• Journal of Drive and Control
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• v.14 no.2
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• pp.16-22
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• 2017

This paper presents the algorithm of an adaptive model-free-control-based steering control for multi-axle all-terrain cranes for which the recursive least squares with forgetting are applied. To optimally control the actual system in the real world, the linear or nonlinear mathematical model of the system should be given for the determination of the optimal control inputs; however, it is difficult to derive the mathematical model due to the actual system's complexity and nonlinearity. To address this problem, the proposed adaptive model-free controller is used to control the steering angle of a multi-axle crane. The proposed model-free control algorithm uses only the input and output signals of the system to determine the optimal inputs. The recursive least-squares algorithm identifies first-order systems. The uncertainty between the identified system and the actual system was estimated based on the disturbance observer. The proposed control algorithm was used for the steering control of a multi-axle crane, where only the steering input and the desired yaw rate were employed, to track the reference path. The controller and performance evaluations were constructed and conducted in the Matlab/Simulink environment. The evaluation results show that the proposed adaptive model-free-control-based steering-control algorithm produces a sound path-tracking performance.

• International Journal of Highway Engineering
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• v.14 no.1
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• pp.103-109
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• 2012

Digital speedometer which is supposed to provide the basic data for analyzing human factors of drivers has a limitation for human behavior studies of drivers, because it records limited driving information including GPS velocities. Besides, Black Box, which is currently being actively commercialized in the market, records mostly vehicles' risky patterns rather than drivers' behaviors. As a result, it also shows a limit to analyze dangerous driving patterns. This study performed a risky driving study for human factor analysis. This study conducted before and after comparisons for real time warning study using a risky driving judgment device. The analysis was conducted based on Longitudinal acceleration, Lateral acceleration, and Yaw rate of vehicles.

• 한국연소학회:학술대회논문집
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• 2006.10a
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• pp.299-303
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• 2006

From the analysis of fly ash, which contains unburned carbon, collected from the coal-fired Yong Hung power station, most particles are turned out to be hollow cenosphere and agglomerated soot particles. The sooting potential from six coals used in the plant were investigated with CPD model. The results show that the higher potential presented to Peabody, Arthur, Shenhua coals rather than other coals. It is necessary to measure the coal flow rates at each coal feeding pipe for four burner levels since they affect the extent of mixing of soot with oxidant, in turn, the oxidation rate of soot particles. The unbalance in coal flow rate was found in several coal pipes. We successfully reduced unburned carbon in ash by increasing the excess air and changing the SOFA yaw angle.

• Journal of Biosystems Engineering
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• v.15 no.2
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• pp.79-87
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• 1990

An automatic guidance system based upon two position-measurement systems was designed to record where the tractor traveled and to guide the tractor along the predetermined path. An algorithm, using the kinematic behavior of tractor movement, was developed to determine the steering angle to reduce lateral position error. The algorithm was based upon constant travel speed, constant steering rate, and zero slip angles of the tractor wheels. The algorithm was evaluated through use of computer simulation and verified in field experiments. Results showed that the distance interval between position measurements was an important factor in guidance system performance. The position-measurement error of the guidance system must be less than 5 cm to be acceptably precise for field operations. An algorithm based upon a variable steering rate might improve the stability of the guidance system. More accurate measurement of tractor position and yaw angle, and faster error processing are required to improve the field performance of the guidance system.

• Bulletin of the Korean Space Science Society
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• 2003.10a
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• pp.104-104
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• 2003

본 포스터에서는 다목적 위성 2호의 주 탑재체인 MSC(Multi-Spectral Camera)가 TDI(Time Delayed Integration) 방식을 채택함에 따라, TDI에 의해 MSC 영상 자료가 어떻게 영향을 받게 되는 지를 연구한 내용을 설명한다. MSC는 지상 해상도가 1m인 고해상도에서 영상을 촬영하기 때문에 상대적으로 입사 광량이 부족한 문제를 안고 있음에 따라 32 line의 TDI 방식을 사용한다. TDI 방식을 사용하여 MSC에서 직하방향으로 영상을 촬영할 경우, 영상의 가운데 pixel에서 멀어질수록 TDI에 의해 영상의 MTF 값이 떨어지는 결과가 발생한다. 또한, 다목적 위성 2호는 Roll 축을 중심으로 $\pm$30도 Pitch 축을 중심으로 $\pm$30도 tilt를 하여 영상을 촬영하도록 운영될 예정이기 때문에 더더욱 TDI에 의채 영상의 MTF 값이 떨어지는 결과가 발생하게 된다. 이외에도 TDI는 다목적 위성 2호의 고도가 감소하거나, Yaw 축의 변화, Jitter 등에 의해서도 영상의 MTF 값이 감소하게 된다. 물론 MSC CCD pixel의 sampling rate인 Line Rate 값을 각각의 경우에 따라 적절한 값을 부여함으로써 TDI에 의한 MTF 값의 감소를 많은 부분은 수습할 수 있으나 완벽한 보정은 힘든 상황이다.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2012-2015
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• 2003

