• Bulletin of the Korean Mathematical Society
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• v.33 no.2
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• pp.259-265
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• 1996

The history of option valuation problem goes back to the year 1900 when Louis Bachelier deduced on option valuation formula under the assumption that the price process follows standard Brownian motion. More than 50 years later, the research for a mathematical theory of option valuation was taken up by Samuelson ([6]) and others. This work was brought into focus in the major paper by Black and Scholes ([1]) in which a complete option valuation model was derived on the assumption that the underlying price model is a geometric Brownian motion. THis paper starts with subjects developed mainly in Harrison and Kreps ([4]) and in Harrison and Pliska ([5]). The ideas established in these papers are essential for option valuation problem, and in particularfor the point of view that we take in this paper.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.566-571
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• 1994

This paper presents in image-based visual servo control scheme for tracking a workpiece with a hand-eye coordinated robotic system using the fuzzy-neural-network. The goal is to control the relative position and orientation between the end-effector and a moving workpiece using a single camera mounted on the end-effector of robot manipulator. We developed a fuzzy-neural-network that consists of a network-model fuzzy system and supervised learning rules. Fuzzy-neural-network is applied to approximate the nonlinear mapping which transforms the features and theire change into the desired camera motion. In addition a control strategy for real-time relative motion control based on this approximation is presented. Computer simulation results are illustrated to show the effectiveness of the fuzzy-neural-network method for visual servoing of robot manipulator.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.414-421
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• 2007

This paper presents a engine/brake integrated VDC(Vehicle Dynamic Control) system using neural network algorithm methods for wheel slip and yaw rate control. For stable performance of vehicle, not only is the lateral motion control(wheel slip control) important but the yaw motion control of the vehicle is crucial. The proposed NNPI(Neural Network Proportional-Integral) controller operates at throttle angle to improve the performance of wheel slip. Also, the suggested NNPID controller performs at brake system to improve steering performance. The proposed controller consists of multi-hidden layer neural network structure and PID control strategy for self-learning of gain scheduling. Computer Simulation have been performed to verify the proposed neural network based control scheme of 17 dof vehicle dynamic model which is implemented in MATLAB Simulink.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.63.5-63
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• 2002

In this paper, we are concerned with a maneuver detection algorithm which uses the 'lost' measurements down-sampled for computation load saving when a target is in quiescent motion. In general applications of estimation, measurements are available at a relatively high rate, while the estimation processing equipment can only operate at a lower sampling rate. Furthermore, when a target is in nearly quiescent motion, the update of the tracking filter need not to be implemented with maxim urn process power of the filter since the states of the target vary relatively slowly. This does not give serious degradation on the estimation performance. We consider the maneuver detection problem at the case...

• 한국전산유체공학회:학술대회논문집
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• 2010.05a
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• pp.289-294
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• 2010

Numerical stud of an oscillating body in incompressible fluid is performed. Stabilized finite element method comprising of Streamline-Upwind/Petrov-Galerkin (SUPG) and Pressure-Stabilizing/Petrov-Galerkin (PSPG) formulations of linear triangular elements was employed to solve 2D incompressible Navier-Stokes equations whereas the motion of the body was considered by incorporating the arbitrary Langrangian-Eulerian(ALE) formulation. An algebraic moving mesh strategy is utilized for obtaining body conforming mesh deformation at each time step. Two tests cases, namely motion of a circular cylinder and of an airfoil in incompressible flow were analyzed. The model is first validated against the stationary cases and then the capability to handle moving boundaries is demonstrated.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.685-688
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• 1996

In debureing process. Human experts who have long experenc in performing deburring tasks can manipulate tools efficiently and adapt the tool motions according to the state of the process based on their skills. However, human experts have difficulties in describing linguistically their control schemes and strategies because teey don't aware the detailed process in interpreting wensory information and adapting tool motion. Therefore, it is important to develop a mean of understanding the skills and acquiring the control schemes so that the robot can perform the same skillful motion as the human experts. In this paper, an expert's skill model is developed so that it can be transferred effectively from the expertt to the robot. Skills are represented by a mapping which is generated by using a neural network. Expert's skill shows that the robot is able to associate a correct control strategy with process characteristics which is acquired from a vision image in a similar manner to a human expert's

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.112-117
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• 1997

This paper presents a GA(Genetic Algorithms)-Optical control strategy for the control of the swing motion and the transverse position of the overhead crane. The overhead crane system is defined uncertain due to unknown system parameters such as payload and trolly mass. To control the overhead crane. the GA-Optimal control scheme is suggested. which transfers a trolly to a desired place as fast as possible and minimizes the swing of the payload during the transfer. The genetic algorithms are applied to fine digital optimal feedback gains. A computer simulation demonstrate the performance of the proposed the GA-digital optimal controller for the overhead crane.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.743-750
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• 2000

This paper presents an equivalent linearization method and application to the equations of motion of a 6 degree-of-freedom PRRS HexaSlide type parallel manipulators which are characterized as the architecture with constant link lengths that are attached to moving sliders on the ground and to a mobile platform. Since dynamic equations of parallel manipulators are complicated and highly nonlinear, control bandwidth, adjustable control gain as well as vibration characteristics cannot be easily found. The proposed equivalent linearization method can be applied over specified workspace as well as on a path of mobile platform. Through an equivalent linearization method, one can easily get a simple linear dynamic model. This linearized dynamic model may be utilized in a simplified computed torque control strategy.

• Proceedings of the KSR Conference
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• 2003.10c
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• pp.401-405
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• 2003

This paper presents a design strategy of the dynamic simulator for the Korean tilting train. The tilting train simulator will generate the tilting motion to the lateral acceleration date obtained from the train dynamic analysis. The simulator will be composed of five components: (1) GUI control panel, (2) train dynamic analysis part, (3) tilting control part, (4) motion base with 6 electrical-motor-driven actuators and (5) visualization system. Using the simulator, we will verify the dynamic behaviors of the tilting train, interfaces among subparts and ride comfort before manufacturing of the tilting train.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.23.1-23
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• 2001

The unmanned vehicle is composed of three parts the front & side sensor system for keeping the lane and avoiding obstacles, the acceleration & brake control system for longitudinal motion control, and the steering control system for the lateral motion control. Each system helps the unmanned vehicle of which should take notice of its location and recognize obstacles around the place by itself and make a decision how much fast to proceed according to circumstances. During the operation, the control strategy that the vehicle can detect obstacles and avoid collision on the road involves with vehicle velocity very much. Therefore, We have to define a traction system which is powered by DC motor so that, unmanned vehicle can control its velocity accurately. In this study, we find mechanical and ...