• International Journal of Advanced Culture Technology
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• v.11 no.2
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• pp.170-177
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• 2023

In quantum mechanics, uncertainty refers to the uncertainty of a measurement physical quantity, because some mechanical quantity can only be in its eigenstate under certain conditions, and the values shown are discrete.The exact value can only be obtained by measuring it in the eigenstate of this mechanical quantity.Uncertainty is like a double-edged sword, which has both advantages and disadvantages in art itself and in the process of artistic creation. In this study, it is divided into three main parts. First, the existence of uncertainties in contemporary art is sorted out in two broad parts, the definition of the uncertainties in art and the specific expression in contemporary art, respectively, with examples from four aspects of psychological impact, accidental presentation effect, expression form and connection with the viewer. The purpose is to understand how uncertainties are expressed in the process of artistic creation. Second, the role of the uncertainties in artistic creation is analyzed through examples, and then it is proposed that artists should use uncertainties to serve art with a scientific and rational attitude. Thirdly, the application of uncertainties in my creative practice and their influences on my painting creation. In summary, every artistic creator should take art seriously and sincerely. The relationship among the creative subject, society and life is an eternal and continuous interaction, and art is a carrier of reflection. For the problems brought by uncertainties in artistic creation, from choosing new certainty by thinking to the emergence of uncertainties, such a cycle is the process of art sublimating from life and being closely related to life.

• The Journal of Korea Robotics Society
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• v.5 no.1
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• pp.23-31
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• 2010

This paper suggests a multiple robot simulator which considers the uncertainties in robot motion and sensing. A mobile robot moves with errors due to some kinds of uncertainties from actuators, wheels, electrical components, environments. In addition, sensors attached to a mobile robot can't make accurate output information because of uncertainties of the sensor itself and environment. Uncertainties in robot motion and sensing leads researchers find difficulty in building mobile robot navigation algorithms. Generally, a robot algorithm without considering unexpected uncertainties fails to control its action in a real working environment and it leads to some troubles and damages. Thus, the authors propose a simulator model which includes robot motion and sensing uncertainties to help making robust algorithms. Sensor uncertainties are applied in range sensors which are widely used in mobile robot localization, obstacle detection, and map building. The paper shows performances of the proposed simulator by comparing it with a simulator without any uncertainty.

• Nuclear Engineering and Technology
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• v.35 no.1
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• pp.64-79
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• 2003

In the risk and reliability analysis of complex technological systems, the primary concern of formal uncertainty analysis is to understand why uncertainties arise, and to evaluate how they impact the results of the analysis. In recent times, many of the uncertainty analyses have focused on parameters of the risk and reliability analysis models, whose values are uncertain in an aleatory or an epistemic way. As the field of parametric uncertainty analysis matures, however, more attention is being paid to the explicit treatment of uncertainties that are addressed in the predictive model itself as well as the accuracy of the predictive model. The essential steps for evaluating impacts of these model uncertainties in the presence of parameter uncertainties are to determine rigorously various sources of uncertainties to be addressed in an underlying model itself and in turn model parameters, based on our state-of-knowledge and relevant evidence. Answering clearly the question of how to characterize and treat explicitly the forgoing different sources of uncertainty is particularly important for practical aspects such as risk and reliability optimization of systems as well as more transparent risk information and decision-making under various uncertainties. The main purpose of this paper is to provide practical guidance for quantitatively treating various model uncertainties that would often be encountered in the risk and reliability modeling process of complex technological systems.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.293-296
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• 1997

Robust stability conditions for discrete-time variable structure control is proposed. Conventionally the discrete-time variable structure control method with a variable structure uncertainty compensator approach requires a bounded changing rate of the uncertainties to ensure robust stability. However, when uncertainties vary as a function of state variables, which occur with parametric uncertainties, it is not reasonable to assume a bounded variation on the uncertainties. In this paper, uncertainties are assumed to consist of exogenous disturbances and parametric uncertainties. An uncertainty compensator is used to deal with the former, and a robust stability condition is derived using Small Gain Theorem for the latter.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.561-565
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• 2005

Sliding mode control (SMC) is an effective method of controlling systems with uncertainties which satisfy the so-called matching condition. However, how to effectively handle mismatched uncertainties of systems is still an ongoing research issue in SMC. Several methods have been proposed to design a stable sliding surface even if mismatched uncertainties exist in a system. Especially, it is presented that robustness and efficiency of SMC for linear systems with mismatched uncertainties can be improved by reducing mismatched uncertainties in the reduced-order system. The reduction method needs a new sliding surface with an additional component based on Lyapunov redesign technique. In this paper, a stable sliding surface which contains additional component to reduce the influence of mismatched uncertainties, is introduced. It is designed by using linear matrix inequalities that guarantees the stability of the system. A numerical example demonstrates the validity of the proposed scheme.

