• 대한토목학회논문집
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• 제38권2호
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• pp.349-356
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• 2018

본 논문은 국내에서 연구가 미진한 적재설비의 지진 취약도 평가에 적용할 수 있는 FE 해석 기반의 연결부 모델을 개발하는데 목적이 있다. 이러한 목표를 달성하기 위하여, 적재설비 거동을 파악하기 위한 진동대 실험과 Modal Test, 그리고 구성 부재를 대상으로 한 다양한 부재실험(8가지 Push-over Test)을 진행하였다. 실험결과를 바탕으로 지진취약도 평가에 적용하기 위한 적재설비의 연결부 모델을 개발하기 위하여, NX-Nastran 프로그램을 활용하여 연결부의 상세 모델링을 진행하였다. 특히, 단순 걸쇠 방식으로 연결되는 기둥 부재와 보 부재의 연결을 모사하기 위하여 면대면 표면접촉 요소와 스프링 요소를 적용하였으며, 스프링 요소의 모델은 ARX (Auto Regressive eXogenous) 기반의 수학적 모델을 개발하여 적용하였다. FE 모델 기반의 simulation 결과는 부재 실험 결과와 비교하였을 때, 상호 오차율 8% 미만의 우수한 신뢰도를 보여주었다. 결과적으로 연구에서 개발한 FE해석 기반의 연결부 모델은 적재설비의 지진 취약도 평가를 위한 해석 모델에 활용될 수 있음을 확인하였다.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2004년도 가을 학술발표회 논문집
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• pp.371-376
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• 2004

This study presents a way to generate and manage engineering information by applying steel bridge information model with 3D shape to existing application program. ACIS solid modeling kernel is used to visualize 3D geometric shape of steel bridge on the AutoCAD program. The shape information of 3D solid model can be connected to structural design information of steel bridge by an application module based on information model. The application module for manipulating steel bridge information can be easily developed by ObjectARX programming library supporting functional expansion of AutoCAD program. End-users can use the application module without any additional environmental setup on the AutoCAD. Thus this study facilitates information management of steel bridge by using ACIS solid modeler and ISO/STEP methodology.

• Journal of Mechanical Science and Technology
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• 제15권7호
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• pp.847-858
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• 2001

This paper considers the control model identification and H(sub)$\infty$ controller design for a tandem cold mill (TCM). In order to improve the performance of the existing automatic gauge control (AGC) system based on the Taylor linearized model of the TCM, a new mathematical model that can complement the Taylor linearized model is constructed by using the N4SID algorithm based on subspace method and the least squares algorithm based on ARX model. It is shown that the identified model had dynamic characteristics of the TCM than the existing Taylor linearized model. The H(sub)$\infty$ controller is designed to have robust stability to the system parameters variation, disturbance attenuation and robust tracking capability to the set-up value of strip thickness. The H(sub)$\infty$ servo problem is formulated and it is solved by using LMI (linear matrix inequality) techniques. Simulation results demonstrate the usefulness and applicability of the proposed H(sub)$\infty$ controller.

• International Journal of Aeronautical and Space Sciences
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• 제13권4호
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• pp.428-434
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• 2012

Missiles suffer from flight instability problems at high angles of attack, since vortex flow over a fuselage cause lateral force to the body. To overcome this problem at a high angle of attack, the development of a real time vortex controller is needed. In this paper, Proper Orthogonal Decomposition (POD) and feedback controllers are developed for real time vortex control. The POD method is one of the most well known techniques for modeling low order models that represent the original full-order model. An adaptive control algorithm is used for real time control.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.20-25
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• 1993

The control of the motion of a mobile robot is studied. The driving and steering motor assembly is located in the front of the mobile robot. The position of the mobile robot is determined by the steering angle and driving distance. For the controller design, a time-series multivariate model of the autogressive exogenous (ARX) type is used to describe the input-output relation. The discounted least square method is used to estimate parameters of the time-series model. A self-tuning controller is so designed that the position of the center of the mobile robot track the given trajectory. Simulation result controlled by a self-tuning controller is presented to illustrate the approach.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.161.1-161
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• 2001

Tire roller is one of the most useful machines for the road constructions site. In this research, we are trying to develop tire roller which is operated by hydraulic transmission system instead of mechanical one. Now, we are trying to design the controller of tire roller in order to improve performance. Our present system model is somewhat different from the actual experimental results. Therefore we would like to develop new accurate modeling through ARX model by system identification method with random inputs. In this paper, we applied it to the steering system only. Later we will apply it to the traction system and expand to the whole tire roller system.

• Smart Structures and Systems
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• 제11권6호
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• pp.569-587
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• 2013

This paper evaluates the closed loop performance of the reaching law based discrete sliding mode controller with multisensor data fusion (MSDF) in real time, by controlling the first two vibrating modes of a piezo actuated structure. The vibration is measured using two homogeneous piezo sensors. The states estimated from sensors output are fused. Four fusion algorithms are considered, whose output is used to control the structural vibration. The controller is designed using a model identified through linear Recursive Least Square (RLS) method, based on ARX model. Improved vibration suppression is achieved with fused data as compared to single sensor. The experimental evaluation of the closed loop performance of sliding mode controller with data fusion applied to piezo actuated structure is the contribution in this work.

• 대한전기학회논문지:전력기술부문A
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• 제48권4호
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• pp.410-418
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• 1999

This paper describes the use of residual and parameter identification methods for fault detection in an air handling unit. Faults can be detected by comparing expected condition with the measured faulty data using residuals. Faults can also be detected by examining unmeasurable parameter changes in a model of a controlled system using a system identification technique. In this study, AutoRegressive Moving Average with seXtrnal input(ARMAX) and AutoRegressive with eXternal input(ARX) models with both single-input/single-input and multi-input/single-input structures are examined. Model parameters are determined using the Kalman filter recursive identification method. Regression equations are calculated from normal experimental data and are used to compute expected operating variables. These approaches are tested using experimental data from a laboratory's variable-air-volume air-handling-unit.

• Journal of Information Processing Systems
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• 제14권4호
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• pp.904-915
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• 2018

We demonstrate how social media content can be used to predict the unemployment rate, a real-world indicator. We present a novel method for predicting the unemployment rate using social media analysis based on natural language processing and statistical modeling. The system collects social media contents including news articles, blogs, and tweets written in Korean, and then extracts data for modeling using part-of-speech tagging and sentiment analysis techniques. The autoregressive integrated moving average with exogenous variables (ARIMAX) and autoregressive with exogenous variables (ARX) models for unemployment rate prediction are fit using the analyzed data. The proposed method quantifies the social moods expressed in social media contents, whereas the existing methods simply present social tendencies. Our model derived a 27.9% improvement in error reduction compared to a Google Index-based model in the mean absolute percentage error metric.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2016년도 추계학술대회 논문집
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• pp.75-76
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• 2016

The relationship of widely used Open circuit Voltage (OCV) versus State of Charge (SOC) is critical for any reliable SOC estimation technique. However, the hysteresis existing in all type of battery which has been come to the market leads this relationship to a complicated one, especially in Lithium Iron Phosphate (LiFePO4) battery. An accurate model for hysteresis phenomenon is essential for a reliable SOC identification. This paper aims to investigate and propose a method for hysteresis modeling. The SOC estimation is done by using Extended Kalman Filter (EKF), the parameter of the battery is modeled by Auto Regressive Exogenous (ARX) and estimated by using Recursive Least Square (RLS) filter to tract each element of the parameter of the model.