From Plant Data to Process Control: Ideas for Process Identification and PID Design

by Liuping Wang

Overview

Process engineering spans industrial applications in the manufacturing sector from petrochemical to polymer to mineral production. From Plant Data to Process Control covers the most up-to-date techniques and algorithms in the area of process identification (PID) and process control, two key components of process engineering, essential for optimizing production systems. It examines both the theoretical advances in process design and control theory, and a wide variety of implementations. A wide variety of approaches are presented for building models of dynamical systems based on observed data (process identification) and for making the output of a system behave in a desired fashion by properly selecting the process input (process control).

Product Details

ISBN-13:	9780748407019
Publisher:	Taylor & Francis
Publication date:	08/31/2000
Series:	Taylor and Francis Series , #11
Edition description:	New Edition
Pages:	240
Product dimensions:	6.88(w) x 9.69(h) x (d)

About the Author

Wang, Liuping

Table of Contents

1. Introduction 2. Modelling from Noisy Step Response Data Using Laguerre Fuctions 3. Least Squares and the PRESS Statistic using Orthogonal Decomposition 4. Frequency Sampling Filters in Process Identification 5. From FSF Models to Step Response Models 6. New Frequency Domain PID Controller Design Method 7. Tuning Rules for PID Controllers 8. Recursive Estimation from Relay Feedback Experiments; Bibliography; Index

What People are Saying About This

From the Publisher

"The book provides a useful reference for engineers and researchers working in the fields of system identification and control." The International Journal of Advanced Manufacturing Technology

Editorial Reviews

"The book provides a useful reference for engineers and researchers working in the fields of system identification and control." The International Journal of Advanced Manufacturing Technology

From the Publisher