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10.1109/CSSim.2009.22guideproceedingsArticle/Chapter ViewAbstractPublication PagesConference Proceedingsacm-pubtype
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Diagnosis of a Continous Stirred Tank Reactor Using Kalman Filter

Published: 07 September 2009 Publication History

Abstract

This paper is dedicated to complex system diagnosis. Therefore, a Kalman filter has been proposed to cope with external disturbances and unpredictable faults that are associated with chemical processes. The Continuous Stirred Tank Reactor (CSTR) model with parametric uncertainties is linearized around a chosen steady state and discretized to apply the diagnosis approach. A Kalman filter is employed to generate conversion estimate for the CSTR using only temperature measurements and precedent estimates. Numerical simulation Results of a no isothermal CSTR with coolant jacket dynamics are presented. Robustness with respect to interpolation errors, disturbances and model parametric uncertainties is achieved by using the obtained Kalman filter.

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  • (2019)Fault detection and identification using combination of EKF and neuro-fuzzy network applied to a chemical process (CSTR)Pattern Analysis & Applications10.1007/s10044-017-0634-722:2(359-373)Online publication date: 25-May-2019
  1. Diagnosis of a Continous Stirred Tank Reactor Using Kalman Filter

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    Published In

    cover image Guide Proceedings
    CSSIM '09: Proceedings of the 2009 International Conference on Computational Intelligence, Modelling and Simulation
    September 2009
    295 pages
    ISBN:9780769537955

    Publisher

    IEEE Computer Society

    United States

    Publication History

    Published: 07 September 2009

    Author Tags

    1. Actuator and sensor faults
    2. CSTR
    3. Fault Detection and Isolation
    4. Kalman filter
    5. Model Parametric Uncertainties

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    • (2019)Fault detection and identification using combination of EKF and neuro-fuzzy network applied to a chemical process (CSTR)Pattern Analysis & Applications10.1007/s10044-017-0634-722:2(359-373)Online publication date: 25-May-2019

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