• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.525-527
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• 1999

In this paper, we propose the target tracking system using fuzzy basis function expansion (FBFN) based on genetic algorithm (GA). In general, the objective of target tracking is to predict the future trajectory of the target based on the past position of the target obtained from the sensor. In the conventional and mathematical method, the parameter uncertainty and the environmental noise may deteriorate the performance of the system. To resolve these problems, we apply artificial intelligent technique to the tracking control of moving targets. The proposed method combines the advantages of both traditional and intelligent technique. The result of numerical simulation shows the effectiveness of the proposed method.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.347-350
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• 1992

In this note, we propose a method for designing a robot controller which can suppress the effects of both the model uncertainty and noisy velocity measurements. The controller is an output feedback compensator of which the constant gains are given in terms of a Riccati equation and a Lyapunov equation. The controller guarantees not only uniform boundedness but uniform ultimate boundedness. The stability result is local but the region can be arbitrarily enlarged at the expense of large control gain. The control law needs neither the exact knowledge of the physical robot parameters nor clean velocity measurements.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.12-15
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• 1988

A controller described in this paper is designed for implicit generalised minimum varience controller with variable time delays in which the weighting polynominals are calculated to reduce the output and control signals variances. This paper is based on the fact that the pole-assigment equation may have multiple solutions if the weighting polynominals are not of minimal order. It is shown that the larger order of the weighting polynominals increment the better is the stochastic behavior of the closed-loop system with variable time delays without changs in the deterministic behavior of the system. Based on this theory, the controller is applied to position control of a three-link manipulater with parameter uncertainty.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.9
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• pp.2257-2264
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• 1994

A method to evaluate the position performance for a stochastically defined planar robot manipulator is presented. Performance is defined as the operational reliability based upon the positional errors of the manipulator tip. An analytical method is developed and applied to a two-link robot manipulator through forward kinematics. This study includes uncertainties in the link length, pin center location and radial clearance. By virtue of the effective link length model, only the nominal manipulator model and statistical information on the uncertainties are required. The results from the analytical method is compared to those from the Monte Carlo simulation.

• Asia pacific journal of information systems
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• v.6 no.1
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• pp.195-222
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• 1996

Faced with the challenge of reducing costs and improving competitive position, firms have recognized outsourcing as an important information systems (IS) strategic option. It has not been understood clearly what determines IS outsourcing. Based on the IS literature and transaction cost economics, cost efficiency related factors were identified, and a questionnaire survey was conducted. The results based on 181 responses from the bank executives in U.S. revealed that vendor production cost advantage and transaction risk are significant predictors of degree of outsourcing and outsourcing preference for data processing services. Insufficiency of IS funds and information technology uncertainty were found to be not only positively associated with vendor production cost advantage, but also directly associated with outsourcing preference and degree of outsourcing. Firm size is, however, not significantly related to vendor production cost advantge and IS outsourcing.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.1072-1077
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• 1992

In ths paper a new active assembly algorithm for chamferless precision parts mating, is considered. The successful assembly task requires an extremely high position accuracy and a good knowledge of mating parts. However, conventional assembly mehtod alone makes it difficult to achieve satisfactory assembly performance because of the complexity and the uncertainties of the process and its environments such as imperfect knowledge of the parts being assembled as well as the limitation of the devices performing the assebled as well as the limitation of the devices performing the assembly. To cope with these problems, a self-learning rule-based assembly algorithm is proposed by intergaring fuzzy set theory and neural network. In this algortihm, fuzzy set theory copes with the complexity and the uncertainties of the assembly process, while neural network enhances the assembly schemen so as to learn fuzzy rules form experience and adapt to changes in environment of uncertainty and imprecision. The performance of the proposed assembly algorithm is evaluated through a series of experiments. The results show that the self-learning fuzzy assembly scheme can be effecitively applied to chamferless precision parts mating.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.10
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• pp.878-886
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• 2004

Uncertainties are inevitable in robotic assembly in unstructured environment since it is difficult to construct fixtures to guide motions of robots. This paper proposes an augmented Petri net and an algorithm to adapt the assembly model on-line during actual assembly process. The augmented Petri net identifies events using force and position information simultaneously. Unmodeled contact states are identified and incorporated into the model on-line. The proposed method increases the level of intelligence of the robot system by enhancing the autonomy. The proposed method is evaluated by simulation and experiments with L-type peg-in-hole assembly using a two-arm robot system.

• Journal of the Korean Society of Industry Convergence
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• v.6 no.4
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• pp.361-366
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• 2003

Most sensor array signal processing methods for multiple source localization require knowledge of the correct shape of array(the correct positions of sensors that consist array), because sensor position uncertainty can severely degrade the performance of array signal processing. In particular, it is assumed that the correct positions of the sensors are known, but the known positions may not represent the true sensor positions. Various algorithms have been proposed for 2-D sensor array shape calibration in far field environment. However, they are not available in near field. In this paper, 3-D sensor array shape calibration algorithm is proposed, which is available in near field.

• Journal of the Korean Society for Precision Engineering
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• v.6 no.4
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• pp.108-118
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• 1989

An adaptive control scheme has been recognized as an effective approach for a robot manipulator to track a desired trajectory in spite of the presence of nonliearity and parameter uncertainty in robot dynamics model. In this paper, an adaptive control scheme for a robot manipulator is proposed to design robust controller using model reference adaptive control technique and hyperstability theory but it does away with] assumption that the process is characterized by a linear model remaining time invariant during the adaptation process. The performance of controller is demonstrated by the simulation about position and speed control of a six-link manipulator with disturbance and payload variation.

• The Bulletin of The Korean Astronomical Society
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• v.35 no.1
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• pp.41.2-41.2
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• 2010

The infrared astronomy satellite AKARI/FIS (Far-Infrared Surveyor) performed all-sky survey in 4 Far-IR bands (50 - 200${\mu}m$ range). It observed around 94% of the whole sky twice or more with a higher spatial resolution and a wider wavelength coverage than that of previous all-sky mission, IRAS. The AKARI/FIS bright source catalogue ${\beta}-2$ is the second released version which included around 290,000 point sources. It provides us with more reliable position and flux information, and around 4 times larger number of sources compared with the first version of catalogue. The sensitivity limit at $90{\mu}m$ band is 0.6 Jy and the estimated flux uncertainty is 20-35% for bright sources. The catalogue will be open to public in this year after the improvement of accuracy, reliability and completeness.