This paper proposes a pose-invariant face recognition method using cylindrical model and stereo camera. We divided this paper into two parts. One is single input image case, the other is stereo input image case. In single input image case, we normalized a face's yaw pose using cylindrical model, and in stereo input image case, we normalized a face's pitch pose using cylindrical model with estimated object's pitch pose by stereo geometry. Also, since we have advantage that we can utilize two images acquired at the same time, we can increase overall recognition rate by decision-level fusion. By experiment, we confirmed that recognition rate could be increased using our methods.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.126-129
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• 2008

In this study the aerodynamic characteristics of a canard-controlled missile with freely spinning tailfins were investigated by using a CFD code. The aerodynamic coefficients and roll-rate of freely spinning tailfins were calculated by an analysis of 6-DOF and the Euler code. Results were in good agreement with experimental data, and the roll-rates of freely spinning tailfins were also in good agreement with the experimental data for the roll and yaw canard control inputs. This indicates that the CFD Euler code can be applied to predict the canard-controlled missile with freely spinning tailfins.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.9
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• pp.124-129
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• 1997

The purpose of this study is to predict the stability and frequency response of multipurpose vehicle. The vehicle model has seven degrees of freedom. The motion equations are derived by using Lagrangian equation and linearized. The positions of eigenvalues of model which are dominated by lateral velocity, yaw rate, roll rate of sprung mass are used to predict the stability of motion. The resonse of sprung mass to steering wheel is simulated in time domain. It is predicted that the roll response of sprung mass would rather be improved by modifying the position of eigenvalues. The responses of sprung mass to steering wheel are also simulated in frequency domain. The magnitude and phase plots of gains are evaluated in driver's steering input frequency range.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.3
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• pp.261-270
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• 2017

Bad sitting postures are known to cause for a variety of diseases or physical deformation. However, it is not easy to fit right sitting posture for long periods of time. Therefore, methods of distinguishing and inducing good sitting posture have been constantly proposed. Proposed methods were image processing, using pressure sensor attached to the chair, and using the IMU (Internal Measurement Unit). The method of using IMU has advantages of simple hardware configuration and free of various constraints in measurement. In this paper, we researched on distinguishing sitting postures with a small amount of data using just one IMU. Feature extraction method was used to find data which contribution is the least for classification. Machine learning algorithms were used to find the best position to classify and we found best machine learning algorithm. Used feature extraction method was PCA(Principal Component Analysis). Used Machine learning models were five : SVM(Support Vector Machine), KNN(K Nearest Neighbor), K-means (K-means Algorithm) GMM (Gaussian Mixture Model), and HMM (Hidden Marcov Model). As a result of research, back neck is suitable position for classification because classification rate of it was highest in every model. It was confirmed that Yaw data which is one of the IMU data has the smallest contribution to classification rate using PCA and there was no changes in classification rate after removal it. SVM, KNN are suitable for classification because their classification rate are higher than the others.

• International Journal of Aeronautical and Space Sciences
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• v.13 no.4
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• pp.468-473
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• 2012

Cost is an important aspect in designing a target drone, however the poor performance of low cost IMU, GPS, and microcontrollers prevents the use of complex algorithms, such as ARS, or INS/GPS to estimate attitude angles. We propose an autopilot which uses rate gyro and GPS only for a target drone to follow a prescribed path for anti-aircraft training. The autopilot consists of an altitude hold, roll hold, and path following controller. The altitude hold controller uses vertical speed output from a GPS to improve phugoid damping. The roll hold controller feeds back yaw rate after filtering the dutch roll oscillation to estimate the roll angle. The path following controller operates as an outer loop of the altitude and roll hold controllers. A 6-DOF simulation showed that the proposed autopilot guides the target drone to follow a prescribed path well from the view point of anti-aircraft gun training.