Shaping of molecular weight distribution by iterative learning probability density function control strategies

H. Yue, H. Wang, J. Zhang

    Research output: Contribution to journalArticlepeer-review

    Abstract

    A mathematical model is developed for the molecular weight distribution (MWD) of free-radical styrene polymerization in a simulated semi-batch reactor system. The generation function technique and moment method are employed to establish the MWD model in the form of Schultz-Zimm distribution. Both static and dynamic models are described in detail. In order to achieve the closed-loop MWD shaping by output probability density function (PDF) control, the dynamic MWD model is further developed by a linear B-spline approximation. Based on the general form of the B-spline MWD model, iterative learning PDF control strategies have been investigated in order to improve the MWD control performance. Discussions on the simulation studies show the advantages and limitations of the methodology. © IMechE 2008.
    Original languageEnglish
    Pages (from-to)639-653
    Number of pages14
    JournalProceedings of the Institution of Mechanical Engineers. Part I: Journal of Systems and Control Engineering
    Volume222
    Issue number7
    DOIs
    Publication statusPublished - 2008

    Keywords

    • B-spline model
    • Iterative learning control (ILC)
    • Molecular weight distribution (MWD)
    • Probability density function (PDF)

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