Impact of model uncertainty descriptions for high-purity distillation control

The ways in which modeling uncertainties are described for a particular process critically affects the results obtained in robustness studies. In this paper, four multivariable robust stability methodologies are used to characterize and analyze the effects of model inaccuracy due to non-linearity in high-purity distillation processes. The unstructured and structured singular value, numerical range, and a mapping of det(l + GPGc) are compared in terms of their ability to predict the stability of the dual-composition control system over a wide composition range. The importance of using uncertainty descriptions that include a realistic representation of the phase-magnitude relationship as well as the corrections between uncertainties in each element of the model is demonstrated. The conservation associated with norm-bounded uncertainty descriptions reveals itself by the extent of detuning needed to insure stability and the subsequent degradation in control performance.