• Title/Summary/Keyword: modelling errors

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ON-LINE FAULT DETECTION METHOD ACCOUNTINE FOR MODELLING ERRORS

  • Kim, Seong-Jin;Kwon, Oh-Kyu
    • 제어로봇시스템학회:학술대회논문집
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    • 1990.10b
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    • pp.1228-1233
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    • 1990
  • This paper proposes a robust on-line fault detection method for uncertain systems. It is based on the fault detection method [10] accounting for modelling errors, which is shown to have superior performance over traditional methods but has some computational problems so that it is hard to be applied to on-line problems. The proposed method in this paper is an on-line version of the fault detection method suggested in [10]. Thus the method has the same detection performance robust to model uncertainties as that of [10]. Moreover, its computational burden is shown to be considerably lessened so that it is applicable to on-line fault detection problems.

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A Design of the Robust Controller for an Active Noise Control

  • Chung, Tae-Jin
    • The Journal of the Acoustical Society of Korea
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    • v.17 no.1E
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    • pp.3-9
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    • 1998
  • In this paper, a robust active noise controller is designed to reduce noise in al small cavity. Noise characteristics in the small cavity are nonlinear and we could get its model with considerable modelling errors. The objective of this paper is to minimize the effects of these modelling errors and maximize the noise reduction performance. The solution could be obtained by the H∞ robust control theory. The resulting feedback controller minimizes the H∞ norm of the mixed sensitivity function, which means the effects of uncertainties of the model are suppressed in the sense of stability and the performance is enhanced as a given specification. The designed controller is realized with analog devices such as Op. Amps and experimental results show that the controller reduces noise signal sufficiently.

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Verification of OpenMC for fast reactor physics analysis with China experimental fast reactor start-up tests

  • Guo, Hui;Huo, Xingkai;Feng, Kuaiyuan;Gu, Hanyang
    • Nuclear Engineering and Technology
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    • v.54 no.10
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    • pp.3897-3908
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    • 2022
  • High-fidelity nuclear data libraries and neutronics simulation tools are essential for the development of fast reactors. The IAEA coordinated research project on "Neutronics Benchmark of CEFR Start-Up Tests" offers valuable data for the qualification of nuclear data libraries and neutronics codes. This paper focuses on the verification and validation of the CEFR start-up modelling using OpenMC Monte-Carlo code against the experimental measurements. The OpenMC simulation results agree well with the measurements in criticality, control rod worth, sodium void reactivity, temperature reactivity, subassembly swap reactivity, and reaction distribution. In feedback coefficient evaluations, an additional state method shows high consistency with lower uncertainty. Among 122 relative errors in the benchmark of the distribution of nuclear reaction, 104 errors are less than 10% and 84 errors are less than 5%. The results demonstrate the high reliability of OpenMC for its application in fast reactor simulations. In the companion paper, the influence of cross-section libraries is investigated using neutronics modelling in this paper.

Error Analysis and Modeling of Airborne LIDAR System (항공라이다시스템의 오차분석 및 모델링)

  • Yoo Byoung-Min;Lee Im-Pyeong;Kim Seong-Joon;Kang In-Ku
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2006.04a
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    • pp.199-204
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    • 2006
  • Airborne LIDAR systems have been increasingly used for various applications as an effective surveying mean that can be complementary or alternative to the traditional one based on aerial photos. A LIDAR system is a multi-sensor system consisting of GPS, INS, and a laser scanner and hence the errors associated with the LIDAR data can be significantly affected by not only the errors associated with each individual sensor but also the errors involved in combining these sensors. The analysis about these errors have been performed by some researchers but yet insufficient so that the results can be critically contributed to performing accurate calibration of LIDAR data. In this study, we thus analyze these error sources, derive their mathematical models and perform the sensitivity analysis to assess how significantly each error affects the LIDAR data. The results from this sensitivity analysis in particular can be effectively used to determine the main parameters modelling the systematic errors associated with the LIDAR data for their calibration.

