Neural network based estimation of a semi-batch polymerisation reactor
Three different approaches for;modelling a semi-batch polymerisation reactor using artificial neural networks (ANN) have been investigated. Based on the characteristics of the semi-batch reactor a multi-stage strategy is recommended. It divides the whole reaction process into semi-batch and batch, and further divides the semi-batch part into two periods, before and after arriving at the first maximum temperature. Different ANN architectures are used to model the three parts separately. The results demonstrate that the multi-stage approach proposed can be used to estimate difficult-to-measure polymer variables with acceptable accuracy for semi-batch processes. Concentrations of monomer and initiator are estimated from reactor temperature, feed temperature and concentration of initiator in feed.
neural network estimation polymerisation reactor semi-batch process