Model Predictive Control in the Process Industry

✍ Scribed by Eduardo Fernandez-Camacho, Carlos Bordons-Alba (auth.)

• Publisher: Springer-Verlag London
• Year: 1995
• Tongue: English
• Leaves: 249
• Series: Advances in Industrial Control
• Edition: 1
• Category: Library

✦ Synopsis

Model Predictive Control is an important technique used in the process control industries. It has developed considerably in the last few years, because it is the most general way of posing the process control problem in the time domain. The Model Predictive Control formulation integrates optimal control, stochastic control, control of processes with dead time, multivariable control and future references. The finite control horizon makes it possible to handle constraints and non linear processes in general which are frequently found in industry. Focusing on implementation issues for Model Predictive Controllers in industry, it fills the gap between the empirical way practitioners use control algorithms and the sometimes abstractly formulated techniques developed by researchers. The text is firmly based on material from lectures given to senior undergraduate and graduate students and articles written by the authors.

✦ Table of Contents

Front Matter....Pages i-xviii
Introduction to Model Based Predictive Control....Pages 1-8
Model Based Predictive Controllers....Pages 9-37
Simple Implementation of GPC for Industrial Processes....Pages 39-67
Robustness Analysis in Precomputed GPC....Pages 69-103
Multivariable GPC....Pages 105-128
Constrained MPC....Pages 129-154
Robust MPC....Pages 155-170
Applications....Pages 171-195
Back Matter....Pages 197-239

✦ Subjects

Control; Software Engineering/Programming and Operating Systems