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    Extension of first order Predictive Functional Controllers to handle higher order internal models


    Khadir, Mohamed Tarek and Ringwood, John (2008) Extension of first order Predictive Functional Controllers to handle higher order internal models. International Journal of Applied Mathematics and Computer Science, 18 (2). pp. 229-239. ISSN 2083-8492

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    Abstract

    Predictive Functional Control (PFC), belonging to the family of predictive control techniques, has been demonstrated as a powerful algorithm for controlling process plants. The input/output PFC formulation has been a particularly attractive paradigm for industrial processes, with a combination of simplicity and effectiveness. Though its use of a lag plus delay ARX/ARMAX model is justified in many applications, there exists a range of process types which may present difficulties, leading to chattering and/or instability. In this paper, instability of first order PFC is addressed, and solutions to handle higher order and difficult systems are proposed. The input/output PFC formulation is extended to cover the cases of internal models with zero and/or higher order pole dynamics in an ARX/ARMAX form, via a parallel and cascaded model decomposition. Finally, a generic form of PFC, based on elementary outputs, is proposed to handle a wider range of higher order oscillatory and non-minimum phase systems. The range of solutions presented are supported by appropriate examples.

    Item Type: Article
    Keywords: model predictive control; predictive functional control; non-minimum phase systems; oscillatory systems;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Item ID: 9494
    Depositing User: Professor John Ringwood
    Date Deposited: 22 May 2018 11:36
    Journal or Publication Title: International Journal of Applied Mathematics and Computer Science
    Publisher: De Gruyter Open
    Refereed: Yes
    URI:

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