Reactive extrusion processes are widely employed by polymer processing industries for the production and modification of commercial polymers (e.g. ethylene co-polymers, polyamides, etc.). Due to strongly interacting process mechanisms and unavailability of high frequency measurements of quality variables, ‘q' (melt index, viscosity, density, etc), as well as product end-use properties, ‘w' (toughness, UV/chemical resistance, etc.), it has been very difficult to guarantee acceptable end-use product performance for this class of processes. To achieve the challenging goal of assuring acceptable end-use performance, we have proposed a modeling and control framework for effectively controlling key product properties and meeting customer requirements on end-use performance [1]. In this framework, an appropriate quantitative representation of the relationships between variables across the entire processing chain is realized through a modeling scheme consisting of a hierarchical network of judiciously selected models. These models presented in [1,2], constitute an integral part of a control scheme consisting of a fast model-based controller C₁ for the inner loop between the manipulated variables, u, and the process variables, y, and a slower (model-based) controller C₂, which translates the end-use performance objectives to set points for the process variables, y.

In this presentation, we will focus on our current work on the development of the multivariable cascade control scheme, specifically for an experimental system involving the reaction of a functionalized ethylene co-polymer, “Elvaloy” (ethylene/n-butyl acrylate/glycidal methacrylate terpolymer) with an acid co-polymer “Nucrel” (ethylene/methacrylic acid copolymer) in a Coperion W&P ZSK-30mm co-rotating, intermeshing twin-screw extruder. Previously we found that the task of designing the multivariable controller C₁ is challenging because of strong process nonlinearities and the process ill-conditioning at an operating point in the low viscosity regime [2]. In this presentation, we evaluate the performance of a gain-scheduled model predictive controller on this process for set-point tracking and disturbance rejection. We also discuss and illustrate a strategy for developing control-relevant models for the outer loop controller C₂ – models used for predicting infrequently measured product properties and for controller design. Finally, we discuss some of the issues related to the design and performance of the controller C₂. For example, since the performance of this controller is linked directly with the performance of the inner loop controller C₁, if the outer loop controller outputs set-points that are unattainable by the inner loop – unattainable primarily because of constraints on the manipulated inputs, u – there will be significant steady-state offsets in key product quality variables, resulting in poor product end-use performance. We demonstrate how the design and implementation of the product controller C₂ accounts for such possibilities.

References:

1] Garge S. C.; Wetzel M. D., and Ogunnaike B. A., “ Modeling for control of reactive extrusion processes”, ADCHEM, Gramado, Brazil, (2006).

2] Garge S. C.; Wetzel M. D., and Ogunnaike B. A., “On Identification and control of reactive extrusion processes”, AIChE Conf., Cincinnati, Ohio (2005).