Optimal control of a rate-based modelled batch distillation column: Initialization strategy

Abstract

Batch distillation columns are dynamic processes represented by a system of differential and algebraic equations (DAE). Their optimal control problem can be solved through orthogonal collocation, which is an effective discretization method with accurate approximations to the behavior of state and control variables. Convergence of such technique is greatly improved by providing good initial values and bounds of the variables. Thus, this work proposes a strategy to estimate the initial values for a sieve trays batch distillation column modeled with a rate-based approach. During the initialization procedure, the modeling equations are solved under a steady state assumption by using the GAMS modeling environment. An experimental pilot scale batch distillation column was used as the case-study to evaluate the proposed initialization algorithm. This column was used to separate a mixture of methanol and ethanol. The initialization results for the state profiles show good agreement with the experimental results.