Dynamic Modeling and Simulation of Low Density Polyethylene Production – A Comparative Study

Abstract

This study deals with the modelling and simulation of low density polyethylene (LDPE) production. LDPE is one of the most widely produced polymers which appears in the form of simple goods in our everyday life (e.g. food and pharmaceutical packaging, carrier bags). It is produced in a complex industrial process which takes place under extreme operating conditions (at pressure of ca. 2000-3000 bar) and may lead to nonlinear dynamics due to highly exothermic addition polymerization reactions. In principle, the process is represented by a distributed system with an external coordinate (the reactor length > 1000m) and various internal coordinates (the chain length of the polymer molecules, short and long chain branching and the number of double bounds), which can have strong effect on product properties. In this contribution a detailed reference model is introduced and possible model simplifications are discussed systematically from an on-line optimization and control point of view.

Low‐density polyethylene tubular reactor control using neural Wiener model predictive control

“…7 However, controlling the LDPE polymerization process is not a trivial task, as it is reported to demonstrate dynamic nonlinear behaviors. 8,9 Moreover, the availability of multiple reactor parameters to be controlled (such as initiators and chain transfer agent [CTA] flow rates) and monitored (such as reactor temperatures, conversion, and melt flow index [MFI]) has made the LDPE tubular reactor production into a multivariable system. 10 In addition, the need to produce multiple polymer grades requires the plant controller to control a broad operating region.…”