• 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.

• Computational Structural Engineering : An International Journal
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• v.1 no.2
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• pp.81-87
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• 2001

A framework for reliability analysis of structural components and systems under conditions of statistical and model uncertainty is presented. The Bayesian parameter estimation method is used to derive the posterior distribution of model parameters reflecting epistemic uncertainties. Point, predictive and bound estimates of reliability accounting for parameter uncertainties are derived. The bounds estimates explicitly reflect the effect of epistemic uncertainties on the reliability measure. These developments are enhance-ments of second-moment uncertainty analysis methods developed by A. H-S. Ang and others three decades ago.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.10
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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.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1500-1503
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• 1996

This paper combines the disturbance accommodating control(DAC) and nonlinear model inversion control for a skid-to-turn(STT) missile. The missile autopilot may be designed to be robust with respect to a variety of uncertainties. We proposes the two step control design method. Nonlinear model inversion control is used as the main design method. Due to the model uncertainties and external disturbances, the exact nonlinear model inversion can not be achieved. DAC is designed to detect, to identify, and to compensate these uncertainties. DAC's disturbance observer is linear. Thus it is easy to implement. It does not cause the convergence problem due to coexistence between the modeling uncertainties and external disturbances. 6 DOF simulation results show that the proposed method may improve the missile tracking performance.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.4 s.181
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• pp.44-51
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• 2006

This paper addresses sliding mode control of the anti-lock braking system (ABS) with a disturbance observer for model uncertainties such as vehicle parameter variation, un-modeled dynamics, and external disturbances. By using a nominal vehicle model, a sliding mode controller is designed to achieve a desired wheel slip ratio for ABS control. To compensate the model uncertainties, a disturbance observer is introduced with the help of a transfer function of a hydraulic brake dynamics. A proposed sliding mode controller with a disturbance observer is evaluated through simulations for model uncertainties. The simulation results show that the disturbance observer can enhance performances of sliding mode control for ABS.

• Structural Engineering and Mechanics
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• v.27 no.3
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• pp.263-276
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• 2007

This paper presents a fuzzy finite element model for the analysis of structures in the presence of multiple uncertainties. A new methodology to evaluate the cumulative effect of multiple uncertainties on structural response is developed in the present work. This is done by modifying Muhanna's approach for handling single uncertainty. Uncertainty in load and material properties is defined by triangular membership functions with equal spread about the crisp value. Structural response is obtained in terms of fuzzy interval displacements and rotations. The results are further post-processed to obtain interval values of bending moment, shear force and axial forces. Membership functions are constructed to depict the uncertainty in structural response. Sensitivity analysis is performed to evaluate the relative sensitivity of displacements and forces to uncertainty in structural parameters. The present work demonstrates the effectiveness of fuzzy finite element model in establishing sharp bounds to the uncertain structural response in the presence of multiple uncertainties.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.161-166
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• 1990

In this paper, Proposed the robust controller for robot manipulator plus actuator with dynamic parameter uncertainties. In general, errors and uncertainties system parameters exist more or less between the actual system and mathematical model. To reduce these trems, used Lyapunov stability theorem. The performance of the controller is evaluated for the three degree of freedom robot manipulator plus actuator model with uncertainties of parameters and model errors.

• International Journal of Automotive Technology
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• v.8 no.3
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• pp.351-359
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• 2007

In this study, a hierarchical switching control scheme based on robust control theory is proposed for tracking control of vehicle longitudinal acceleration in the presence of large uncertainties. A model set consisting of four multiplicative-uncertainty models is set up, and its corresponding controller set is designed by the LMI approach, which can ensures the robust performance of the closed loop system under arbitray switching. Based on the model set and the controller set, a switching index function by estimating the system gain of the uncertainties between the plant and the nominal model is designed to determine when and which controller should be switched into the closed loop. After theoretical analyses, experiments have also been carried out to validate the proposed control algorithm. The results show that the control system has good performance of robust stability and tracking ability in the presence of large uncertainties. The response time is smaller than 1.5s and the max tracking error is about $0.05\;m/S^2$ with the step input.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.2
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• pp.43-51
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• 2017

In this study, the effect of the steering vector model mismatch due to array uncertainties on the performance of array processing was analyzed through simulation, along with the alleviation of the model mismatch effect depending on array calibration. To increase the reliability of the simulation results, the actual steering vector of the array antenna obtained by electromagnetic simulation was used along with the Jahn's channel model, which is an experimental channel model. Based on the analysis of the power spectrum for each direction, beam pattern, and the signal-to-interference-plus-noise ratio of the beamformer output, the performance deterioration of array processing due to array uncertainties was examined, and the performance improvement of array processing through array calibration was also examined.