High-Purity Distillation

Abstract

Distillation is one of the most common separation techniques in chemical manufacturing. This multi-input, multi-output staged separation process is strongly interactive, as determined by the singular value decomposition of a linear dynamic model of the system. Process dynamics associated with the low-gain direction are critical to the design of high-performance controllers for high-purity distillation but are difficult to estimate from conventional experimental test signals for identification. As a result, high-purity distillation columns are considered challenging cases for multivariable system identification and robust control system design. High-purity distillation is a challenging process application for system identification because of its nonlinear and strongly interactive dynamics. This article has described several constrained-optimization-based formulations for multisine input signal design that allow users to simultaneously specify the essential frequency- and time-domain properties of these signals. Because constraints are explicitly part of the design procedure, the approach is useful for accomplishing plant-friendly identification testing in the process industries. The problem formulations were evaluated for a highly nonlinear methanol-ethanol distillation column. Introducing directional sinusoids in the multisine signal, applying a closed-loop signal design, and minimizing an objective function based on Weyl's theorem enhanced the information content of the low-gain direction in the identification experiment.