Model Predictive Control: Theory and Design
Contributed by: James B. Rawlings, [log in to unmask]
Nob Hill Publishing is pleased to announce the availability of
the textbook "Model Predictive Control: Theory and Design," by
James B. Rawlings, University of Wisconsin-Madison, and David
Q. Mayne, Imperial College, London. This text provides a
comprehensive and foundational treatment of the theory and design
of model predictive control. It enables researchers to learn
and teach the fundamentals of MPC without continually searching
the diverse control research literature for omitted arguments and
requisite background material. More than 200 end-of-chapter
exercises support the teaching and learning of MPC.
A solution manual for end-of-chapter exercises is available to
course instructors who adopt the text.
Appendices A-C are available on the web.
Sample homeworks and exams for a one-semester graduate course
are available at: www.che.wisc.edu/~jbraw/mpc.
Order electronically here:
Table of Contents
1. Getting Started with Model Predictive Control
2. Model Predictive Control - Regulation
3. Robust Model Predictive Control
4. State Estimation
5. Output Model Predictive Control
6. Distributed Model Predictive Control
7. Explicit Control Laws for Constrained Linear Systems
A. Mathematical Background
B. Stability Theory
The authors received the 2011 inaugural IFAC High Impact Paper award
for an MPC review paper that preceded the text. The text was also
recognized in the 2011 Ragazzini (Education) Award of the American
Automatic Control Council. This book has been adopted for graduate
courses at nine universities in six countries.