• Journal of Astronomy and Space Sciences
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• 제28권3호
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• pp.193-201
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• 2011

A strategy for geostationary orbit (or geostationary earth orbit [GEO]) surveillance based on optical angular observations is presented in this study. For the dynamic model, precise analytical orbit model developed by Lee et al. (1997) is used to improve computation performance and the unscented Kalman filer (UKF) is applied as a real-time filtering method. The UKF is known to perform well under highly nonlinear conditions such as surveillance in this study. The strategy that combines the analytical orbit propagation model and the UKF is tested for various conditions like different level of initial error and different level of measurement noise. The dependencies on observation interval and number of ground station are also tested. The test results shows that the GEO orbit determination based on the UKF and the analytical orbit model can be applied to GEO orbit tracking and surveillance effectively.

• International Journal of Aeronautical and Space Sciences
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• 제18권2호
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• pp.327-333
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• 2017

This study presents the orbit determination (OD) of a candidate Korea Regional Navigation Satellite System (KRNSS) using both inter-satellite links (ISLs) and ground observations. The candidate constellation of KRNSS is first introduced. The OD algorithm based on both ISL and ground observation is developed, and consists of three main components: dynamic model for Korean navigation satellites, measurement model for ISLs and ground observations, and the batch least-square filter for estimating OD parameters. As numerical simulations are performed to analyze the OD performances, the present study focuses on investigating the effects of ISL measurements on the OD accuracy of KRNSS. Simulation results show that the use of ISLs can considerably enhance the OD accuracy to one meter (design preference) under certain distributions of ground stations.

• Wind and Structures
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• 제5권2_3_4호
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• pp.151-164
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• 2002

Predictions of the pedestrian level wind speeds for the downtown area of Auckland that have been obtained by wind tunnel and computational fluid dynamic (CFD) modelling are presented. The wind tunnel method involves the observation of erosion patterns as the wind speed is progressively increased. The computational solutions are mean flow calculations, which were obtained by using the finite volume code PHOENICS and the $k-{\varepsilon}$ turbulence model. The results for a variety of wind directions are compared, and it is observed that while the patterns are similar there are noticeable differences. A possible explanation for these differences arises because the tunnel prediction technique is sensitivity to gust wind speeds while the CFD method predicts mean wind speeds. It is shown that in many cases the computational model indicates high mean wind speeds near the corner of a building while the erosion patterns are consistent with eddies being shed from the edge of the building and swept downstream.

• 조명전기설비학회논문지
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• 제27권10호
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• pp.101-106
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• 2013

This paper proposes the new high precision monitoring sensor for the Marine Installation. Among variety of sensor network systems, wireless information transmission through the marine is one of the enabling technologies for the development of future marine-observation systems and sensor networks. Applications of marine monitoring range from oil industry to aquaculture, and include instrument monitoring, pollution control, climate recording, prediction of natural disturbances. For these marine applications to be available, however, the provision of precise location information using monitoring sensor is essential. In this paper, the dynamic characteristics for obtaining the location information of monitoring sensor is analyzed. The theoretical and experimental studies have been carried out. The presented results from the above investigation show considerably excellent performance for the Monitoring for the Marine Installation.

• Journal of Power Electronics
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• 제15권6호
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• pp.1559-1566
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• 2015

The brushless DC motor (BLDCM) has many advantages. As a result, it is widely used in electric vehicle (EV) drive systems. To improve the reliability of the motor control system, a position sensorless control strategy based on a sliding mode observer (SMO) is proposed. The global fast terminal sliding mode observer (GFTSMO) is proposed to enhance the control performance of the SMO control system. The advantages of the linear sliding mode and the nonsingular terminal sliding mode (NTSM) are combined in the control strategy. The convergence speed of the system state is enhanced. The motor commutation point is obtained with the observation of the back EMF, and the instantaneous torque value of the motor is calculated. Therefore, the position sensorless control of the BLDCM is realized. Experimental results show that the proposed control strategy can improve the convergence speed, dynamic characteristics and robustness of the system.

• Macromolecular Research
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• 제13권2호
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• pp.152-155
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• 2005

A dynamic density functional theory is presented for the observation of the phase revolutions of a solution-casting film of di- and tri-block copolymers under solvent evaporation conditions. With the evaporation of the solvent, the inverted phases, the minor part of the component becomes the continuous phase at the higher solvent evaporation rate, as observed in this experiment. Further simulation revealed that these inverted phases are converted into the normal phase and the major part of the component becomes the continuous phase, implying that the inverted phases observed in this experiment are unstable.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.16-21
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• 2005

This paper considers the problem of state estimation in linear continuous-time systems with multi-sensor environment and observation uncertainties. We propose two suboptimal filtering algorithms for these types of systems. The filtering algorithms consist of two steps: The local optimal Kalman estimates are computed at the first step. And, these local estimates are lineally fused at the second step. The implementation of the two-step filtering algorithms needs a lower memory demand than the optimal Kalman and adaptive Lainiotis-Kalman filters. In consequence of parallel structure of the proposed filters, the parallel computers can be used for their design. The examples exhibit the effect of common noise on the performance of fusion of the local Kalman estimates based on observations from different sensors and in the presence of uncertainties.

• 제어로봇시스템학회논문지
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• 제14권8호
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• pp.779-784
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• 2008

This paper presents Kalman filter based system modeling algorithm for autonomous robot systems. State of the robot system is measured using embedded sensor systems and then carried to a host computer via ubiquitous sensor network (USN). We settle a linear state-space motion equation for unknown robot system dynamics and modify a popular Kalman filter algorithm in deriving suitable parameter estimation mechanism. To represent time-delay nature due to network media in system modeling, we construct an augmented state-space model which is mainly composed of original state and estimated parameter vectors. We conduct real-time experiment to test our proposed estimation algorithm where speed state of the constructed robot is used as system observation.

• 한국환경과학회지
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• 제16권12호
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• pp.1439-1449
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• 2007

Heavy snowfall was occurred over the south-western part of the Korean Peninsula called as Honam Districts, on two days from 21 December 2005. The development mechanism of snowfall and its characteristics were analysed using observation and numerical data provided by Korea Meteorological Administration. In comparison with other years Arctic air mass developed and maintained during all December 2005 due to active planetary waves with three branches. And jet streams at lower and higher levels make easy development of snow convection cells. Especially thermal low induced by mesoscale heat and dynamic sources, also help the developments of convection cells in strong ascension. The understanding the relation between synoptic and mesoscale circumstance, therefore, is also important to predict the heavy snowfall and to prevent the disaster.

• 한국지능시스템학회논문지
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• 제11권5호
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• pp.395-399
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• 2001

이 논문은 학습을 통해 관측 데이터로부터 퍼지 추론 모듈을 생성할 수 있는 적응 능력을 갖는 모듈화 퍼지추론 시스템을 제안한다. 제안한 시스템은 TS 퍼지모델과 모듈화 신경회로망의 구조적 유사성을 기초로 한다. 학습과정은 새로운 퍼지추론 모듈의 생성과 모듈 파라미터의 갱신으로 구성된다. 퍼지추론 모듈은 국부모델망과 퍼지 게이팅망으로 구성된다. 제안한 시스템의 파라미터들은 표준 LMS 알고리즘을 이용하여 최적화된다. 제안한 시스템의 성능은 비선형 동적 시스템 적응제어에의 응용을 통해서 입증된다.