MURAL - Maynooth University Research Archive Library

    A Robust Multi-Model Predictive Controller for Distributed Parameter Systems

    García, Míriam R. and Vilas, Carlos and Santos, Lino O. and Alonso, Antonio A. (2012) A Robust Multi-Model Predictive Controller for Distributed Parameter Systems. Journal of Process Control, 22 (1). pp. 60-71. ISSN 0959-1524

    [img] Download (698kB)

    Share your research

    Twitter Facebook LinkedIn GooglePlus Email more...

    Add this article to your Mendeley library


    In this work a robust nonlinear model predictive controller for nonlinear convection-diusion-reaction systems is presented. The controller makes use of a collection of reduced order approximations of the plant (models) reconstructed on-line by projection methods on POD (Proper Orthogonal Decomposition) basis functions. The model selection and model update step is based on a sucient condition that determines the maximum allowable process-model mismatch to guarantee stable control performance despite process uncertainty and disturbances. Proofs on the existence of a sequence of feasible approximations and control stability are given. Since plant approximations are built on-line based on actual measurements the proposed controller can be interpreted as a multi-model nonlinear predictive control (MMPC). The performance of the MMPC strategy is illustrated by simulation experiments on a problem that involves reactant concentration control of a tubular reactor with recycle.

    Item Type: Article
    Additional Information: Preprint version of original published article. The definitive version of this article is available from at DOI:
    Keywords: Plant Model Mismatch; Proper Orthogonal Decomposition; Controller Stability; Projection methods;
    Academic Unit: Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 3623
    Depositing User: Miriam Garcia
    Date Deposited: 01 May 2012 15:30
    Journal or Publication Title: Journal of Process Control
    Publisher: Elsevier
    Refereed: No
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

    Repository Staff Only(login required)

    View Item Item control page


    Downloads per month over past year

    Origin of downloads