Nonlinear Model Predictive Control

Theory and Algorithms

  • Lars Grüne
  • Jürgen Pannek
Part of the Communications and Control Engineering book series (CCE)

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Lars Grüne, Jürgen Pannek
    Pages 1-11
  3. Lars Grüne, Jürgen Pannek
    Pages 13-43
  4. Lars Grüne, Jürgen Pannek
    Pages 45-69
  5. Lars Grüne, Jürgen Pannek
    Pages 71-90
  6. Lars Grüne, Jürgen Pannek
    Pages 177-219
  7. Lars Grüne, Jürgen Pannek
    Pages 221-258
  8. Lars Grüne, Jürgen Pannek
    Pages 259-295
  9. Lars Grüne, Jürgen Pannek
    Pages 297-342
  10. Lars Grüne, Jürgen Pannek
    Pages 343-366
  11. Lars Grüne, Jürgen Pannek
    Pages 367-434
  12. Back Matter
    Pages 435-456

About this book

Introduction

This book offers readers a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC schemes with and without stabilizing terminal constraints are detailed, and intuitive examples illustrate the performance of different NMPC variants. NMPC is interpreted as an approximation of infinite-horizon optimal control so that important properties like closed-loop stability, inverse optimality and suboptimality can be derived in a uniform manner. These results are complemented by discussions of feasibility and robustness. 
An introduction to nonlinear optimal control algorithms yields essential insights into how the nonlinear optimization routine—the core of any nonlinear model predictive controller—works. Accompanying software in MATLAB® and C++ (downloadable from extras.springer.com/), together with an explanatory appendix in the book itself, enables readers to perform computer experiments exploring the possibilities and limitations of NMPC.
This book (second edition) has been substantially rewritten, edited and updated to reflect the significant advances that have been made since the publication of its predecessor, including:

• a new chapter on economic NMPC relaxing the assumption that the running cost penalizes the distance to a pre-defined equilibrium;
• a new chapter on distributed NMPC discussing methods which facilitate the control of large-scale systems by splitting up the optimization into smaller subproblems;
• an extended discussion of stability and performance using approximate updates rather than full optimization;
• replacement of the pivotal sufficient condition for stability without stabilizing terminal conditions with a weaker alternative and inclusion of an alternative and much simpler proof in the analysis; and
• further variations and extensions in response to suggestions from readers of the first edition.

Though primarily aimed at academic researchers and practitioners working in control and optimization, the text is self-contained, featuring background material on infinite-horizon optimal control and Lyapunov stability theory that also makes it accessible for graduate students in control engineering and applied mathematics.

Keywords

Feedback Control Model Predictive Control Numerical Methods Optimal Control Nonlinear Systems

Authors and affiliations

  • Lars Grüne
    • 1
  • Jürgen Pannek
    • 2
  1. 1.Mathematisches InstitutUniversität BayreuthBayreuthGermany
  2. 2.Bremer Institut für Produktion und Logistik (BIBA)Universität BremenBremenGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-46024-6
  • Copyright Information Springer International Publishing Switzerland 2017
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-46023-9
  • Online ISBN 978-3-319-46024-6
  • Series Print ISSN 0178-5354
  • Series Online ISSN 2197-7119
  • About this book