© 2011

Nonlinear Model Predictive Control

Theory and Algorithms


Part of the Communications and Control Engineering book series (CCE)

Table of contents

  1. Front Matter
    Pages I-XI
  2. Lars Grüne, Jürgen Pannek
    Pages 1-11
  3. Lars Grüne, Jürgen Pannek
    Pages 13-41
  4. Lars Grüne, Jürgen Pannek
    Pages 43-66
  5. Lars Grüne, Jürgen Pannek
    Pages 67-85
  6. Lars Grüne, Jürgen Pannek
    Pages 87-112
  7. Lars Grüne, Jürgen Pannek
    Pages 113-163
  8. Lars Grüne, Jürgen Pannek
    Pages 165-210
  9. Lars Grüne, Jürgen Pannek
    Pages 211-250
  10. Lars Grüne, Jürgen Pannek
    Pages 251-273
  11. Lars Grüne, Jürgen Pannek
    Pages 275-339
  12. Back Matter
    Pages 341-359

About this book


Nonlinear model predictive control (NMPC) is widely used in the process and chemical industries and increasingly for applications, such as those in the automotive industry, which use higher data sampling rates.

Nonlinear Model Predictive Control is a thorough and rigorous introduction to NMPC for discrete-time and sampled-data systems. 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. NMPC schemes with and without stabilizing terminal constraints are detailed and intuitive examples illustrate the performance of different NMPC variants. An introduction to nonlinear optimal control algorithms gives insight into how the nonlinear optimisation routine – the core of any NMPC controller – works. An appendix covering NMPC software and accompanying software in MATLAB® and C++(downloadable from ) enables readers to perform computer experiments exploring the possibilities and limitations of NMPC.

Nonlinear Model Predictive Control is primarily aimed at academic researchers and practitioners working in control and optimisation but the text is self-contained featuring background material on infinite-horizon optimal control and Lyapunov stability theory which makes the book accessible to graduate students of control engineering and applied mathematics..


Control Control Applications Control Engineering Control Theory Feedback Control Model Predictive Control Nonlinear Control Numerical Methods OJ0061 Optimal Control

Authors and affiliations

  1. 1.Mathematisches InstitutUniversität BayreuthBayreuthGermany
  2. 2.Mathematisches InstitutUniversität BayreuthBayreuthGermany

Bibliographic information

Industry Sectors
Chemical Manufacturing
IT & Software
Materials & Steel
Oil, Gas & Geosciences


“The book provides an excellent and extensive treatment of NMPC from a careful introduction to the underlying theory to advanced results. It can be used for independent reading by applied mathematicians, control theoreticians and engineers who desire a rigorous introduction into the NMPC theory. It can also be used as a textbook for a graduate-level university course in NMPC.” (Ilya Kolmanovsky, Mathematical Reviews, April, 2015)

“In the monograph nonlinear, discrete-time, finite-dimensional control systems with constant parameters are considered. … Each chapter of the monograph contains many numerical examples which illustrate the theoretical considerations, several possible extensions and open problems. Moreover, relationships to results on predictive control published in the literature are pointed out.” (Jerzy Klamka, Zentralblatt MATH, Vol. 1220, 2011)