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

Yue, H. and Wang, H. and Zhang, J. (2008) Shaping of molecular weight distribution by iterative learning probability density function control strategies. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 222 (7). pp. 639-653. ISSN 0959-6518 (https://doi.org/10.1243/09596518JSCE584)

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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-Zimmdistribution. 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.

ORCID iDs

Yue, H. ORCID logoORCID: https://orcid.org/0000-0003-2072-6223, Wang, H. and Zhang, J.;
CORE (COnnecting REpositories)