This book addresses the critical, often overlooked challenge of selecting appropriate model structures for the control of industrial chemical processes. Ronald K. Pearson, an expert in signal processing and system identification, provides a systematic framework for navigating the complexities of model selection. By focusing on discrete-time dynamic models, the text bridges the gap between theoretical modeling literature and the practical requirements of modern control system design.

Experts recognize this work as a specialized resource for engineers and researchers focused on process control. Readers frequently note the technical density of the prose, which serves as a foundational reference for those integrating advanced computational models into industrial environments.