NONLINEAR INPUT-OUTPUT MODELING

This paper gives a highly abbreviated overview of some of the key issues in empirical nonlinear modelling for chemical process applications. This task is complicated by the inherent nature of nonlinearity: the term describes a class of systems by the one feature they lack. In fact, this division - linear vs. nonlinear - suggests a 'unity' or 'homogeneity' of the class of nonlinear systems that does not exist. Consequently, this review will focus on specific sub-classes of nonlinear models that have analytically useful structural characteristics, and comparisons will be made both between these classes and with the more familiar linear models. Length limitations restrict these discussions somewhat, but it is hoped that the range of examples will be great enough to demonstrate how nonlinear model identification is both similar to and different from linear model identification. The general conclusion of this paper is that nonlinear input/output modelling is a vitally important practical art with many unresolved issues; the principal objective of this paper is to elucidate some of these issues.