On-Line Optimization for a Batch-Fed Copolymerization Reactor with Partial State Measurement

Abstract

Polymerization processes require adequate monitoring to ensure that the final product meets specification. Various on-line measuring techniques have been developed and implemented to track polymer properties in reactors. For most processes, however, on-line measurement cannot be implemented. In other situations, certain polymer properties or states might not be measurable and hence have to be estimated. This work deals with improving an on-line optimization technique and demonstrating its eff ectiveness by sensitivity analysis. In addition, state estimation is used as a tool to reconstruct states that are unavailable for measurement in a styrene and butyl methacrylate batch-fed solution free-radical copolymerization process subject to on-line optimization. A hybrid extended Kalman filter is used to observe the nonlinear dynamic system which is subject to real-time dynamic optimization. With very limited measurement information, the states of the system were reconstructed. Additional unobservable quantities were reconstructed using the process model and estimated states.