Dynamic data reconciliation for sequential modular simulators: application to a mixing process

V. M. Becerra, P. D. Roberts, G. W. Griffiths

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    This paper describes a method for dynamic data reconciliation of nonlinear systems that are simulated using the sequential modular approach, and where individual modules are represented by a class of differential algebraic equations. The estimation technique consists of a bank of extended Kalman filters that are integrated with the modules. The paper reports a study based on experimental data obtained from a pilot scale mixing process.
    Original languageEnglish
    Title of host publication Proceedings of the 2000 American Control Conference, 2000
    Place of PublicationPiscataway
    PublisherIEEE
    Pages2740-2744
    Volume4
    ISBN (Print)0780355199
    DOIs
    Publication statusPublished - 2000

    Keywords

    • Kalman filters, data reconciliation, differential algebraic equations, mixing process, nonlinear systems, process control, sequential modular simulators

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