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Model Predictive control

  • E. F. Camacho
  • C. Bordons

Table of contents

  1. Front Matter
    Pages i-xxii
  2. E. F. Camacho, C. Bordons
    Pages 1-11
  3. E. F. Camacho, C. Bordons
    Pages 13-30
  4. E. F. Camacho, C. Bordons
    Pages 31-46
  5. E. F. Camacho, C. Bordons
    Pages 47-79
  6. E. F. Camacho, C. Bordons
    Pages 81-126
  7. E. F. Camacho, C. Bordons
    Pages 127-176
  8. E. F. Camacho, C. Bordons
    Pages 177-216
  9. E. F. Camacho, C. Bordons
    Pages 217-248
  10. E. F. Camacho, C. Bordons
    Pages 249-288
  11. E. F. Camacho, C. Bordons
    Pages 289-310
  12. E. F. Camacho, C. Bordons
    Pages 311-336
  13. E. F. Camacho, C. Bordons
    Pages 337-380
  14. Back Matter
    Pages 381-405

About this book

Introduction

From power plants to sugar refining, model predictive control (MPC) schemes have established themselves as the preferred control strategies for a wide variety of processes.

The second edition of Model Predictive Control provides a thorough introduction to theoretical and practical aspects of the most commonly used MPC strategies. It bridges the gap between the powerful but often abstract techniques of control researchers and the more empirical approach of practitioners. Model Predictive Control demonstrates that a powerful technique does not always require complex control algorithms.

The text features material on the following subjects:

  • general MPC elements and algorithms;
  • commercial MPC schemes;
  • generalized predictive control
  • multivariable, robust, constrained nonlinear and hybrid MPC;
  • fast methods for MPC implementation;
  • applications.

All of the material is thoroughly updated for the second edition with the chapters on nonlinear MPC, MPC and hybrid systems and MPC implementation being entirely new. Many new exercises and examples have also have also been added throughout and MATLAB® programs to aid in their solution can be downloaded from extras.springer.com. The text is an excellent aid for graduate and advanced undergraduate students and will also be of use to researchers and industrial practitioners wishing to keep abreast of a fast-moving field.

Keywords

Constraint Control Engineering Industrial Application Model Predictive Control Modelling Optimal control Robustness TB Adopted algorithms optimization robot

Authors and affiliations

  • E. F. Camacho
    • 1
  • C. Bordons
    • 1
  1. 1.Escuela Superior de IngenierosUniversidad de SevillaSevillaSpain

Bibliographic information

  • DOI https://doi.org/10.1007/978-0-85729-398-5
  • Copyright Information Springer-Verlag London Limited 2007
  • Publisher Name Springer, London
  • eBook Packages Engineering
  • Print ISBN 978-1-85233-694-3
  • Online ISBN 978-0-85729-398-5
  • Series Print ISSN 1439-2232
  • Buy this book on publisher's site
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