Simultaneous Process and Control System Design for Optimal Grade Transition in a Styrene Polymerization Reactor

ASTEASUAIN, MARIANO; BRANDOLIN, ADRIANA; SARMORIA, CLAUDIA; BANDONI, ALBERTO

Valencia

Simposio; VII Simposio Latinoamericano de Polímeros; 2004

Universidad Politécnica de Valencia

Grade transition optimization is very important for a profitable operation of continuous polymerization processes. Polymers have many application areas, and each area demands different grade specifications. In order to achieve market requirements, continuous polymer plants usually alternate between the production of several polymer grades in the same equipment by switching the operating points. Since this operation can be performed even every few days, it is essential to determine optimal transition policies that minimize the production of off-specification material and the transition time. In addition to this, it is necessary to count with a suitable control system that guarantees that the optimal transition policies are actually followed, and also ensures safe process operation.This has motivated intense research on grade transition optimization and control of polymerization reactors. In most cases, however, a sequential approach has been used to deal with control system design and optimization of transition policies. By following this sequential methodology, the strong interaction between process design and control is not accounted for. Although several works in other fields of chemical engineering have shown the great benefits of incorporating control aspects in the process design stages (2), few efforts have been done in this direction in polymer engineering.In this work we focus on grade transition operation in a CSTR styrene polymerization reactor. A Mixed ? Integer Dynamic Optimization (MIDO) approach is used to simultaneously design the process and its control system for A  B grade transition sequences. The process design involves reactor size and initiator type selection (discrete decisions), and the two steady state operating points in which each polymer grade is produced (continuous decisions). Simultaneously, feedforward ? feedback controllers are optimally designed to drive the process between steady states. The proposed control superstructure for PI feedback controllers involves the monomer, initiator and coolant flow rates as possible manipulated variables, and the reactor temperature, jacket temperature, number average molecular weight and polymerization rate as possible controlled variables. Optimal pairings between them must be determined (discrete decisions) as well as the controllers tuning parameters and the set points of the controlled variables (continuous decisions). The feedforward controllers? signals consist of time-varying profiles for each manipulated variable, which are calculated by the optimizer.