Nonlinear Model-Based Control: Using First-Principles Models in Process Control (International Society of Automation)

Nonlinear Model-Based Control: Using First-Principles Models in Process Control

First-principles models (engineering models) are used in industry for process design, troubleshooting, training, online analysis and supervisory optimization. The author's vision is to use them for control.

Why? They effectively handle nonlinearity, nonstationary behavior and interacting variables with just one tuning coefficient per controlled variable (CV). Using optimization, the controller can handle constraints and shape the manipulated variables to achieve desired controlled variable trajectories. Using first-principles models for control can also enhance the operational staff's understanding of the process, support auxiliary process management, and keep the mathematics at the engineers' comfort level. In addition, unifying all models across diverse process management operations ensures continuity and compatibility.

The book explains four control techniques using first-principles models that have been credibly demonstrated for industrial practice: generic model control, process-model-based control, predictive functional control and horizon predictive control. It illustrates their applications and discusses the pros and cons of each. To provide a better understanding of first-principles models, the book includes examples of setting up functions for controllers and discusses inherent properties such as ease of tuning, the handling of nonlinearity and interaction, feedforward constraints and the range of operation.

Dr. R. Russell Rhinehart, professor emeritus in the School of Chemical Engineering at Oklahoma State University, has experience in both industry (13 years) and academia (31 years) and was head of the school for 13 years. Russ is a past president of the American Automatic Control Council, was editor-in-chief of ISA Transactions from 1998 to 2012, and Director of the ISA Automatic Control Systems Division (now Control and Robotics). He is a Fellow of both ISA and AIChE and a Process Automation Hall of Fame inductee. He received the 2009 ISA Distinguished Service Award and the 2013 Fray International Sustainability Award.
Inspired by his industrial experience, his mission has been to bridge the gap between industry and academia. Russ was the codirector of two industrial consortia (one at Texas Tech and a second at Oklahoma State) and built pilot-scale laboratories for dual use in undergraduate education and graduate research. He left industry in 1982 with a vision to use engineers’ process models in control and pursued many aspects of doing so in his academic research career. This book is his collection of practicable methods. His goal is for it to be a useful guide to others seeking to use nonlinear models in control.
His 1968 BS in chemical engineering and subsequent MS in nuclear engineering are both from the University of Maryland. His 1985 PhD in chemical engineering is from North Carolina State University.
He maintains a website (www.r3eda.com) to provide open access to software (including simulators to support this text) and technique monographs.
In "retirement," he offers consulting services related to engineering analysis, and serves on several ISA, American Automatic Control Council (AACC), and International Federation of Automatic Control (IFAC) committees.