In Advanced Control Foundation: Tools, Techniques, and Applications, the authors address key concepts and terminology needed to apply advanced control techniques in the process industry. This book targets process or control engineers who are familiar with traditional control but have limited or no experience in designing, installing, commissioning and maintaining advanced control systems. Each chapter aims to help readers quickly understand the technology and its applications. Examples illustrate what's needed for specific use cases, and a dedicated section in each chapter offers a more detailed discussion for those interested in the mathematical basis behind the technology. A workshop is included at the end of each chapter to deepen the reader's understanding of the technology. The workshop solutions are available at the website URL provided in the book. This book provides comprehensive coverage of the key advanced control techniques most commonly used in the process industry. It includes tools for monitoring control system performance, on-demand and adaptive tuning methods, model predictive control, linear programming (LP) optimization, data analytics for batch and continuous processes, fuzzy logic control, neural networks and advancements in proportional–integral–derivative (PID) control for use with wireless measurements. Because many readers may work with existing distributed control systems (DCSs) that do not support advanced control, a chapter of this book is dedicated to tools and techniques that the authors have found useful in integrating advanced control tools into an existing control system. Additionally, one chapter of the book discusses how dynamic process simulations can be easily created in a DCS to support checkout and operator training in the use of advanced control.
