Multivariate Model Identification and Stochastic Control of a Chemical Reactor

Multivariate time series and process identification methods are used to develop a dynamicstochastic model for a packed bed tubular reactor carrying out highly exothermic hydrogenolysis reactions. A canonical analysis procedure is used on the data collected from the reactor to first reduce the dimensionality of the identification and control problems. The identified transfer function-ARIMA model is transformed into a state space model form and …