A Shortcut Method for Controlled Variable Selection and Its Application to the Butane Alkylation Process

The importance of selecting controlled variables appropriately for an entire process has long been recognized. However, because of its combinatorial nature, finding an optimal set of controlled variables requires solving a large number of nonconvex optimization problems, a computationally intensive task for any realistic chemical process. In this paper, we propose a shortcut method to eliminate poor choices and to generate and rank attractive alternatives without solving optimization problems. The method is based on scaling of all of the candidate controlled variables so that they have similar effects on the steady-state profit. The procedure is illustrated on a simplified butane alkylation process.