• Journal of the Korean Society for Precision Engineering
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• v.18 no.5
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• pp.137-146
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• 2001

A robust controller with the sliding mode is proposed for stable dynamic walking of the biped robot in this paper. For the robot system to be controlled, which is modeled as 14 DOF rigid bodies by the method of multi-body dynamics, the joint angle trajectories are determined by the velocity transformation matrix. Also Hertz force model and Hysteresis damping element are utilized for the ground reaction and impact forces during the contact with the ground. The biped robot system becomes unstable since those forces contain highly confused noise components and some discontinuity, and modeling uncertainties such as parameter inaccuracies. The sliding mode control is applied to solve above problems. Under the assumption of the bounded estimation errors on the unknown parameters, the proposed controller provides a successful way to achieve the stability and good performance in spite of the presence of modeling imprecisions of uncertainties.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.3
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• pp.651-659
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• 1999

This Paper Proposes new speed and electromagnetic torque control of an induction motor, which is robust against time varying parameters. The control is based on adaptive vector control with serial block adaptive algorithm. Motor parameters used to estimates slip frequency and electromagnetic torque. Parameters mismatch in the control system detrimentally affects slip frequency estimation and torque response. In order to compensate lot degradation of the responses, an adaptive identifier for the magnetizing inductance and the secondary time constant is introduced. adaptive vector control system consisted of two subsystems, a vector control system realized on synchronous frame and a parameter identification system on stationary frame. the effectiveness of the proposed method was verified by some digital simulations.

• ETRI Journal
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• v.37 no.6
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• pp.1176-1187
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• 2015

This work proposes a highly efficient sensorless motor driver chip for various permanent-magnet synchronous motors (PMSMs) in a wide power range. The motor driver chip is composed of two important parts. The digital part is a sensorless controller consisting mainly of an angle estimation block and a speed control block. The analog part consists of a gate driver, which is able to sense the phase current of a motor. The sensorless algorithms adapted in this paper include a sliding mode observer (SMO) method that has high robust characteristics regarding parameter variations of PMSMs. Fabricated SMO chips detect back electromotive force signals. Furthermore, motor current-sensing blocks are included with a 10-bit successive approximation analog-to-digital converter and various gain current amplifiers for proper sensorless operations. Through a fabricated SMO chip, we were able to demonstrate rated powers of 32 W, 200 W, and 1,500 W.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.256-263
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• 2010

The paper proposes a sensorless speed control strategy for a PMSM (Permanent Magnet Synchronous Motor) based on a new SMO (Sliding Mode Observer), which substitutes a signum function with a sigmoid function. To apply robust sensorless control of PMSM against parameter fluctuations and disturbance, the high speed SMO is proposed, which estimates the rotor position and angular velocity from the back EMF. The low-pass filter and additional position compensation of the rotor are used to reduce the chattering problem commonly found in sliding mode observer with signum function, which becomes possible by applying the sigmoid function with the control of a switching function. Also the proposed sliding mode observer with the sigmoid function has better efficiency than the conventional sliding mode observer since it adjusts the observer gain by variable boundary layer and estimates the stator resistance. The stability of the proposed sliding mode observer is verified by the Lyapunov second method in determining the observer gain. The validity of the proposed high speed PMSM sensorless velocity control has been demonstrated by real experiments.

• Structural Engineering and Mechanics
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• v.41 no.1
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• pp.25-41
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• 2012

Kriging surrogate model provides explicit functions to represent the relationships between the inputs and outputs of a linear or nonlinear system, which is a desirable advantage for response estimation and parameter identification in structural design and model updating problem. However, little research has been carried out in applying Kriging model to crack identification. In this work, a scheme for crack identification based on a Kriging surrogate model is proposed. A modified rectangular grid (MRG) is introduced to move some sample points lying on the boundary into the internal design region, which will provide more useful information for the construction of Kriging model. The initial Kriging model is then constructed by samples of varying crack parameters (locations and sizes) and their corresponding modal frequencies. For identifying crack parameters, a robust stochastic particle swarm optimization (SPSO) algorithm is used to find the global optimal solution beyond the constructed Kriging model. To improve the accuracy of surrogate model, the finite element (FE) analysis soft ANSYS is employed to deal with the re-meshing problem during surrogate model updating. Specially, a simple method for crack number identification is proposed by finding the maximum probability factor. Finally, numerical simulations and experimental research are performed to assess the effectiveness and noise immunity of this proposed scheme.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.9
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• pp.66-75
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• 1999

