Measurement selection for on-line estimation of nonlinear wave models for high purity distillation columns

Abstract

Nonlinear wave models are commonly used to provide a reduced-order description of distillation column dynamics. Due to the simplified model structure, on-line parameter estimation is typically required for satisfactory prediction of column performance. In this paper an approach for selecting stage composition/temperature measurements for on-line estimation of wave model parameters is presented. We focus on high purity distillation columns which are particularly challenging due to the presence of highly pinched composition profiles. The proposed method provides a compromise between two competing effects, the sensitivity of stage composition predictions to model parameters and collinearities between these sensitivities. An iterative calculation procedure based on a scaled sensitivity matrix yields a ranking of the stage compositions according to their usefulness for parameter estimation. Two high purity column simulators are used to illustrate the measurement selection procedure and the subsequent design of nonlinear state/parameter estimators using the extended Kalman filtering approach. The proposed method is shown to be more flexible than a conventional measurement selection technique based on singular value decomposition.