• 대한골대사학회지
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• 제25권4호
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• pp.243-249
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• 2018

Background: The aim of this study was to determine the accuracy and error range of hand grip strength measurement using various methods. Methods: Methods used for measurement of hand grip strength in 34 epidemiologic studies on sarcopenia were analyzed. Maximum grip strength was measured in a sitting position with the elbow flexed at 90 degrees, the shoulder in 0 degrees flexion, and the wrist in neutral position (0 degrees). Maximum grip strength in standing position was measured with the shoulder in 180 degrees flexion, the elbow fully extended, and the wrist in neutral position (0 degrees). Three measurements were taken on each side at 30 sec intervals. The uncertainty of measurement was calculated. Results: The combined uncertainty in sitting position on the right and left sides was 1.14% and 0.38%, respectively, and the combined uncertainty in standing position on the right and left sides was 0.35 and 1.20, respectively. The expanded uncertainty in sitting position on the right and left sides was 2.28 and 0.79, respectively, and the expanded uncertainty in standing position on the right and left sides was 0.71 and 2.41, respectively (k=2). Conclusions: Uncertainty of hand grip strength measurement was identified in this study, and a significant difference was observed between measurement. For more precise diagnosis of sarcopenia, dynamometers need to be corrected to overcome uncertainty.

• Structural Engineering and Mechanics
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• 제76권4호
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• pp.529-540
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• 2020

Concurrent topology optimization of macrostructure and microstructure has attracted significant interest due to its high structural performance. However, most of the existing works are carried out under deterministic conditions, the obtained design may be vulnerable or even cause catastrophic failure when the load position exists uncertainty. Therefore, it is necessary to take load position uncertainty into consideration in structural design. This paper presents a computational method for robust concurrent topology optimization with consideration of load position uncertainty. The weighted sum of the mean and standard deviation of the structural compliance is defined as the objective function with constraints are imposed to both macro- and micro-scale structure volume fractions. The Bivariate Dimension Reduction method and Gauss-type quadrature (BDRGQ) are used to quantify and propagate load uncertainty to calculate the objective function. The effective properties of microstructure are evaluated by the numerical homogenization method. To release the computation burden, the decoupled sensitivity analysis method is proposed for microscale design variables. The bi-directional evolutionary structural optimization (BESO) method is used to obtain the black-and-white designs. Several 2D and 3D examples are presented to validate the effectiveness of the proposed robust concurrent topology optimization method.

• 한국정보과학회논문지:데이타베이스
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• 제33권3호
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• pp.261-270
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• 2006

위치기반서비스에서 이동체의 위치 데이타 수집 비용을 줄이기 위하여 위치 데이타를 주기적으로 수집한다. 주기적으로 수집된 위치 데이타는 보고 주기 사이의 위치 변화를 반영하지 못하기 때문에 시간에 대한 선형 함수를 이용하여 예측된 위치 데이타와 오차가 발생한다. 따라서 오차를 포함한 불확실한 미래위치데이타로 인하여 TPR 트리에서 현재위치질의의 정확도가 떨어지는 문제점이 발생한다. 이 논문에서는 불확실한 위치 데이타에 대한 현재질의를 처리하기 위하여 선형 함수에 의해 예측된 위치 데이타에 오차분을 반영한 불확실성 영역을 정의하고 불확실성 영역을 설정하기 위하여 최근 예측 오차 가중치 기법과 칼만 필터 기법을 제시한다. 또한 TPR 트리를 기반으로 불확실성 영역을 반영한 질의 처리기를 구현하고 성능 비교 평가를 수행한다. 성능 평가 결과에 따르면 기존의 선형함수 기반 질의처리 기법보다 불확실성 영역 기반 질의처리 기법이 최소 약 15% 이상의 정확도가 향상되는 장점을 가진다.

• 제어로봇시스템학회논문지
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• 제3권3호
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• pp.252-258
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• 1997

This paper presents neural networks for hybrid position/force control which is a type of position and force control for robot manipulators. The performance of conventional hybrid position/force control is excellent in the case of the exactly-known dynamic model of the robot, but degrades seriously as the uncertainty of the model increases. Hence, the neural network control scheme is presented here to overcome such shortcoming. The introduced neural term is designed to learn the uncertainty of the robot, and to control the robot through uncertainty compensation. Further more, the learning rule of the neural network is derived and is shown to be effective in the sense that it requires neither desired output of the network nor error back propagation through the plant. The proposed scheme is verified through the simulation of hybrid position/force control of a 6-dof robot manipulator.

