measurement system consists of the spherical ball artifact (SBA), the touch probe unit with a star type stylus, the thermal data logger and the personal computer. Experiments, performed with the developed measurement system, show that the system provides a high measuring accuracy, with repeatability of ${\pm}2{\mu}m$ in X, Y and Z directions.

• Journal of the Korea Computer Industry Society
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• v.5 no.1
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• pp.123-130
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• 2004

In this paper, an advanced error tracking algorithm by using feedback channel was proposed for error resilient transmission. Using this proposed algorithm, the propagation of errors were reduced within the decoded data over bit error prone network. The addresses of corrupted blocks are reported to encoder by decoder. With negative acknowledgments of feedback channel, the encoder can precisely calculate negative acknowledgments and track the propagated errors by examining the backward motion dependency for proper pixel in the current encoding frame. The error-propagation effects can be terminated completely by INTRA refreshing the affected macro-blocks by using proposed error tracking algorithm. By utilizing the selective four-corner error tracking approximation, the error tracking computations of the proposed algorithm is less than that of the algorithm using full pixel without substantial degradation in video quality. The proposed algorithm can track errors rapidly and accurately.

• Journal of the Korean Institute of Navigation
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• v.23 no.3
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• pp.35-44
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• 1999

This research aims to seek active control of ball-beam position stability by resorting to neural networks whose layers are given bias weights. The controller consists of an LQR (linear quadratic regulator) controller and a neural networks controller in parallel. The latter is used to improve the responses of the established LQR control system, especially when controlling the system with nonlinear factors or modelling errors. For the learning of this control system, the feedback-error learning algorithm is utilized here. While the neural networks controller learns repetitive trajectories on line, feedback errors are back-propagated through neural networks. Convergence is made when the neural networks controller reversely learns and controls the plant. The goals of teaming are to expand the working range of the adaptive control system and to bridge errors owing to nonlinearity by adjusting parameters against the external disturbances and change of the nonlinear plant. The motion equation of the ball-beam system is derived from Newton's law. As the system is strongly nonlinear, lots of researchers have depended on classical systems to control it. Its applications of position control are seen in planes, ships, automobiles and so on. However, the research based on artificial control is quite recent. The current paper compares and analyzes simulation results by way of the LQR controller and the neural network controller in order to prove the efficiency of the neural networks control algorithm against any nonlinear system.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.629-634
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• 2000

Generally, the accuracy of motion control systems is strongly influenced by both the mechanical characteristics and servo characteristics of feed drive systems. In the fed drive systems of machine tools that consist of mechanical parts and electrical parts, a torsional vibration is often generated because of its elastic elements in torque transmission. Especially, a torsional vibration caused by the elasticity of mechanical elements might deteriorate the quick movement of system and lead to shorten the life time of the mechanical transmission elements. So it is necessary to analyze the electromechanical system mathematically to optimize the dynamic characteristics of the feed drive system. In this paper, based on the simplifies feed drive system model, radius errors due to position gain mismatch and servo response characteristic have been developed and an optimal criterion for tuning the gain of speed controller is discussed. The proportional and integral parameter gain of the feed drive controller are optimal design variables for the gain tuning of PI speed controller. Through the optimization problem formulation, both proportional and integral parameter are optimally tuned so as to compensate the radius errors by using the genetic algorithm. As a result, higher performance on circular profile tests has been achieved than the one with standard parameters.

• Journal of Biosystems Engineering
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• v.30 no.5 s.112
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• pp.293-298
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• 2005

The purpose of this study was the development of a multi-joint robot manipulator for milking robot system. The multi-joint robot manipulator was controlled by 5 drivers with driver controller through the position information obtained from the image processing system. The robot manipulator to automatically attach each teat cup to the teats of a milking cow was developed and it's motion was accurately measured with error rate. Results were as follows. 1. Maximum errors in position accuracy were 4mm along X-axis, 4.5mm along Y-axis and 0.9mm along Z-axis. Absolute distance errors were maximum 4.8mm, minimum 2.7mm, and average 3.6mm. 2. Errors of repeatability were maximum 3.0mm along X-axis, 3.0mm along Y-axis, and 0.5mm along Z-axis. Distance error values were maximum 3.2mm, minimum 2.2mm, and average 2.5mm. It is envisaged that multi-joint robot manipulator can be applicate to milking robot system being developed in consideration of the experiment results.

• ETRI Journal
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• v.27 no.1
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• pp.53-63
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• 2005

A compressed video bitstream is sensitive to errors that may severely degrade the reconstructed images even when the bit error rate is small. One approach to combat the impact of such errors is the use of error concealment at the decoder without increasing the bit rate or changing the encoder. For spatial-error concealment, we propose a method featuring edge continuity and texture preservation as well as low computation to reconstruct more visually acceptable images. Aiming at temporal error concealment, we propose a two-step algorithm based on block matching principles in which the assumption of smooth and uniform motion for some adjacent blocks is adopted. As simulation results show, the proposed spatial and temporal methods provide better reconstruction quality for damaged images than other methods.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.191-196
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• 2003

This paper presents a method to design an adaptive controller for the kinematic model of a two-wheeled welding mobile robot (WMR) with unknown parameters. We propose a nonlinear controller based on the Lyapunov function to enhance the tracking properties of the WMR. The WMR can track any smooth curved welding path at a constant velocity of the welding point. The system has three degrees of freedom including two wheels and one torch slider. Torch slider motion is used for fast tracking. To design the tracking performance, the errors from WMR to steel wall is defined, and the controller is designed to drive the errors to zero as fast as possible. The effectiveness of the proposed controller is shown through simulation results.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.830-835
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• 1995

To quickly determine the effect of the substitute component on the machine's performance is very important in the defign and the manufacturing processes. And minimizing machine cost and maximizing machine quality mandata predictability of machine accuracy. In the study, in order to evaluate the effects of the component's geometric errors and dimensions on the machining accuracy of gantry-type 5-axis machining centers, a geometric error analysis and virtual manufacturing system is developed based on the mathematical model for the shape generation motion of machine tool considering the component's geometric errors and dimensions, the solid modeling techniques and so on.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.552-558
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• 1993

In this paper, control of a planar two-link structurally flexible robotic manipulator executing unconstrained and constrained maneuvers is considered. The dynamic model, which is obtained by using the extended Hamilton's principle and the Galerkin criterion, includes the impact force generated during the transition from unconstrained to constrained segment of the robotic task. A method is presented to obtain the linearized equations of motion in Cartesian space for use in designing the control system. The linear quadratic Gaussian with loop transfer recovery (LQG/LTR) design methodology is exploited to design a robust feedback control system that can handle modeling errors and sensor noise, and operate on Cartesian space trajectory errors. The LQG/LTR compensator together with a feedforward loop is used to control the flexible manipulator. Simulated results are presented for a numerical example.