Determining the model order of nonlinear input/output systems directly from data

The method of false nearest neighbors (FNN) is presented here as a tool for analyzing the "dimensionality" of a nonlinear input/output system directly from data. A unique feature of this method is that no specific model structure is assumed, the dimensional determination is made directly from topological considerations. An extension to the FNN algorithm is given to consider the problem of inferential measurement selection for a nonlinear system. Methods of control relevant modeling for distillation are considered, and some ideas on how to accurately model high purity distillation columns are presented.