• Proceedings of the KIPE Conference
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• 2004.07a
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• pp.316-320
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• 2004

This paper presents an advanced method for an initial pole position estimation of a PMLSM (Permanent Magnet Linear Synchronous Motor) that has an incremental encoder for servo applications but does not have Hall sensors as a magnetic pole sensor. The proposed algorithm finds either of two zero force positions and then the correct d-axis by appropriately using the secant method as a numerical method. It only requires the tuned current controller and the relative position information and so it can be simply applicable to a rotary PMSM. The experimental results show the validity of the proposed method with respect to accurate pole position estimation under the minimal moving distance during estimation process.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.6
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• pp.1010-1019
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• 1994

It is shown that there exists a nonlinear mapping which transforms image features and their changes to the desired camera motion without measuring of the relative distance between the camera and the object. This nonlinear mapping can eliminate several difficulties occurring in computing the inverse of the feature Jacobian as in the usual feature-based visual feedback control methods. Instead of analytically deriving the closed form of this mapping, a Fuzzy Membership Function-based Neural Network (FMFNN) incorporating a Fuzzy-Neural Interpolating Network is used to approximate the nonlinear mapping. Several FMFNN's are trained to be capable of tracking a moving object in the whole workspace along the line of sight. For an effective implementation of the proposed FMF network, an image feature selection process is investigated. Finally, several numerical examples are presented to show the validity of the proposed visual servoing method.

• Journal of the Korea Society for Simulation
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• v.3 no.1
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• pp.17-28
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• 1994

A statistical procedure is developed to estimate the relative difference between two parameters each obtained from either true model or approximate model. Double sample procedure is applied to find the additional number of simulation runs satisfying the preassigned absolute precision of the confidence interval. Two types of parameters, mean and standard deviation, are considered as the performance measures and tried to show the validity of the model by examining both queues and inventory systems. In each system it is assumed that there are three distinct means and their own standard deviations and they form the simultaneous confidence intervals but with control in the sense that the absolute precision for each confidence interval is bounded on the limits with preassigned confidence level. The results of this study may contribute to some situations, for instance, first, we need a statistical method to compare the effectiveness between two alternatives, second, we find the adquate number of replications with any level of absolute precision to avoid the unrealistic cost of running simulation models, third, we are interested in analyzing the standard deviation of the output measure, ..., etc.

• Journal of the Optical Society of Korea
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• v.16 no.1
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• pp.29-35
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• 2012

We propose a subpixel scale elemental image generation method to correct the errors created by finite display pixel size in integral imaging. In this paper, two errors are mainly discussed: pickup-and-display mismatch error and mismatch error between pixel pitch and lens pitch. The proposed method considers the relative positions between lenses and pixels in subpixel scale. Our proposed pickup method calculates the position parameters, generates an elemental image with pixels completely inside the lens, and generates an elemental image with border pixels using a weighted sum method. Appropriate experiments are presented to verify the validity of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1042-1046
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• 1993

This paper describes a control scheme for a robot manipulator system which uses visual information to position and orientate the end-effector. In this scheme, the position and orientation of the target workpiece with respect to the base frame of the robot are assumed to be unknown, but the desired relative position and orientation of the end-effector to the target workpiece are given in advance. The control scheme directly integrates visual data into the servoing process without subdividing the process into determination of the position and orientation of the workpiece and inverse kinematics calculation. A neural network system is used for determining the change in joint angles required in order to achieve the desired position and orientation. The proposed system can be control the robot so that it approach the desired position and orientation from arbitrary initial ones. Simulation for the robot manipulator with six degrees of freedom will be done. The validity and the effectiveness of the proposed control scheme will be verified by computer simulations.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.410-414
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• 1996

A visual servoing algorithm is proposed for a robot with a camera in hand. Specifically, novel image features are suggested by employing a viewing model of perspective projection to estimate relative pitching and yawing angles between the object and the camera. To compensate dynamic characteristics of the robot, desired feature trajectories for the learning of visually guided line-of-sight robot motion are obtained by measuring features by the camera in hand not in the entire workspace, but on a single linear path along which the robot moves under the control of a, commercially provided function of linear motion. And then, control actions of the camera are approximately found by fuzzy-neural networks to follow such desired feature trajectories. To show the validity of proposed algorithm, some experimental results are illustrated, where a four axis SCARA robot with a B/W CCD camera is used.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.05a
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• pp.494-497
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• 2006

The objectives of this study are to develop and evaluate the Neural Network algorithm which can predict the inelastic shortening such as the creep strain and the drying shrinkage strain of reinforced concrete members using the previous test data. New learning algorithms for the prediction of creep strain and the drying shrinkage strain are proposed focusing on input layer components and a normalization method for input data and their validity is examined through several test data. In Neural Network algorithm, the main input data to be trained are the compressive strength of the concrete, volume to surface ratio, curing condition, relative humidity, and the applied load. The results show that the new algorithms proposed herein successfully predict creep strain and the drying shrinkage strain.

• 유체기계공업학회:학술대회논문집
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• 2001.11a
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• pp.63-68
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• 2001

A numerical analysis to predict the flow characteristics in turbo fan for vacuum cleaner has been performed by using CFD. The rotating reference frame method is applied to compute the impeller-diffuser interaction and the characteristics of two models, 460 and 380, are calculated for various rotating speeds and flow rates. The flow in impeller, diffuser and return channel is assumed as steady and compressible. STAR-CD with k- $\epsilon$ turbulence model is used to solve the Navier-Stokes equations. Computed relative velocity, absolute pressure and flow angles are shown and compared with measurement results. The good agreement between the predictions and measurement results confirms the validity of this study.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.131.4-131
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• 2001

A lot of path planning algorithms have been developed to find the collision-free path with minimum cost. But most of them require complicated computations. In this paper, a thinning method, which is one of the image processing schemes, was adopted to simplify the path planning procedure. In addition, critical points are used to find the shortest-distance path among all possible paths from the start to the goal point. Since the critical points contain the information on the neighboring paths, a new path can be quickly obtained on the map even when the start and goal points change. To investigate the validity of the proposed algorithm, various simulations have been performed for the environment where the obstacles with arbitrary shapes exist. It is shown that the optimal paths can be found with relative easiness.

• International Journal of Aeronautical and Space Sciences
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• v.8 no.1
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• pp.129-139
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• 2007

In this paper, attitude control laws for simultaneous pointing of multiple spacecrafts are considered under a formation flying scenario. The basic approach lies in adaptive feedback gains using relative attitude information or maneuver time approximation for coordinated attitude control. Each control law is targeted to balancing mean motion or to correcting system response to the slowest satellite. The control gain adaptation is constructed by two approaches. The first one is using variable damping gain to manipulate speed of a fast system response, and the second one uses alternate natural frequency of the system under control. The validity and stability of the proposed approaches are examined analytically and tested through numerical simulations.