• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1864-1866
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• 1991

We present a parameter estimator which operates in the domain of iteration sequence. The scheme can be applied to identify unknown algebraic system whose uncertainty is parametric.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.152-155
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• 1991

A solution to the problem of robot manipulator tracking of a smoothly moving object is given. It is shown that fuzzy prediction rule, fuzzy control can compensate the adverse effects of noise, time delay, unknown object trajectory, and robot modeling uncertainty. Simulations show that the fuzzy logic control results in acceptable precision,

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.325-325
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• 2000

This paper proposes a modified adaptive sliding mode control which improve the performance by making the system follow the nominal trajectories controlled by nominal controller. This method is used for the system with unknown parameter uncertainty and bounded uncertainties.

• 제어로봇시스템학회논문지
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• 제8권12호
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• pp.1023-1030
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• 2002

Since the dynamics of autonomous underwater vehicles (AUVs) are highly nonlinear and their hydrodynamic coefficients vary with different vehicle's operating conditions, high performance control systems of AUVs are needed to have the capacities of teaming and adapting to the variations of the vehicle's dynamics. In this paper, a linearly parameterized neural network (LPNN) is used to approximate the uncertainties of the vehicle dynamics, where the basis function vector of the network is constructed according to the vehicle's physical properties. The network's reconstruction errors and the disturbances in the vehicle dynamics are assumed be bounded although the bound may be unknown. To attenuate this unknown bounded uncertainty, a certain estimation scheme for this unknown bound is introduced combined with a sliding mode scheme. The proposed controller is proven to guarantee that all signals in the closed-loop system are uniformly ultimately bounded (UUB). Numerical simulation studies are performed to illustrate the effectiveness of the proposed control scheme.

• 제어로봇시스템학회논문지
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• 제14권10호
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• pp.1014-1021
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• 2008

This paper proposes an intelligent sliding mode control method for robotic systems with the unknown bound of model uncertainties. In our control structure, the unknown bound of model uncertainties is used as the gain of the sliding controller. Then, we employ the function approximation technique to estimate the unknown nonlinear function including the width of boundary layer and the uncertainty bound of robotic systems. The adaptation laws for all parameters of the self-recurrent wavelet neural network and those for the reconstruction error compensator are derived from the Lyapunov stability theorem, which are used for an on-line control of robotic systems with model uncertainties and external disturbances. Accordingly, the proposed method can not only overcome the chattering phenomenon in the control effort but also have the robustness regardless of model uncertainties and external disturbances. Finally, simulation results for the five-link biped robot are included to illustrate the effectiveness of the proposed method.

• 한국전문물리치료학회지
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• 제23권2호
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• pp.93-99
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• 2016

Background: Parametric statistical procedures are typically conducted under the condition in which a sample distribution is statistically identical with its population. In reality, investigators use inferential statistics to estimate parameters based on the sample drawn because population distributions are unknown. The uncertainty of limited data from the sample such as lack of sample size may be a challenge in most rehabilitation studies. Objects: The purpose of this study is to review the bootstrapping method to overcome shortcomings of limited sample size in rehabilitation studies. Methods: Articles were reviewed. Results: Bootstrapping method is a statistical procedure that permits the iterative re-sampling with replacement from a sample when the population distribution is unknown. This statistical procedure is to enhance the representativeness of the population being studied and to determine estimates of the parameters when sample size are too limited to generalize the study outcome to target population. The bootstrapping method would overcome limitations such as type II error resulting from small sample sizes. An application on a typical data of a study represented how to deal with challenges of estimating a parameter from small sample size and enhance the uncertainty with optimal confidence intervals and levels. Conclusion: Bootstrapping method may be an effective statistical procedure reducing the standard error of population parameters under the condition requiring both acceptable confidence intervals and confidence level (i.e., p=.05).

• 한국공작기계학회논문집
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• 제18권1호
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• pp.90-102
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• 2009

In this paper, a tracking control problem for a mechanical servo system with nonlinear dynamic friction is treated. The nonlinear friction model contains directly immeasurable friction state and the uncertainty caused by incomplete modeling and variations of its parameter. In order to provide the efficient solution to these control problems, we propose a hybrid control scheme, which consists of a robust friction state observer, a RFNN estimator and an approximation error estimator with sliding mode control. A sliding mode controller and a robust friction state observer is firstly designed to estimate the unknown infernal state of the LuGre friction model. Next, a RFNN estimator is introduced to approximate the unknown lumped friction uncertainty. Finally, an adaptive approximation error estimator is designed to compensate the approximation error of the RFNN estimator. Some simulations and experiments on the mechanical servo system composed of ball-screw and DC servo motor are presented. Results demonstrate the remarkable performance of the proposed control scheme.

• 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.

• 생물정신의학
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• 제21권3호
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• pp.87-92
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• 2014

Objectives Risk taking has been implicated in the development of various psychiatric disorders. Previous studies have indicated that risk taking behavior is associated with high levels of impulsiveness. Risk taking entail uncertain situation that outcome probability is unknown. This study tested impulsivity, intolerance of uncertainty and risk taking behavior. Methods A total of 73 participants completed a test battery comprised of the UPPS-P scale as a psychometric measurement of five dimensions of impulsivity, Intolerance of Uncertainty Scale, and Balloon Analog Risk Task (BART) as a behavioral measure of risk taking. The Pearson correlation analysis was used. Results The sensation seeking factor was positively correlated with BART measure (r = 0.27, p = 0.02). Specifically, the relationship between sensation seeking and BART was significant in females. Conclusions Among the five factors of UPPS-P, only the sensation seeking factor predicts risk taking propensity.

• Smart Structures and Systems
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• 제22권4호
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• pp.399-411
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• 2018

The difficulty in modeling complex nonlinear structures lies in the presence of significant sources of uncertainties mainly attributed to sudden changes in the structure's behavior caused by regular aging factors or extreme events. Quantifying these uncertainties and accurately representing them within the complex mathematical framework of Structural Health Monitoring (SHM) are significantly essential for system identification and damage detection purposes. This study highlights the importance of uncertainty quantification in SHM frameworks, and presents a comparative analysis between intrusive and non-intrusive techniques in quantifying uncertainties for SHM purposes through two different variations of the Kalman Filter (KF) method, the Ensemble Kalman filter (EnKF) and the Polynomial Chaos Kalman Filter (PCKF). The comparative analysis is based on a numerical example that consists of a four degrees-of-freedom (DOF) system, comprising Bouc-Wen hysteretic behavior and subjected to El-Centro earthquake excitation. The comparison is based on the ability of each technique to quantify the different sources of uncertainty for SHM purposes and to accurately approximate the system state and parameters when compared to the true state with the least computational burden. While the results show that both filters are able to locate the damage in space and time and to accurately estimate the system responses and unknown parameters, the computational cost of PCKF is shown to be less than that of EnKF for a similar level of numerical accuracy.