Nonlinear model predictive control (NMPC) is used to maintain and control polymer quality at speci-
fied production rates because the polymer quality measures have strong interacting nonlinearities with
different temperatures and feed rates. Polymer quality measures that are available from the laboratory
infrequently are controlled in closed-loop using a NMPC to set the temperature profile of the reactors.
NMPC results in better control of polymer quality measures at different production rates as compared
to using the nonlinear process model with reaction kinetics to implement offline targets for reactor
temperatures.