• 한국정보통신학회논문지
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• 제10권4호
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• pp.769-774
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• 2006

본 논문에서는 능동현가장치의 해석 및 설계에 최소위상시스템개념을 적용하여 제어시스템설계에 응용 할 수 있는 이론적 수식모델링에 관한 연구를 수행하였다. 최근의 현가장치설계에서는 강성과 댐핑을 능동적으로 제어하는 기술의 적용이 일반화 되고 있으며, 다른 차량안정성제어장치와의 연계성이 높아짐에 따라, 제어시스템설계에서 보다 내구성이 강하고 제어효과의 응답성이 빠르며 정도 또한 높은 제어장치의 필요성이 요구되고 있다. 본 연구는 센서와 액츄에이터의 위치관계에 따른 능동현가장치의 위상시스템을 해석하여 위와 같은 빠른 응답성과 높은 정도의 제어가 가능한 제어시스템을 해석, 설계하기 위하여 제어장치의 대칭성에 관한 해석을 하였다. 그리고 대칭인 대상시스템에 관한 대칭 제어시스템을 설계하기 위한 모델링 및 적용방법을 수식적으로 해석하였으며, 현가장치의 제어시스템설계에 중요한 내외란성 향상을 위한 강인제어시스템설계에 적용하는 방법에 관해 고찰하였다.

• 한국전산유체공학회지
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• 제7권1호
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• pp.10-19
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• 2002

The non-staggered(collocated) grid approach in which all the solution variables are located at the centers of control volumes is very popular for incompressible flow analyses because of its numerical efficiency on the curvilinear or unstructured grids. Rhie and Chow's paper is the first in using non-staggered grid method for SIMPLE algorithm, where pressure weighted interpolation was used to prevent decoupling of pressure and velocity. But it has been known that this non-staggered grid method has stability problems when pressure fields are nonlinear like in natural convection flows. Also Rhie-Chow scheme generates large numerical diffusion near curved walls. The cause of these unwanted problems is too large pressure damping term compared to the magnitude of face velocity. In this study the magnitude of pressure damping term of Rhie-Chow's method is limited to 1∼10% of face velocity to prevent physically unreasonable solutions. The wall pressure extrapolation which is necessary for cell-centered FVM is another source of numerical errors. Some methods are applied in a unstructured FV solver and analyzed in view of numerical accuracy. Here, two natural convection problems are solved to check the effect of the Rhie-Chow's method on numerical stability. And numerical diffusion from Rhie-Chow's method is studied by solving the inviscid flow around a circular cylinder.

• 대기
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• 제32권2호
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• pp.163-178
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• 2022

This study aims to evaluate the accuracy of retrieved horizontal winds with different quality control methods from three Doppler lidars deployed over the complex terrain during the PyeongChang 2018 Olympic and Paralympic games. To retrieve the accurate wind profile, this study also proposes two quality control methods to distinguish between meteorological signals and noises in the Doppler velocity field, which can be broadly applied to different Doppler lidars. We evaluated the accuracy of retrieved winds with the wind measurements from the nearby or collocated rawinsondes. The retrieved wind speed and direction show a good agreement with rawinsonde with a correlation coefficient larger than 0.9. This study minimized the sampling error in the wind evaluation and estimation, and found that the accuracy of retrieved winds can reach ~0.6 m s^-1 and 3° in the quasi-homogeneous wind condition. We expect that the retrieved horizontal winds can be used in the high-resolution analysis of the horizontal winds and provide an accurate wind profile for model evaluation or data assimilation purposes.

• Smart Structures and Systems
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• 제16권2호
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• pp.295-328
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• 2015

In recent years the monitoring of structural behavior through acquisition of vibrational data has become common practice. In addition, recent advances in sensor development have made the collection of diverse dynamic information feasible. Other than the commonly collected acceleration information, Global Position System (GPS) receivers and non-contact, optical techniques have also allowed for the synchronous collection of highly accurate displacement data. The fusion of this heterogeneous information is crucial for the successful monitoring and control of structural systems especially when aiming at real-time estimation. This task is not a straightforward one as measurements are inevitably corrupted with some percentage of noise, often leading to imprecise estimation. Quite commonly, the presence of noise in acceleration signals results in drifting estimates of displacement states, as a result of numerical integration. In this study, a new approach based on a time domain identification method, namely the Unscented Kalman Filter (UKF), is proposed for correcting the "drift effect" in displacement or rotation estimates in an online manner, i.e., on the fly as data is attained. The method relies on the introduction of artificial white noise (WN) observations into the filter equations, which is shown to achieve an online correction of the drift issue, thus yielding highly accurate motion data. The proposed approach is demonstrated for two cases; firstly, the illustrative example of a single degree of freedom linear oscillator is examined, where availability of acceleration measurements is exclusively assumed. Secondly, a field inspired implementation is presented for the torsional identification of a tall tower structure, where acceleration measurements are obtained at a high sampling rate and non-collocated GPS displacement measurements are assumed available at a lower sampling rate. A multi-rate Kalman Filter is incorporated into the analysis in order to successfully fuse data sampled at different rates.