• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.52-54
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• 1996

A number of algorithm using the VSS(Variable Structure System) for uncertain dynamic system are developed. But, in these algorithms, the assumption that the uncertainties are bounded and their bounds are available to the designer is involved. And bounds on the uncertainties are an important clue to guarantee the stability of the closed loop system. However, sometimes bounds on the uncertainties may not be easily obtained because of the complexity of the structure of the uncertainties. Therefore, a methodology by which the boundary values on the uncertainties can be easily obtained is required. The VSS proposed in this proposal employ the new adaptive VSS scheme for uncertain dynamic system being estimated on line. The resulting control law is simple and easy to apply to on line computer control. It can also suppress chattering and maintain good tracking precision even if unmodeled dynamics are considered. And, a new method using nonlinear switching surface is introduced so that the speed response is improved and the good transient response can be obtained. Simulation results are presented and show the advantage of the proposed adaptive VSS with nonlinear switching surfaces.

• Journal of Electrical Engineering and Technology
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• v.6 no.5
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• pp.677-683
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• 2011

The present paper describes the setup of standard partial discharge calibrator for measuring partial discharge and estimating uncertainties. The standard PD calibrator was designed and set up, consisting of a digital pulse generator, capacitor modules, and a digital oscilloscope controlled by software developed in the laboratory. Using this software, averages of charges and rising times and their standard deviations in the measured pulses can also be calculated. The standard PD calibrator generates five types of pulses: single, double, random, oscillating, and long-rising. The coefficient sensitivities to estimate the uncertainties of pulses were extracted in the model circuit of the standard PD calibrator. The uncertainties of charges and rising times in pulses of the standard PD calibrator were estimated with single pulses. These values were 0.3%-1.4% in charges and 1.9%-7.0% in rising time; however, these values are lower than the limit values in IEC 60270.

• Nuclear Engineering and Technology
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• v.46 no.1
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• pp.11-26
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• 2014

The analyses carried out within the Seismic Probabilistic Risk Assessments (SPRAs) of Nuclear Power Plants (NPPs) are affected by significant aleatory and epistemic uncertainties. These uncertainties have to be represented and quantified coherently with the data, information and knowledge available, to provide reasonable assurance that related decisions can be taken robustly and with confidence. The amount of data, information and knowledge available for seismic risk assessment is typically limited, so that the analysis must strongly rely on expert judgments. In this paper, a Dempster-Shafer Theory (DST) framework for handling uncertainties in NPP SPRAs is proposed and applied to an example case study. The main contributions of this paper are two: (i) applying the complete DST framework to SPRA models, showing how to build the Dempster-Shafer structures of the uncertainty parameters based on industry generic data, and (ii) embedding Bayesian updating based on plant specific data into the framework. The results of the application to a case study show that the approach is feasible and effective in (i) describing and jointly propagating aleatory and epistemic uncertainties in SPRA models and (ii) providing 'conservative' bounds on the safety quantities of interest (i.e. Core Damage Frequency, CDF) that reflect the (limited) state of knowledge of the experts about the system of interest.

• Nuclear Engineering and Technology
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• v.56 no.2
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• pp.762-769
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• 2024

The TMSR-SF0 simulator is an integral effect thermal-hydraulic experimental system for the development of thorium molten salt reactor (TMSR) program in China. The simulator has two heat transport loops with liquid FLiNaK. In literature, the 95% level confidence uncertainties of the thermophysical properties of FLiNaK are recommended, and the uncertainties of density, heat capacity, thermal conductivity and viscosity are ±2%, ±10, ±10% and ±10% respectively. In order to investigate the effects of thermophysical properties uncertainties on the molten salt heat transport system, the uncertainty and sensitivity analysis of the heat transfer characteristics of the simulator system are carried out on a RELAP5 model. The uncertainties of thermophysical properties are incorporated in simulation model and the Monte Carlo sampling method is used to propagate the input uncertainties through the model. The simulation results indicate that the uncertainty propagated to core outlet temperature is about ±10 ℃ with a confidence level of 95% in a steady-state operation condition. The result should be noted in the design, operation and code validation of molten salt reactor. In addition, more experimental data is necessary for quantifying the uncertainty of thermophysical properties of molten salts.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.548-551
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• 1997

Performance of force tracking impedance control of robot manipulators is degraded by the uncertainties in the robot and environment dynamic model. The purpose of this paper is to improve the controller robustness by applying neural network. Neural networks are designed to learn the uncertainties in robot and environment model for compensating the uncertainties. The proposed scheme is verified through the simulation of 20DOF robot manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2004-2009
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• 2003

A robust optimal control design is proposed in this study for rigid robotic systems under the unknown load and the other uncertainties. The uncertainties are quadratically bounded for some positive definite matrix. Iterative method finding the Q weighting matrix is shown. Computer simulations have been done for a weight-lifting operation of a two-link manipulator and the result of the simulation shows that the proposed algorithm is very effective for a robust control of robotic systems.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.4
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• pp.207-211
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• 2004

We consider a class of uncertain nonlinear systems containing the uncertainties without a priori information except that they are bounded. For such systems, we assume that the upper bound of the uncertainties is represented as a Fredholm integral equation of the first kind and we propose an adaptation law that is capable of estimating the upper bound. Using this adaptive upper bound, a continuous robust control which renders uncertain nonlinear systems uniformly ultimately bounded is designed.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.125.3-125
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• 2001

Recently, aircraft is designed to have high maneuverable at high angle of attack. However, it is very hard to obtain the accurate dynamic model for the high performance, because aerodynamic characteristics are nonlinear and include a lot of uncertainties. Therefore, nonlinear controller without considering uncertainties may degrade the control system performance. On this paper, to overcome these defects, the neural networks based adaptive nonlinear controller is proposed making use of the backstepping technique. Neural networks are implemented to guarantee robustness to uncertainties caused by aerodynamic coefficients variation. The main feature of the proposed controller is that the adaptive controller is developed under the assumption ...

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.455-458
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• 2003

An optimal control approach to robust control design is proposed in this study for rigid robotic systems under the unknown load and the other uncertainties. The uncertainties are quadratically bounded for some positive definite matrix. Iterative method to find the matrix is shown. Simulations arc made for a weight-lifting operation of a two-link manipulator and the robust control performance of robotic systems by the proposed algorithm is remarkable.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.742-746
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• 1992

This paper proposes a new linear robust state feedback controller for the linear discrete time systems which have uncertainties in the state and input matrices. The uncertainties need not satisfy the matching conditions, but only their bounds are needed to be known. The proposed controller is derived from the linear quadratic game problem, which solution is obtained via the modified algebraic Riccati equation. The controller guarantees the robust performance bound. The bound of the solution and the condition of the uncertainties, which can stabilize the uncertain system are explored.