• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.29 no.1 s.232
• /
• pp.59-66
• /
• 2005

In this paper, a robust stationary Kalman filter is designed by minimizing selected performance indices so that it is less sensitive to uncertainties. The uncertainties include not only stochastic factors such as process noise and measurement noise, but also deterministic factors such as unknown initial estimation error, modeling error and sensing bias. To reduce the effect on the uncertainties, three performance indices that should be minimized are selected based on the quantitative error analysis to both the deterministic and the stochastic uncertainties. The selected indices are the size of the observer gain, the condition number of the observer matrix, and the estimation error variance. The observer gain is obtained by optimally solving the multi-objectives optimization problem that minimizes the indices. The robustness of the proposed filter is demonstrated through the comparison with the standard Kalman filter.

• The Korean Journal of Applied Statistics
• /
• v.29 no.4
• /
• pp.595-611
• /
• 2016

We use nonlinear regression models (such as the Hill Model) when we analyze data in toxicology and/or pharmacology. In nonlinear regression models an estimator of parameters and estimation of measurement about uncertainty of the estimator are influenced by the variance structure of the error. Thus, estimation methods should be different depending on whether the data are homoscedastic or heteroscedastic. However, we do not know the variance structure of the error until we actually analyze the data. Therefore, developing estimation methods robust to the variance structure of the error is an important problem. In this paper we propose a method to estimate parameters in nonlinear regression models based on a preliminary test. We define an estimator which uses either the ordinary least square estimation method or the iterative weighted least square estimation method according to the results of a simple preliminary test for the equality of the error variance. The performance of the proposed estimator is compared to those of existing estimators by simulation studies. We also compare estimation methods using real data obtained from the National Toxicology program of the United States.

• 유체기계공업학회:학술대회논문집
• /
• 2003.12a
• /
• pp.143-148
• /
• 2003

This study was experimentally performed in order to estimate the errors due to the leakage of transmitter gaugelines in the orifice flow meter for natural gas. It would be a serious problem in safety if a large quantity of leak was occurred at the tubes or fittings like valve. But in most cases the safety problems might be rarely happened because the gas leak detectors could be operated in advance and the various kinds of inspection would be also fulfilled periodically. If the leakage was occurred continuously with an undetectable amount at the gaugelines for measuring the pressure or the differential pressure(DP), the amount of leakage might be an error or an unaccounted flow(UAE). In addition if the measuring value of pressure or DP were affected by the leakage, it might also be a measurement error. The experiments were performed to estimate the amount of leakage and to check the DP changes if it exited. First, through the measurement of the air pressure changes in the airtight container connected to a transmitter with gaugelines as the time passed, the amount of leakage causing from the fittings of gaugelines was roughly estimated. As changing the leak position of the gaugeline, the leak was intentionally made to break out. The variance of DP was checked as controlling the extent of leakage and compared to no leak conditions. Consequently, under the normal maintenance conditions, the result represented that the amount of leakage causing from the gaugelines was insignificant and also the DP changes on leakage conditions were too small to cause the errors of measurements.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.9 no.6
• /
• pp.33-42
• /
• 2010

Travel speed is an important parameter in measurement of road traffic. UTIS(Urban Traffic Information System) was developed as a type of section detector. However, UTIS incur errors caused by irregular vehicle trajectories, wireless communication range and so on. This paper suggests a new model that use an error-filtering algorithm to improve the accuracy of travel speed measurements. In the field test, the variance of the percent errors measured by the new model was reduced. Therefore, it can be concluded that the proposed model significantly improves travel speed measuring accuracy.

• Journal of Environmental Science International
• /
• v.24 no.4
• /
• pp.393-401
• /
• 2015

Rainfall-runoff model of Jeju Oedo Stream was used to compute the optimal unit hydrograph by HEC-HMS model that reflecting on watershed characteristics. Each rainfall event was comparatively analyzed with the actual flow measurement using Clark, Snyder and SCS synthetic methods for derived unit hydrograph. Subsequently, the null hypothesis was established as p-value for peak flow and peak time of each unit hydrograph by one-way ANOVA(Analysis of variance) was larger than significance level of 0.05. There was no significant difference in peak flow and peak time between different methods of unit hydrograph. As a result of comparing error rate with actual flow measurement data, Clark synthetic unit graph best reflected in Oedo Stream as compared to other methods, and error rate of Clark unit hydrograph was 0.02~1.93% and error rate at peak time was 0~2.74%.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.06a
• /
• pp.1797-1802
• /
• 2005

