Process Control is the largest, most important segment of the chemical engineering industry. In the past decade, one of the most important topics within process control engineering has been the control of nonlinear systems. This work provides an introduction to nonlinear process control systems and covers four major topics: nonlinear dynamics; nonlinear identification; nonlinear controller design; and nonlinear state estimation. Case studies are presented to illustrate the controller design procedures. Feedback linearization techniques which yield exact linearization of the closed-loop system are discussed, as well as nonlinear model predictive control strategies.
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Editorial Reviews
From the Publisher
This edition is intended as an introduction to the design, analysis, and application of nonlinear control strategies for process systems.
From the Back Cover
Many common industrial process control problems exhibit nonlinear behavior, and the limitations of traditional linear controllers in managing these processes have become increasingly apparent. Meanwhile, new model-based controller design strategies—coupled with more inexpensive and powerful computer—have made nonlinear process control much more practical. As a result, understanding nonlinear process control has become a high priority in both industry and academia.
Nonlinear Process Control assembles the latest theoretical and practical research on design, analysis and application of nonlinear process control strategies. It presents detailed coverage of all three major elements of nonlinear process control: identification, controller design, and state estimation.
An introductory chapter outlines the issues driving nonlinear process control research, as well as several classic techniques. The book then offers a detailed introduction to nonlinear process modeling, which is central to every nonlinear control strategy.
Once the fundamentals are understood, Nonlinear Process Control covers two leading approaches: input/output linearization and nonlinear predictive control. The book also shows how to design nonlinear state observers that permit control even if on-line measurements of all state variables cannot be obtained.
Finally, the book discusses new techniques for obtaining nonlinear empirical models using artificial neural networks, which are becoming increasingly prevalent in industry.
Nonlinear Process Control reflects the contributions of eleven leading researchers in the field.
It is an ideal textbook for graduate courses in process control, as well as a concise, up-to-date reference for control engineers.
Nonlinear Process Control assembles the latest theoretical and practical research on design, analysis and application of nonlinear process control strategies. It presents detailed coverage of all three major elements of nonlinear process control: identification, controller design, and state estimation.
An introductory chapter outlines the issues driving nonlinear process control research, as well as several classic techniques. The book then offers a detailed introduction to nonlinear process modeling, which is central to every nonlinear control strategy.
Once the fundamentals are understood, Nonlinear Process Control covers two leading approaches: input/output linearization and nonlinear predictive control. The book also shows how to design nonlinear state observers that permit control even if on-line measurements of all state variables cannot be obtained.
Finally, the book discusses new techniques for obtaining nonlinear empirical models using artificial neural networks, which are becoming increasingly prevalent in industry.
Nonlinear Process Control reflects the contributions of eleven leading researchers in the field.
It is an ideal textbook for graduate courses in process control, as well as a concise, up-to-date reference for control engineers.
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0 of 1 people found the following review helpful:
5.0 out of 5 stars
Primer for all things nonlinear...,
By A Customer
This review is from: Nonlinear Process Control (Hardcover)
This is an excelent book for the control engineer looking to learn, or brush up on their nonlinear control knowledge. I found this text to be very useful in understanding nonlinear differential state-space methods. The text convers differential geometric methods for input-output tranformations, NL observers, MPC, and various other topics. Nonlinear Process Control was easy to follow and contains very practical examples to solidify the concepts.
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