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Numerical and experimental verifications on damping identification with model updating and vibration monitoring data

  • Li, Jun;Hao, Hong;Fan, Gao;Ni, Pinghe;Wang, Xiangyu;Wu, Changzhi;Lee, Jae-Myung;Jung, Kwang-Hyo
    • Smart Structures and Systems
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    • v.20 no.2
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    • pp.127-137
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    • 2017
  • Identification of damping characteristics is of significant importance for dynamic response analysis and condition assessment of structural systems. Damping is associated with the behavior of the energy dissipation mechanism. Identification of damping ratios based on the sensitivity of dynamic responses and the model updating technique is investigated with numerical and experimental investigations. The effectiveness and performance of using the sensitivity-based model updating method and vibration monitoring data for damping ratios identification are investigated. Numerical studies on a three-dimensional truss bridge model are conducted to verify the effectiveness of the proposed approach. Measurement noise effect and the initial finite element modelling errors are considered. The results demonstrate that the damping ratio identification with the proposed approach is not sensitive to the noise effect but could be affected significantly by the modelling errors. Experimental studies on a steel planar frame structure are conducted. The robustness and performance of the proposed damping identification approach are investigated with real measured vibration data. The results demonstrate that the proposed approach has a decent and reliable performance to identify the damping ratios.

Compensation for temperature-level control of tanked water system with time delay

  • Nakamura, Masatoshi;Watanabe, Kiyoto
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10b
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    • pp.42-47
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    • 1993
  • Importance of separation of a nonlinear dynamical system into nonlinear static part and linear dynamical part was insisted in designing a controller for the nonlinear system. We further proposed compensation techniques for oscillation of controlled variables caused by system time delay and compensation of steady state errors caused by modelling errors of the systems. The proposed principle of designing procedure and the compensation methods were discussed by applying them for temperature and level control of an actual tanked water system.

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Iterative learning control for a class of discrete-time nonlinear systems (이산시간 비선형 시스템에 대한 반복학습제어)

  • 안현식;최종호;김도현
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10a
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    • pp.836-841
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    • 1993
  • For a class of discrete-time nonlinear systems, an iterative learning control method is proposed and a sufficient condition is derived for the convergence of the output error. The proposed method is shown to be less sensitive to modelling errors and the uniform boundedness of the output error is guaranteed even in the presence of initial state errors. It is illustrated by simulations that the actual output converges to a desired output within the tolerance bound and convergence performance is improved by the presented method.

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A Robust Fault Detection method for Uncertain Systems with Modelling Errors (모델링 오차를 갖는 불확정 시스템에서의 견실한 이상 검출기)

  • 권오주;이명의
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.39 no.7
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    • pp.729-739
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    • 1990
  • This paper deals with the fault detection problem in uncertain linear/non-linear systems having both undermodelling and noise. A robust fault detection method is presented which accounts for the effects of noise, model mismatch and nonlinearities. The basic idea is to embed the unmodelled dynamics in a stochastic process and to use the nominal model with a predetermined fixed denominator. This allows the input /output relationship to be represented as a linear function of the system parameters and also facilitate the quatification of the effect of noise, model mismatch and linearization errors on parameter estimation by the Bayesian method. Comparisons are made via simulations with traditional fault detection methods which do not account for model mismatch or linearization errors. The new method suggested in this paper is shown to have a marked improvement over traditional methods on a number of simulations, which is a consequence of the fact that the new method explicitly for the effects of undermodelling and linearization errors.

Design of robust autopilot for underwater vehicle (수중운동체의 강인한 자동조종장치 설계)

  • 정연태;김인환;옥질표;권순홍;이만형
    • 제어로봇시스템학회:학술대회논문집
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    • 1990.10a
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    • pp.653-657
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    • 1990
  • Since linearized equations of notion have much modelling errors, robust controller for disturbances and noises Is necessary for autopilot. In this paper, notion equations for underwater vehicle with six degree-of-freedom are derived and linearized. And robust autopilot for this system is designed by using LQG/LTR methodology.

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