• ETRI Journal
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• v.38 no.5
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• pp.1008-1018
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• 2016

This paper presents a control scheme for the leader-following formation of multiple robots. The control scheme combines the sliding mode control (SMC) method with the nonlinear disturbance observer (NDOB) technique. The formation dynamics suffer from uncertainties because the individual robots are uncertain. Concerning such formation uncertainties, the leader-following formation dynamics are modeled. Assuming that the formation uncertainties have an unknown boundary, an NDOB-based observer was designed to estimate the formation uncertainties. A sliding surface containing the observer outputs has been defined. Regarding the sliding surface, an SMC-based controller was investigated to form uncertain robots. A sufficient condition in the sense of the Lyapunov theory was proven such that the formation system is asymptotically stable. Herein, some comparison results between the sole SMC method and the second-order SMC method are presented to demonstrate the effectiveness and feasibility of the control scheme for multiple robots in the presence of uncertainties.

• Nuclear Engineering and Technology
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• v.30 no.6
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• pp.617-627
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• 1998

A technically more direct Statistical Combination of Uncertainties (SCU) method, extended SCU (XSCU), was developed to statistically combine the uncertainties associated with the DNBR alarm setpoint and the DNBR trip setpoint of digital nuclear power plants. The Modified SCU (MSCU) method is currently used as the USNRC approved design method to perform the same function. In this study, the MSCU and XSCU methods were compared in terms of the total uncertainties, and the thermal margins to the DNBR alarm and trip setpoints. The MSCU method resulted in small total uncertainties due to large negative biases which are unphysical. The XSCU method gives virtually unbiased total uncertainties which are physically meaningful in order to represent the actual magnitude of the total uncertainties associated with the DNBR alarm and trip setpoints. But the thermal margins to the DNBR alarm and trip setpoints by the MSCU method agree with those by the XSCU method within allowable statistical Variations.

• Structural Engineering and Mechanics
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• v.16 no.3
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• pp.327-340
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• 2003

Variations in system parameters due to uncertainties of parameters may result in system performance deterioration and create system internal stability problems. Uncertainties in structural modeling of structures are often considered to ensure that the control system is robust with respect to response errors. So the uncertain concept plays an important role in the analysis and design of the engineering structures. In this paper, the active control of the intelligent structures with the uncertainties is studied and a new method for analyzing the robustness of systems with the uncertainties is presented. Firstly, the system with uncertain parameters is considered as the perturbation of the system with deterministic parameters. Secondly, the feedback control law is designed on the basis of deterministic system. Thirdly, perturbation analysis and robustness analysis of intelligent structures with uncertainties are discussed when the feedback control law is applied to the original system and perturbed system. Combining the convex model of uncertainties with the finite element method, the analysis theory of the robustness of intelligent structures with the uncertainties can be developed. The description and computation of the robustness of intelligent structures with uncertain parameters is obtained. Finally, a numerical example of the application of the present method is given to show the validity of the method.

• Journal of Advanced Marine Engineering and Technology
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• v.18 no.4
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• pp.102-111
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• 1994

This article deals with the problem of designing a robust algorithm for the motion control of robot manipulator whose nonlinear dynamics contain various uncertainties. To ensure high performance of control system, a model-based feedforward compensation with continuous robust control has been developed. The control structure based on the deterministic approach consists of two parts : the nominal control law is first introduced to stabilize the system without uncertainties, then a robust nonlinear control law is adopted to compensate for both the resulting errors(or structured uncertainties) and unstructured uncertainties. The uncertainties assumed in this study are bounded by polynomials in the Euclidean norms of system states with known bounding coefficients. The presented control scheme is relatively simple as well as computationally efficient. With a feasible class of desired trajectories, the proposed control law provides sufficient criteria which guarantee that all possible responses of the closed-loop system are uniformly ultimately bounded in the presence of uncertainties. Therefore, the control algorithm proposed is shown to be robust with respect to the involved uncertainties.

• Nuclear Engineering and Technology
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• v.53 no.9
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• pp.2816-2829
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• 2021

Decay heat residuals of spent nuclear fuel (SNF), i.e., the differences between calculations and measurements, were obtained previously for various spent fuel assemblies (SFA) using the Polaris module of the SCALE code system. In this paper, we compare decay heat residuals to their uncertainties, focusing on four PWRs and four BWRs. Uncertainties in nuclear data and model inputs are propagated stochastically through calculations using the SCALE/Sampler super-sequence. Total uncertainties could not explain the residuals of two SFAs measured at GE-Morris. The combined z-scores for all SFAs measured at the Clab facility could explain the resulting deviations. Nuclear-data-related uncertainties contribute more in the high burnup SFAs. Design and operational uncertainties tend to contribute more to the total uncertainties. Assembly burnup is a relevant variable as it correlates significantly with the SNF decay heat. Additionally, burnup uncertainty is a major contributor to decay heat uncertainty, and assumptions relating to these uncertainties are crucial. Propagation of nuclear data and design and operational uncertainties shows that the analyzed assemblies respond similarly with high correlation. The calculated decay heats are highly correlated in the PWRs and BWRs, whereas lower correlations were observed between decay heats of SFAs that differ in their burnups.