IMPLEMENTATION OF ADAPTIVE OPTIMAL OPERATION FOR A SEMIBATCH REACTIONSYSTEM

This paper presents the results of on-line optimization of the acetoac etylation of pyrrole with diketene in a laboratory-scale reactor. In a ddition to the desired reaction of pyrrole to 2-acetoacetyl pyrrole, t here are several undesired side reactions. The selectivity can be cont rolled by adjusting the feed rate of diketene to a given solution of p yrrole. Variable amounts of impurities in the crude pyrrole imply diff erent rate constants for each batch. Consequently, on-line estimation of some rate constants and subsequent adjustment of the feeding strate gy through dynamic optimization are necessary to reach a desired objec tive. The nonlinear differential-algebraic optimization problems for b oth the estimation and the optimization are transformed into nonlinear algebraic optimization problems (AOP). Due to the different character istics of the estimation and optimization problems, the resulting AOPs are solved using different techniques. Successive quadratic programmi ng is applied to solve the AOP in the estimation, and successive linea r programming is used for the optimization. Both are fast infeasible-p ath methods. The estimation and optimization problems are solved seque ntially at given points in time. Results are presented for the minimiz ation of batch time subject to endpoint constraints with respect to yi eld and two of the concentrations. Runs with and without on-line optim ization are compared to demonstrate the effectiveness of the on-line s trategy. (C) 1997 Elsevier Science Ltd.