• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1352-1355
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• 1997

This paper presents the algorithm for estimating the attitude of an underwater vehicle using EFK. The system model is designed by linerizing the nonlinear Euler angle differential equation and the measurements is a speed logger output. The simulation result shows that the estimation lagorithm is adequate for decreasing attitude errors that grow abruptly during the motion with acceleration and rotation. It also shows that we can adapt the algorithm for compensating initial attitude errors generated after initial leveling.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.1
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• pp.7-12
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• 2012

In this paper, we present an effective viewpoint estimation algorithm for the Moving parallax barrier method of 3D display mobile device. Moving parallax barrier is designed to overcome the biggest problem, the limited view angle. To accomplish it, the position of the viewer's eyes or face should be estimated with strong stability and no latency. We focus on these requirements in the poor performance of mobile processors. We used a pre-processing algorithm in order to overcome the various illumination changes. And, we combined the conventional Viola-Jones face detection method and Optical-flow algorithm for robust and stable viewpoint estimation. Various computer simulations prove the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.746-751
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• 2003

A method of measuring the length of defects on the wall of the spent nuclear fuel pool using the image processing and a laser slit beam is proposed. Since the defect monitoring camera is suspended by a crane and hinged to the crane hook, the camera viewing direction can not be adjusted to the orientation that is exactly perpendicular to the wall. Thus, the image taken by the camera, which is horizontally rotated along the axis of the camera supporting beam, is distorted and thus, the precise length can not be measured. In this paper, by using the LASER slit beam generator, the horizontally rotated angle of the camera is estimated. Once the angle is obtained, the distorted image can be easily reconstructed to the image normal to the wall. The estimation algorithm adopts a 3-dimensional coordinate transformation of the image plane where both the laser slit beam and the original image of the defects exist. The estimation equation is obtained by using the information of the beam projected on the wall and the parameters of this equation are experimentally obtained. With this algorithm, the original image of the defect taken at arbitrary rotated angle can be reconstructed to an image normal to the wall. From the result of a series of experiments, the accuracy of the defect is measured within 0.6 and 1.3 % error bound of real defect size in the air and underwater, respectively under 30 degree of the inclined angle of the laser slit beam generator. Also, the error increases as the inclined angle increases upto 60 degree. Over this angle, the defect length can not be measured since the defect image disappears. The proposed algorithm enables the accurate measurement of the defect length only by using a single camera and a laser slit beam.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.6
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• pp.72-81
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• 1999

A nonlinear engine torque and speed control algorithm using throttle angle control is developed with an engine load torque estimation algorithm. Three 3-dimensional nonlinear engine maps as a part of the nonlinear control algorithm are obtained from steady state engine dynamometer tests. An electric throttle actuator is developed using a stepper motor and a 8 bit micro-processor. The speed control and external load estimation algorithm are tested via engine speed control experiments, and show performance good enough for using various engine torque and speed control applications.

• Journal of Drive and Control
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• v.16 no.2
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• pp.22-29
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• 2019

This study presented a model predictive tracking control algorithm of autonomous truck based on object state estimation using extended Kalman filter. To design the model, the 1-layer laser scanner was used to estimate position and velocity of the object using extended Kalman filter. Based on these estimations, the desired linear path for object tracking was computed. The lateral and yaw angle errors were computed using the computed linear path and relative positions of the truck. The computed errors were used in the model predictive control algorithm to compute the optimal steering angle for object tracking. The performance evaluation was conducted on Matlab/Simulink environments using planar truck model and actual point data obtained from laser scanner. The evaluation results showed that the tracking control algorithm developed in this study can track the object reasonably based on the model predictive control algorithm based on the estimated states.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.26 no.1
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• pp.50-58
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• 2017

This paper proposes a real-time robotic vision control scheme using the weighting matrix to efficiently process the vision data obtained during robotic movement to a target. This scheme is based on the vision system model that can actively control the camera parameter and robotic position change over previous studies. The vision control algorithm involves parameter estimation, joint angle estimation, and weighting matrix models. To demonstrate the effectiveness of the proposed control scheme, this study is divided into two parts: not applying the weighting matrix and applying the weighting matrix to the vision data obtained while the camera is moving towards the target. Finally, the position accuracy of the two cases is compared by performing the slender bar placement task experimentally.

• Proceedings of the KIEE Conference
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• 2001.07e
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• pp.80-85
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• 2001

Frequency is an important operating parameter of a power system. Frequency of a power system remains constant if sum of all the loads plus losses equals total generation in the system. However, the frequency starts to decrease if total generation is less than the sum of loads and tosses. On the other hand, the system frequency increases if total generation exceeds the sum of loads and losses. Electric power systems sustain transient frequency swings whenever the balance between generation and load does not no longer hold. To cope with this Constraints, it requires an accurate and high speedy frequency deviation estimation technique and suitable adjustment to obtain the power system energy balance. The fundamental frequency component of 3-phase signal is first extracted by using an algorithm based on FIR(finite duration impulse response) filter, a phase angle of a voltage. The rate change of the phase angle is used for estimation and speed in its process. Also, to confirm the validity of the proposed algorithm, the simulation results obtained by using EMTP(electro magnetic transients program) are shown.

• Journal of Advanced Navigation Technology
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• v.17 no.4
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• pp.386-395
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• 2013

This paper proposes a root-assisted MUSIC algorithm which uses a combination of the MUSIC and the root-MUSIC algorithm. This algorithm consists of two steps. Firstly, a coarse DOA is computed by the root-MUSIC algorithm. Secondly, a precise DOA estimation is carried out by the MUSIC algorithm in the reduced searching range. This paper analyzes the accuracy and the resolution performance of the proposed DOA estimation method using a software simulation platform.

• Journal of Navigation and Port Research
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• v.28 no.4
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• pp.305-309
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• 2004

The problem for parameters estimation of the received signals impinging on array sensors has long been of great research Interest in a great variety of applications, such as radar, sonar, and land mobile communications systems. Conventional subspace-based algorithms, such as MUSIC and ESPRIT, require an extensive computation of inverse matrix and eigen-decomposition In this paper, we propose a new parameters estimation algorithm via nonlinear minimization, which is simplified computationally and estimates signal parameters simultaneously.

• Smart Structures and Systems
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• v.22 no.4
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• pp.413-424
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• 2018

The factors affecting the shear strength of the angle shear connectors in the steel-concrete composite beams can play an important role to estimate the efficacy of a composite beam. Therefore, the current study has aimed to verify the output of shear capacity of angle shear connector according to the input provided by Support Vector Machine (SVM) coupled with Firefly Algorithm (FFA). SVM parameters have been optimized through the use of FFA, while genetic programming (GP) and artificial neural networks (ANN) have been applied to estimate and predict the SVM-FFA models' results. Following these results, GP and ANN have been applied to develop the prediction accuracy and generalization capability of SVM-FFA. Therefore, SVM-FFA could be performed as a novel model with predictive strategy in the shear capacity estimation of angle shear connectors. According to the results, the Firefly algorithm has produced a generalized performance and be learnt faster than the conventional learning algorithms.