In this study, we were developed an accuracy of the proposed two dimensional statical inclinometer what used a position sensitive detector(PSD) by an error analysis. The inclinometer consists of a laser source, a mass, an optic-fiber, and a PSD. The gravity direction on a base platform of the inclinometer is changed by an unknown inclination angle. And a laser spot is moved from the origin to another position of a PSD following a variation of an optical path by the gravity. These processes enable the inclinometer to estimate the inclination angle from distance information of the moving spot. A design methodology on the basis of a sensitivity analysis was applied to improve the measurement performance such as a full measuring range and a resolution. But it still has error factors, so we analyze the uncertainty of the inclinometer to evaluate the systematic errors from alignments, assembly error and so on. The experimental performance evaluation about the design objectives as a measuring range and a resolution was performed. And the validity and the feasibility of the design process were certified by an experimental process. Systematic errors eliminated to improve the accuracy of the inclinometer by the corrected measuring model from the calibration process between the inclination angle and the PSD position instead of the nominal measuring model. The ANOVA(analysis of variance) confirmed the effect of eliminating the systematic errors in the inclinometer. From these methodologies, the proposed inclinometer was able to measure with a high resolution(35.14sec) and a wide range(from $-15^{\circ}\;to\;15^{\circ}$

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10a
• /
• pp.153-156
• /
• 1996

A new filtering algorithm for radar tracking is developed based on the fact that correct evaluation of the measurement error covariance can be made possible by doing it with respect to the Cartesian state vector. The new filter may be viewed as a modification of the extended Kalman filter where the variance of the range measurement errors is evaluated in an adaptive manner. The structure of the proposed filter allows sequential measurement processing scheme to be incorporated into the scheme, and this makes the resulting algorithm favorable in both estimation accuracy and computational efficiency.

• Aerospace Engineering and Technology
• /
• v.9 no.1
• /
• pp.50-59
• /
• 2010

In this paper, the alignment and navigation results by INGU(Inertial Navigation and Guidance Unit) onboard software and by Inertial Explorer which is a post-processing software specialized for IMU(Inertial Measurement Unit) are compared for identification of inertial sensor error models and estimation of alignment and navigation errors for KSLV-I INGU. For verification of the IMU error estimated by Kalman Filter of Inertial Explorer, the covariance parameters of inertial sensor error model state are identified by using stochastic error model of inertial sensors estimated by Allan variance and the alignment and navigation test with static condition and the land navigation test with dynamic condition are carried out. The validity of inertial sensor model for KSLV-I INGU is verified by comparison the alignment and navigation results of INGU on-board software and Inertial Explorer.

• Journal of Institute of Control, Robotics and Systems
• /
• v.7 no.12
• /
• pp.1015-1023
• /
• 2001

error behaviour can be considered as a linear combination of low amplitude random noise and abrupt jumps. The reason of jump appearance can be explained by the semi-shading effects(buildings, trees), jamming, high dynamic of vehicle and so on. This study describes the stand-alone GPS error jump smoothing algorithm which is developed based on the scalar adaptive filter. The algorithm consists of the coarse jump smoothing and the fine jump smoothing. On the coarse smoothing step, GPS velocities or position differences are used as the measurement for the scalar adaptive filter. The purpose of adaptive filter is to smooth the jump errors. The coarse positions are detennined by the integration of smoothed velocities. On the fine smoothing step, the differences between GPS positions and the coarse positions are smoothed by another scalar adaptive filter. The reason of fine smoothing is based on the facts that smoothing accuracy depends on the variance ofusefuJ signa\. The coarse smoothing which deal with the difference of positions provides the rough error removing. So the coarse smoothed velocities can have much more low amplitude than the raw ones. The fine smoothing procedure provides high quality of filtering process. Simulation results show the efficiency of proposed scheme.

• The Journal of the Acoustical Society of Korea
• /
• v.19 no.4
• /
• pp.16-22
• /
• 2000

In order to predict the performance and the usefulness of the narrow-band underwater acoustic measurement system at design stage, whose error variance is not clearly described, in this study a boundary equation to estimate the measurement accuracy is proposed based on the confidency as SNR variation. The boundary is presented as a function of SNR and the number of samples. In this paper, the measurement performance for narrow-band signal is simulated by the proposed boundary equation and the results are reviewed in the biased noise condition and separately in the background noise rejected condition.