Image segmentation is the process where an image is segmented into regions that are set of homogeneous pixels. The result has a ciritical effect on accuracy of image understanding. In this paper, an Markov random field (MRF) image segmentation is proposed using genetic algorithm(GA). We model an image using MRF which is resistant to noise and blurring. While MRF based methods are robust to degradation, these require accurate parameter estimation. So GA is used as a segmentation algorithm which is effective at dealing with combinatorial problems. The efficiency of the proposed method is shown by experimental results with real images and application to automatic vehicle extraction system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.11
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• pp.2094-2105
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• 1994

This paper contains a Hough transform based projection method derived from Radon transform for tracking dim unresolved(sub-pixel) moving targets that move along straight line parths across a time sequential image data. In contrast to several recently presented Hough transform methods using a compressed image referred to as the track map our proposed technique utilizing a set of projections taken along arbitrary orientations effectively increases the changes of target detection, and creates a robust track estimation environment by incorporating all the available knowledge obtained from the projections. Moreover, in order to quantitatively assess the estimation capability of the projection-based Hough transform algorithm, the analytical bounds on the Hough space parameter errors introduced by image space noise contamination are derived. The simulation yielded promising results of estimating the track parameters even under low signal to noise rations when our technique was tested against the time sequential sets of real infrared image data referred to as the HiCamps.

• The Journal of the Acoustical Society of Korea
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• v.16 no.2
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• pp.107-113
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• 1997

To achive a robust Korean word recognition system for both channel distortion and additive noise, maximum a posteriori estimation(MAP) adaptation is proposed and the effectiveness of environmental adaptation for improving recognition performance is investigated in this paper. To do this, recognition experiments using MAP adaptation are carried out for the three different speech ; 1) channel distortion is introduced, 2) environmental noise is added, 3) both channel distortion and additive noise are presented. Theeffectiveness of additive feature parameters, such as regressive coefficients and durations, for environmental adaptation are also investigated. From the speaker independent 100 words recognition tests, we had 9.0% of recognition improvement for the case 1), more than 75% for the case 2), and 11%~61.4% for the case 3) respectively, resulting that a MAP environmental adaptation is effective for both channel distorted and noise added speech recognition. But it turned out that duration information used as additive feature parameter did not played an important role in the tests.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.35T no.1
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• pp.90-98
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• 1998

This paper is to describe the improved vector control which can control the induction motor robustly in low speed. When the induction motor is drived with low speed, below 10 percent of the rated speed, an algorithm which can compensate the error of unit vector angle generated by the harmonics is proposed. Another algorithm which can be tuned to the rotor time constant so that nay be robust to the rotor parameter change in low speed and transient state was proposed. The ripple of flux and torque was reduced by the proposed vector control and then the stable output characteristics was obtained in low speed. When the input and output is sinusoidal, the proposed vector control, the direct vector control and the indirect vector control were analyzed and compared in the low speed characteristics. And each control characteristics is compared and analyzed in state of containing harmonics. The estimation and tunning performance of rotor time constant is confirmed with simulation. The whole control system is implemented by real hardware and experimented to compare the proposed vector control with the direct vector control. As a result of the experiment with two control methods in low speed, the torque ripple of the proposed vector control is improved by 45 percent than the direct vector control. And it is confirmed that the flux current ripple is reduced in 0.2 p.u. and torque current ripple is reduced in 0.6 p.u. It is confirmed that the rotor time constant by the estimation and the tunning algorithm is tunned by the real rotor time constant. Finally, it was confirmed that the validity and robustness for the proposed vector control in low speed existed.

• Journal of Broadcast Engineering
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• v.21 no.1
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• pp.36-42
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• 2016

Recently, many 3D contents have been produced through the multiview camera system. In this system, since a difference of the viewpoint between color and depth cameras is inevitable, the camera parameter plays the important role to adjust the viewpoint as a preprocessing step. The conventional camera calibration method is inconvenient to users since we need to choose pattern features manually after capturing a planar chessboard with various poses. Therefore, we propose a semi-auto camera calibration method using a circular sampling and an homography estimation. Firstly, The proposed method extracts the candidates of the pattern features from the images by FAST corner detector. Next, we reduce the amount of the candidates by the circular sampling and obtain the complete point cloud by the homography estimation. Lastly, we compute the accurate position having the sub-pixel accuracy of the pattern features by the approximation of the hyper parabola surface. We investigated which factor affects the result of the pattern feature detection at each step. Compared to the conventional method, we found the proposed method released the inconvenience of the manual operation but maintained the accuracy of the camera parameters.