Computer Control in the Process Industries

by Brian Roffel, Patrick Chin

Overview

Techniques such as dead time compensation, adaptive control and Kalman filtering have been around for some time, but as yet find little application in industry.

This book tries to promote the use of advanced control techniques by taking the reader from basic theory to practical implementation. It is therefore of interest to practicing control engineers in various types of industries, especially the process industry. Graduate and undergraduate students in control engineering will also find the book extremely useful since many practical details are given which are usually omitted in books on control engineering.

Product Details

ISBN-13:	9781138557901
Publisher:	Taylor & Francis
Publication date:	01/25/2019
Series:	CRC Press Revivals
Pages:	274
Product dimensions:	6.12(w) x 9.19(h) x (d)

About the Author

Brian Roffel is Global Advisor, Advanced Computer Control at Polysar Limited. He holds a M.Eng in chemical engineering and a Ph.D. in process control. He worked as chief senior research officer at the Twente University of Technology, and as a computer applications engineer at Esso Chemical Canada. During 1986-7 he was adjunct professor at the Universities of Western Ontario and Waterloo. He has written many publications on process dynamics and control.

Patrick A. Chin is a Computer Control Specialist at Polysar Limited. He holds a M.Eng. in chemical engineering from McMaster University with a specialization in process control. Previously he worked as a computer applications engineer at Esso Chemical Canada.

Table of Contents

1. Introduction  2. Distributed Computer Control System Networks  3. Computer System Software  4. Computer System Selection  5. Reliability and Security  6. Batch and Continuous Process Control  7. Introduction to Advanced Control 8. Dead Time Compensators  9. Inferential Control and Model Identification  10. Feed-Forward Control  11. Interaction and Decoupling  12. Constraint Control  13. Design, Adjustment and Application  14. Optimization  15. Self Tuning and Adaptive Controllers  16. State Observers  17. Kalman Filtering