• Journal of Positioning, Navigation, and Timing
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• 제12권1호
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• pp.51-58
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• 2023

Geofencing supports unmanned aerial vehicle (UAV) operation by defining stay-in and stay-out regions. National Aeronautics and Space Administration (NASA) has developed a prototype of the geofencing function, SAFEGUARD, which prevents stayout region violation by utilizing position estimates. Thus, SAFEGUARD depends on navigation system performance, and the safety risk associated with the navigation system uncertainty should be considered. This study presents a methodology to compute the safety risk assessment-based along-track position error bound under nominal and Global Navigation Satellite Systems (GNSS) failure conditions. A Kalman filter system using pseudorange measurements as well as pseudorange rate measurements is considered for determining the position uncertainty induced by velocity uncertainty. The worst case pseudorange and pseudorange rate fault-based position error bound under the GNSS failure condition are derived by applying a Receiver Autonomous Integrity Monitor (RAIM). Position error bound simulations are also conducted for different GNSS fault hypotheses and constellation conditions with a GNSS/INS integrated navigation system. The results show that the proposed along-track position error bounds depend on satellite geometries caused by UAV attitude change and are reduced to about 40% of those of the single constellation case when using the dual constellation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1589-1592
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• 1997

Among the prerequisite abilities (perception of environment, path planning and position estimation) of an autonomous mobile robot, position estimation has been seldom studied by mobile robot researchers. In most cases, conventional positioin estimation has been performed by placing landmarks or giving the entrire environmental information in advance. Unlikely to the conventional ones, the study addresses a new method that the robot itself can select distinctive features in the environment and save them as landmarks without any a priori knowledge, which can maximize the autonomous behavior of the robot. First, an orjentaion probaility model is applied to construct a lcoal map of robot's surrounding. The feature of the object in the map is then extracted and the map is saved as landmark. Also, presented is the position estimation method that utilizes the correspondence between landmarks and current local map. In dong this, the uncertainty of the robot's current positioin is estimated in order to select the corresponding landmark stored in the previous steps. The usefulness of all these approaches are illustrated with the results porduced by a real robot equipped with ultrasonic sensors.

• 한국정밀공학회지
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• 제23권7호
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• pp.51-58
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• 2006

This study analyzes the uncertainty of the compensation method of a sensing error of three-DOF measuring system. This compensation method utilizes a reference coordinate system using a three point by moving a position of an endpoint of a three-DOF manipulator. The coordinate transformation between the three-DOF manipulator and the measuring system is identified by the reference coordinate system. According to the concept of this compensation method, each positioning error at any position of the end-point of the manipulator is derived. Uncertainty analyses of the compensation values on the basis of sensitivity analysis and Monte Carlo simulation are used to investigate a feasibility and effectiveness of the compensation method.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2005년도 춘계학술대회 논문집
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• pp.103-108
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• 2005

In this paper, a controller design procedure for an electro-hydraulic positioning systems have developed using $H_\infty$ control theory. The generalized models and weighting functions for a multiplicative uncertainty modelling error is presented along with $H_\infty$ controller designs in order to investigate the robust stability and performance. The multiplicative uncertainty case is specifically suited for the design of an electro-hydraulic positioning control systems using $H_\infty$ control.

• 한국자기공명학회논문지
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• 제24권2호
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• pp.53-58
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• 2020

Free radicals including reactive oxygen species (ROS) are important chemicals in the research area of biology, pharmaceutical, medical, and environmental science as well as human health risk assessment as they are highly involved in diverse metabolism and toxicity mechanisms through chemical reactions with various components of living bodies. Electron spin resonance (ESR) spectroscopy is a powerful tool for detecting and quantifying those radicals in biological environments. In this work we observed the ESR signal of 2,2,6,6-Tetra-methyl piperidine 1-oxyl (TEMPO) in aqueous solution at various concentrations to estimate the uncertainty factors arising from the experimental conditions and signal treatment methods. As the sample position highly influences the signal intensity, dual ESR tube geometry (consists of a detachable sample tube and a position fixed external tube) was adopted. This type of measurement geometry allowed to get the relative uncertainty of signal intensity lower than 1% when triple measurements are averaged. Linear dependence of signal intensity on the TEMPO concentration, which is required for the quantification of unknown sample, could be obtained over a concentration range of ~10³ by optimizing the signal treatment method depending on the concentration range.

• Journal of Electrical Engineering and Technology
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• 제12권3호
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• pp.1166-1176
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• 2017

Estimation errors of the rotor speed and position in sensorless control systems of Permanent Magnet Synchronous Motors (PMSM) will lead to low efficiency and dynamic-performance degradation. In this paper, a parallel-type extended nonlinear observer incorporating the nominal parameters is constructed in the stator-fixed reference frame, with rotor position, speed, and the load torque simultaneously estimated. The stability of the extended nonlinear observer is analyzed using the indirect Lyapunov's method, and observer gains are selected according to the transfer functions of the speed and position estimators. Taking into account the parameter inaccuracies issue, explicit estimation error equations are derived based on the error dynamics of the closed-loop sensorless control system. An equivalent flux error is defined to represent the back Electromotive Force (EMF) error caused by the inaccurate motor parameters, and a compensation strategy is designed to suppress the estimation errors. The effectiveness of the proposed method has been validated through simulation and experimental results.