Advances in Optimal Control of Polymerization Reactors
نویسنده
چکیده
Optimal control of polymerization reactors is of immense interest due to necessity of operating these reactors optimally to produce a polymer product with desired quality characteristics. In the past, various classical methods have been reported for optimal control of polymerization reactors. However, stochastic and evolutionary optimization methods are found effective in solving complex optimization problems due to their flexibility, ease of operation and global perspective. This chapter deals with the recent advances in optimal control of polymerization reactors. Different multistage dynamic optimization strategies based on iterative dynamic programming (IDP), differential evolution (DE) and tabu search (TS) that seek global optimum of more difficult engineering problems are presented. The optimal control performance of these strategies are evaluated and analyzed through their application to a semi-batch styrene-acrylonitrile (SAN) copolymerization reactor.
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