• 제어로봇시스템학회:학술대회논문집
• /
• 1989.10a
• /
• pp.22-27
• /
• 1989

In this paper influences of disturbances and Modeling errors are qualitatively for the linear approximation model of turret servo system, and then LQG/LTR Control theory is applied to linear approximation model in order to design a controller which satisfies robustneas/stability for the modeling errors. Finally the performance and robustness of designed controller for the given plant are verified through the simulation.

• Smart Structures and Systems
• /
• v.15 no.3
• /
• pp.717-733
• /
• 2015

Modal parameters of a structure are commonly used quantities for system identification and damage detection. With a limited number of studies on the statistics assessment of modal parameters, this paper presents procedures to properly account for the uncertainties present in the process of extracting modal parameters. Particularly, this paper focuses on how to deal with the measurement error in an ambient vibration test and the modeling error resulting from a modal parameter extraction process. A bootstrap approach is adopted, when an ensemble of a limited number of noised time-history response recordings is available. To estimate the modeling error associated with the extraction process, a model prediction expansion approach is adopted where the modeling error is considered as an "adjustment" to the prediction obtained from the extraction process. The proposed procedures can be further incorporated into the probabilistic analysis of applications where the modal parameters are used. This study considers the effects of the measurement and modeling errors and can provide guidance in allocating resources to improve the estimation accuracy of the modal data. As an illustration, the proposed procedures are applied to extract the modal data of a damaged beam, and the extracted modal data are used to detect potential damage locations using a damage detection method. It is shown that the variability in the modal parameters can be considered to be quite low due to the measurement and modeling errors; however, this low variability has a significant impact on the damage detection results for the studied beam.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.57 no.5
• /
• pp.839-844
• /
• 2008

A novel state of health estimation method for hybrid electric vehicle lithium battery using sliding mode observer has been presented. A simple R-C circuit method has been used for the lithium battery modeling for the reduced calculation time and system resources due to the simple matrix operations. The modeling errors of simple model are compensated by the sliding mode observer. The design methodology for state of health estimation using dual sliding mode observer has been presented in step by step. The structure of the proposed system is simple and easy to implement, but it shows robust control property against modeling errors and temperature variations. The convergence of proposed observer system has been proved by the Lyapunov inequality equation and the performance of system has been verified by the sequence of urban dynamometer driving schedule test. The test results show the proposed observer system has superior tracking performance with reduced calculation time under the real driving environments.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.24 no.10 s.181
• /
• pp.2589-2596
• /
• 2000

As current manufacturing processes require high spindle speed and precise machining, increasing accuracy by reducing volumetric errors of the machine itself, particularly thermal errors, is very important. Thermal errors can be estimated by many empirical models, for example, an FEM model, a neural network model, a linear regression model, an engineering judgment model, etc. This paper discusses to make a modeling of thermal errors efficiently through backward elimination and fuzzy logic strategy. The model of a thermal error using fuzzy logic strategy overcomes limitation of accuracy in the linear regression model or the engineering judgment model. It shows that the fuzzy model has more better performance than linear regression model, though it has less number of thermal variables than the other. The fuzzy model does not need to have complex procedure such like multi-regression and to know the characteristics of the plant, and the parameters of the model can be mathematically calculated. Also, the fuzzy model can be applied to any machine, but it delivers greater accuracy and robustness.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1999.05a
• /
• pp.75-80
• /
• 1999

As current manufacturing processes require high spindle speed and precise machining, increasing accuracy by reducing volumetric errors of the machine itself, particularly thermal errors, is very important. Thermal errors can be estimated by many empirical models, for example, an FEM model, a neural network model, a linear regression model, an engineering judgment model etc. This paper discusses to make a modeling of thermal errors efficiently through backward elimination and fuzzy logic strategy. The model of a thermal error using fuzzy logic strategy overcome limitation of accuracy in the linear regression model or the engineering judgment model. And this model is compared with the engineering judgment model. It is not necessary complex process such like multi-regression analysis of the engineering judgment model. A fuzzy model does not need to know the characteristics of the plant, and the parameters of the model can be mathematically calculated. Like a regression model, this model can be applied to any machine, but it delivers greater accuracy and robustness.

• Journal of Korean Society for Geospatial Information Science
• /
• v.13 no.2 s.32
• /
• pp.79-84
• /
• 2005

Recent researches about the accuracy assessment of the satellite sensor modeling usually focused on the quantitative analysis of errors. Quantitative error analysis contains its limitation that the distribution property of error can not be analyzed. The numerical evaluation of result of the satellite sensor modeling drop its confidence because of the absence of the distribution property of error. This study can be presented the distribution property of error to calculate RMSE and direction-coefficient of error. Moreover, Direction-coefficient which is closed to 1 s contains systematic errors. On the contrary, direction-coefficient which is closed to the zero contains random errors. To analyse the direction of errors, we will indicate that a formula is reduced the error.

• Korean Journal of Computational Design and Engineering
• /
• v.6 no.1
• /
• pp.40-47
• /
• 2001

In reverse engineering, existing products are digitized fur the computer modeling. Using the digitized data, surfaces are modeled for new products. However, in the digitizing process measuring errors or deviations can be happened often in practice. Thus, it is important to adjust such errors or deviations during the computer modeling. To adjust the errors, fairing of the modeled surfaces is performed. In this paper, we present a surface fairing algorithm based on various fairness metrics. Fairness metrics can be discrete. We adopt discrete metrics for fairing given 3D point set. The fairness metrics include discrete principal curvatures. In this paper, automatic fairing process is proposed for fairing given 3D point sets for surfaces. The process uses various fairness criteria so that it is adequate to adopt designers'intents.

• Proceedings of KOSOMES biannual meeting
• /
• 2004.05b
• /
• pp.7-11
• /
• 2004

Maritime safety and marine environmental protection are the most important topic in marine society. But, so many marine accidents rave been occurred with the development of marine transportation industry. On the other side, ship is being operated under a highly dynamic environment and many factors are related with ship's collision Nowadays, the increasing tendency to the human errors of ship's collision is remarkable, and the investigation of the human errors has been heavily concentrated. This study analysed on the human errors of ship's collision related to the negligence of lookout and classified basic error type using GEMS(Generic Error Modeling System) dynamic model.

• Korean Journal of Computational Design and Engineering
• /
• v.4 no.2
• /
• pp.127-138
• /
• 1999

For reverse engineering, curves and surfaces are modeled for new products by interpolating the digitized data points. But there are many measuring or deviation errors. Therefore, it is important to handle errors during the curve or surface modeling. If the errors are ignored, designer could get undesirable results. For this reason, fairing procedure with the aesthetics criteria is necessary in computer modeling. This paper presents methods of 3D NURBS curve fairing. The techniques are based on automatic repositioning of the digitized dat points or the NURBS curve control points by a constrained nonlinear optimization algorithm. The objective function is derived variously by derived curved. Constraints are distance measures between the original and the modified digitized data points. Changes I curve shape are analyzed by illustrations of curve shapes, and continuous plotting of curvature and torsion.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2003.04a
• /
• pp.382-387
• /
• 2003

In this paper, a neural networks-based damage detection method using the modal properties is presented, which can effectively reduce the effect of the modeling errors in the baseline finite element model from which the training patterns for the networks are to be generated. The differences or the ratios of the mode shape components between before and after damage are used as the input to the neural networks in this method, since they are found to be less sensitive to the modeling errors than the mode shapes themselves. Results of laboratory test on a simply supported bridge model and field test on a bridge with multiple girders confirm the applicability of the present method.