ABSTRACT

Introduction to Process Control, Third Edition continues to provide a bridge between traditional and modern views of process control by blending conventional topics with a broader perspective of integrated process operation, control, and information systems. Updated and expanded throughout, this third edition addresses issues highly relevant to today’s teaching of process control:

  • Discusses smart manufacturing, new data preprocessing techniques, and machine learning and artificial intelligence concepts that are part of current smart manufacturing decisions
  • Includes extensive references to guide the reader to the resources needed to solve modeling, classification, and monitoring problems
  • Introduces the link between process optimization and process control (optimizing control), including the effect of disturbances on the optimal plant operation, the concepts of steady-state and dynamic back-off as ways to quantify the economic benefits of control, and how to determine an optimal transition policy during a planned production change
  • Incorporates an introduction to the modern architectures of industrial computer control systems with real case studies and applications to pilot-scale operations
  • Analyzes the expanded role of process control in modern manufacturing, including model-centric technologies and integrated control systems
  • Integrates data processing/reconciliation and intelligent monitoring in the overall control system architecture

 

Drawing on the authors’ combined 60 years of teaching experiences, this classroom-tested text is designed for chemical engineering students but is also suitable for industrial practitioners who need to understand key concepts of process control and how to implement them. The text offers a comprehensive pedagogical approach to reinforce learning and presents a concept first followed by an example, allowing students to grasp theoretical concepts in a practical manner and uses the same problem in each chapter, culminating in a complete control design strategy. A vast number of exercises throughout ensure readers are supported in their learning and comprehension.

 

Downloadable MATLAB® toolboxes for process control education as well as the main simulation examples from the book offer a user-friendly software environment for interactively studying the examples in the text. These can be downloaded from the publisher’s website. Solutions manual is available for qualifying professors from the publisher.

part I|44 pages

Introduction

chapter 21|12 pages

Why Process Control?

chapter 2|16 pages

Definitions and Terminology

part I|14 pages

Summary

part II|110 pages

Modeling for Control

chapter 463|16 pages

Basic Concepts in Modeling

chapter 6|24 pages

Models from Process Data

part II|14 pages

Summary

part III|78 pages

Process Analysis

chapter 1567|16 pages

Stability

chapter 8|28 pages

Dynamic Performance

chapter 9|22 pages

Frequency Response

part III|10 pages

Summary

part IV|88 pages

Feedback Control

chapter 23410|26 pages

Basic Elements of Feedback Control

chapter 11|22 pages

Stability Analysis of Closed-Loop Processes

chapter 12|30 pages

Feedback Control Design

part IV|8 pages

Summary

part V|60 pages

Model-Based Control

chapter 32213|32 pages

Model-Based Control

chapter 14|20 pages

Model Predictive Control

part V|6 pages

Summary

part VI|104 pages

Multivariable Control

chapter 38215|20 pages

Multivariable Systems: Special Cases

chapter 16|28 pages

Multivariable Systems

chapter 17|20 pages

Interaction and Structural Analysis

chapter 18|24 pages

Design of Multivariable Controllers

part VI|10 pages

Summary

part VII|152 pages

Control in Modern Manufacturing

chapter 48619|24 pages

Practical Control of Nonlinear Processes

chapter 20|30 pages

Process Optimization and Control

chapter 22|28 pages

Data Processing and Reconciliation

chapter 23|36 pages

Process Monitoring

part VII|10 pages

Summary