• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.377-382
• /
• 2005

This paper presents a new method for the attitude control of planar space robots. In order to control highly constrained non-linear system such as a 3D space robot, the analytical formulation for the system with complex dynamics and effective control methodology based on the formulation, are not always obtainable. In the proposed method, correspondingly, a non-analytical but effective self-organizing modeling method for controlling a highly constrained system is proposed based on a polynomial data mining algorithm. In order to control the attitude of a planar space robot, it is well known to require inputs characterized by a special pattern in time series with a non-deterministic length. In order to correspond to this type of control paradigm, we adopt the Model Predictive Control (MPC) scheme where the length of the non-deterministic horizon is determined based on implementation cost and control performance. The optimal solution to finding the size of the input pattern is found by a solving two-stage programming problem.

• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.6
• /
• pp.517-523
• /
• 2010

In this paper, we proposed an algorithm to detect aggressive driving status by analysing six kinds of driving patterns, which was achieved by comparing for the feature vectors using mahalanobis distance. The first step is to construct feature matrix of $6{\times}2$ size using frequency response of the time-series accelerometer data. Singular value decomposition makes it possible to find the dominant eigenvalue and its corresponding eigenvector. We use the eigenvector as the feature vector of the driving pattern. We conducted real experiments using three drivers to see the effects of recognition. Although there exists differences from individual drivers, we showed that driving patterns can be recognized with about 80% accuracy. Further research topics will include the development of aggressive driving warning system by improving the proposed technique and combining with post-processing of accelerometer signals.

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2006.05a
• /
• pp.70-73
• /
• 2006

In the present study, the flow-softening behavior occurring during high temperature deformation of AZ31 Mg alloy was investigated. Flow softening of AZ31 Mg alloy was attributed to (1) thermal softening by deformation heating and (2) microstructural softening by dynamic recrystallization. Artificial neural networks method was used to derive the accurate amounts of thermal softening by deformation heating. A series of mechanical tests (High temperature compression and load relaxation tests) was conducted at various temperatures ($250^{\circ}C{\sim}500^{\circ}C$) and strain rates ($10^{-4}/s{\sim}100/s$) to formulate the recrystallization kinetics and grain size relation. The effect of DRX kinetics on microstructure evolution (fraction of recrystallization) was evaluated by the unified SRX/DRX (static recrystallization/dynamic recrystallization) approaches

• Proceedings of the Korean Geotechical Society Conference
• /
• 2008.03a
• /
• pp.393-398
• /
• 2008

With the substantial increase of the size of structure, management and monitoring of excavation for the foundation construction becomes more difficult. Therefore, massive collapses which are related to retaining wall recently increase. However, since the study on measuring and monitoring the pre-stressing force of anchor is insufficient, behavior of anchor may not be predicted and monitored appropriately by the existing strain gauge type monitoring system. FBG Sensor, which is smaller than strain gauge and has better durability and does not have a noise from electromagnetic waves, was adapted to develope a smart anchor. A series of pullout tests were performed to verify the feasibility of smart anchor and find out the load transfer mechanism around the steel wire fixed to rock with grout.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.51 no.2
• /
• pp.82-86
• /
• 2002

A series of $Ni_xZn_yFe_{3-x-y}O_4$ films were prepared by spin-spray ferrite plating on glass substrates from aqueous solution at $90[^{\circ}C]$. The magnetic properties in terms of contents of Ni and Zn in the plated films are presented. All the films are polycrystalline with spinel structure. At x+y=0.58, the film presents preferential orientation. As composition of y in the films increases grain size and void in the films increases, while saturation magnetization and coercive force of the films decrease.

• Journal of Ocean Engineering and Technology
• /
• v.21 no.5
• /
• pp.9-17
• /
• 2007

This paper deals with the design and analysis of a 250kW class impulse turbine for wave energy conversion. Numerical analysis was performed using FLUENT. The size and the performance of a turbine required to provide a certain power can be estimated using a series of performance charts built through the present study. Temporal and spatial variations of flaw fields were also considered and compared with those of uniform inflow. It was concluded that a simple steady-flow analysis using performance charts still provided a practical and useful way to predict the design and performance of turbines.

• Proceedings of the IEEK Conference
• /
• 2008.06a
• /
• pp.1025-1026
• /
• 2008

This paper describes a monocular PSD-based motion capture sensor to employ with commercial video game systems such as Microsoft's XBOX and Sony's Playstation II. The system includes a PSD(Position Sensitive Detector) and active infrared (IR) LED markers that are placed on the object to be tracked. The micro-controller calculates the 3D position of the markers using only the measured intensity and the 2D position on the PSD. A series of experiments were performed to evaluate the performance of our prototype system. From the experimental results we see that the proposed system has the advantages of the compact size, the low cost, the easy installation, and the high frame rates to be suitable for high speed motion tracking in games.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
• /
• 2000.11a
• /
• pp.216-219
• /
• 2000

A Ka Band 3-stage MMIC (Monolithic Microwave Integrated Circuits) LNA(Low Noise Amplifiers) has been designed. The MMIC LNA consists of two single-ended type amplication stapes and one balanced type amplication stage to satisfy noise figure characteristics and high gain and amplitude linearity. The 0.15um pHEMT has been used to provide a ultra low noise figure and high gain amplification. Series and Shunt feedback circuits were inserted to ensure high stability over frequency range of DC to 80 GHz. The size of designed MMIC LNA is 3100mm ${\times}$ 2400um(7.44$\textrm{mm}^2$). The on wafer measured noise figure of the MMIC LNA is less than 2.0 dB over frequency range of 22 GHz to 30 GHz.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.25 no.11
• /
• pp.1802-1812
• /
• 2001

The theoretical method is developed to investigate the effects of ring stiffeners on free vibration characteristics and transient response for the ring stiffened composite cylindrical shells subjected to the impulse pressure Loading. In the theoretical procedure, the Love's thin shell theory combined with the discrete stiffener theory to consider the ring stiffening effect is adopted to formulate the theoretical model. The concentric or eccentric ring stiffeners are laminated with composite and have the uniform rectangular cross section. The modal analysis technique is used to develop the analytical solutions of the transient problem. The analysis is based on an expansion of the loads, displacements in the double Fourier series that satisfy the boundary conditions. The effect of stiffener's eccentricity, number, size, and position on transient response of the shells is examined. The results are verified by comparison with FEM results.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1996.10a
• /
• pp.207-210
• /
• 1996

Learning methodologies such as neural networks or genetic algorithms usually require long training times. Case based reasoning, however, attains peak performance swiftly and is often appropriate for learning even with small data sets. Previous work has shown that an extended case reasoning methodology can yield superior performance in the task of predicting financial data series. This paper examines the impact of reasoning procedures on stock price prediction. The following characteristics are evaluated: size of input vector, multiplicity of neighboring states, and a scaling factor for growth. The concepts are illustrated in the context of predicting the price of an individual price.