Models for industrial processes are now in widespread use, but the difficult first step of selecting an appropriate model structure has received little attention. This book fills the gap, providing practical advice on model selection for chemical processes and emphasizing structures suitable for control system design.

1. Motivations and Perspectives; 2. Linear Dynamic Models; 3. Four Views of Nonlinearity; 4. NARMAX Models; 5. Volterra Models; 6. Linear Multimodels; 7. Relations between Model Classes; 8. The Art of Model Development; Bibliography; Index

Ronald K. Pearson

"The author provides an excellent view of his experiences from industry. An excellent book intended to educate the specialized reader in physical fields, particularly those who are working in the time domain. Pearson has done an excellent job of covering nonstandard topics in time series, which more than justifies the book's existence. The book contains many realistic examples, and a rich collection of scenarios with liberal references to the applied literature. It is extremely readable, and the author is to be commended for his lucid writing style. Overall, the authors presentation is insightful and consistent. It is well written and nicely organized. The books appeal is that it illustrates a wide range of results for many kinds of models that appear in stochastic processes and time series literature. Finally, this book is an important addition in the areas of nonlinear time series, and it has much to offer that is hard to find elsewhere." -- Stergios B. Fotopoulos, Technometrics