This book successfully teaches how to analyze dynamic chemical processes and develop automatic control strategies to operate them safely and economically. Rather than simply present theory topics and develop analytical solutions, this textbook uses "interactive learning" through computer-based simulation exercises, employing for this the very popular "Matlab" engineering software package, and the "Simulink" block-diagram simulation environment. Introductions to both "Matlab" and "Simulink" are included in the book.

Each chapter of the book is followed by a series of "learning modules" that serve several purposes: some focus on software tools, while others focus on particular control problems.

An introduction to process control and instrumentation is presented in chapter 1. The development and use of models is very important in control systems engineering, and fundamentals models are developed in chapter 2, including the steady-state solution and linearization to form steady-state models. Chapter 3 focuses on the dynamic behavior of linear systems, starting with state space models and then covering transfer function-based models in detail. Chapter 4 covers the development of empirical models, including continuous and discrete transfer function models.

Chapter 5 provides a detailed introduction to feedback control, developing the basics of feedback systems, PID controllers, and methods of analyzing closed-loop stability. Chapter 6 presents methods for controller tuning. Frequency response analysis techniques, important for determining control system robustness, are presented in chapter 7.

Model-based control leads to improved control loop performance, and one of the clearest model-based techniques (Internal Model Control o IMC) is presented in chapter 8. The PID controller remains the most widely used controller in industry, so chapter 9 is very valuable since it shows how to convert internal model controllers to classical feedback PID controllers.

Chapter 10 develops two widely used control strategies: Cascade and feed-forward control. Chapter 11 presents auto-tuning and gain scheduling, two methods used to deal with poor performance due to changing operating conditions and poor tuned control loops. The phenomenon of reset windup and the development of anti-reset windup strategies are also presented in this chapter.

Chapter 12 presents the split-range, selective, and override control strategies, which are used when we need the control loop to be able of switching between manipulated inputs or select from several measured outputs. Chapter 13 deals with the effect of control loops interactions, while the design of multivariable controllers is developed in chapter 14.

Chapter 15 presents the challenging tasks encountered when developing Plant-wide optimization and control schemes. Chapter 16 presents the most widely applied advanced control strategy: Model Predictive Control (MPC).

Even though the book is designed for Chemical Engineering students, I truly believe that this text would also be suitable for industrial practitioners and students in mechanical, nuclear, industrial, and electrical engineering. I am an Industrial Practitioner of Process Measurement & Control who has been working in the Process Industries for more than 16 years as an Automation, Instrumentation, Process Safety and Process Control Engineer. My academic background is in electrical and electronics engineering (I am an Electronic Engineer), not in chemical engineering as might be the case of the usual reader of this book, but working in the Oil & Gas Industry all this time, I have been dealing with Chemical-Process Control issues in a day-to-day basics. I found this book to be a very useful reference and refresher to gain a better understanding of Modern Process Control Applications.

If you are a practitioner of Process Control you may want to consider also "Instrument Engineers' Handbook, Fourth Edition, Volume Two: Process Control and optimization" by Bela Liptak, for its practical and comprehensive coverage of Process Control.