Nonlinear Model Predictive Control

Towards New Challenging Applications

  • Lalo Magni
  • Davide Martino Raimondo
  • Frank Allgöwer

Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 384)

Table of contents

  1. Front Matter
  2. Stability and Robusteness

    1. D. Limon, T. Alamo, D. M. Raimondo, D. Muñoz de la Peña, J. M. Bravo, A. Ferramosca et al.
      Pages 1-26
    2. M. Lazar, W. P. M. H. Heemels, A. Jokic
      Pages 27-40
    3. Darryl DeHaan, Martin Guay, Veronica Adetola
      Pages 55-67
    4. Shuyou Yu, Hong Chen, Christoph Böhm, Frank Allgöwer
      Pages 69-78
    5. Keunmo Kang, Robert R. Bitmead
      Pages 79-87
    6. M. Lazar, W. P. M. H. Heemels, D. Muñoz de la Peña, T. Alamo
      Pages 89-98
    7. Christoph Böhm, Tobias Raff, Marcus Reble, Frank Allgöwer
      Pages 99-108
    8. Benjamin Kern, Christoph Böhm, Rolf Findeisen, Frank Allgöwer
      Pages 109-117
  3. Control of Complex Systems

    1. James B. Rawlings, Rishi Amrit
      Pages 119-138
    2. Bruno Picasso, Carlo Romani, Riccardo Scattolini
      Pages 139-152
    3. Matthew Kuure-Kinsey, B. Wayne Bequette
      Pages 153-165
    4. Jinfeng Liu, David Muñoz de la Peña, Panagiotis D. Christofides
      Pages 181-194
    5. Daniel E. Quevedo, Anders Ahlén, Graham C. Goodwin
      Pages 215-224
    6. Rob Gielen, Sorin Olaru, Mircea Lazar
      Pages 225-233
  4. Stochastic Systems

    1. Graham C. Goodwin, Jan Østergaard, Daniel E. Quevedo, Arie Feuer
      Pages 235-248

About this book


Over the past few years significant progress has been achieved in the field of nonlinear model predictive control (NMPC), also referred to as receding horizon control or moving horizon control. More than 250 papers have been published in 2006 in ISI Journals. With this book we want to bring together the contributions of a diverse group of internationally well recognized researchers and industrial practitioners, to critically assess the current status of the NMPC field and to discuss future directions and needs. The book consists of selected papers presented at the International Workshop on Assessment an Future Directions of Nonlinear Model Predictive Control that took place from September 5 to 9, 2008, in Pavia, Italy.


Nonlinear Model Predictive Control Nonlinear Receding Horizon Control Process Control algorithms linear optimization nonlinear optimization optimization

Editors and affiliations

  • Lalo Magni
    • 1
  • Davide Martino Raimondo
    • 2
  • Frank Allgöwer
    • 3
  1. 1.Dipartimento di Informatica e SistemisticaUniversita’ di PaviaItaly
  2. 2.Automatic Control LaboratoryETH Zurich ZürichSwitzerland
  3. 3.Institute for Systems Theory and Automatic ControlUniversity of StuttgartStuttgartGermany

Bibliographic information

  • DOI
  • Copyright Information Springer Berlin Heidelberg 2009
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-642-01093-4
  • Online ISBN 978-3-642-01094-1
  • Series Print ISSN 0170-8643
  • Series Online ISSN 1610-7411
  • About this book