Optimized on-line control of MMA polymerization using fast multi-objective DE

ABSTRACT

Optimized on-line control (OOC) of polymerization reactors combine the optimization with the on-line operation and control. In this, re-optimized control variable trajectories, in the presence of unplanned disturbances, are obtained and implemented on-line to save the batch. Also, the available computational time for the optimization is limited as the re-optimized trajectories need to be implemented in real time on the actual system. In the present study, the OOC of such a system, i.e., bulk polymerization of methyl methacrylate (MMA) in a batch reactor, is carried out in the occurrence of heater malfunction. To solve the underlying multi-objective problem, a multi-objective variant of differential evolution with an improved mutation strategy is developed. The developed algorithm shows faster convergence with respect to other compared algorithms for a large number of benchmark problems. Finally, this algorithm is used to find the optimal temperature trajectories and the OOC with these trajectories found to be successfully countering the effect of heater malfunction.

KEYWORDS:

• Batch-reactor
• chain-growth
• control
• convergence
• DE
• multi-objective
• optimization
• polymerization
• temperature
• trajectory