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2017 | OriginalPaper | Chapter

7. Feasibility and Robustness

Authors : Lars Grüne, Jürgen Pannek

Published in: Nonlinear Model Predictive Control

Publisher: Springer International Publishing

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Abstract

In this chapter we consider two different but related issues. In the first part we discuss the feasibility problem, i.e., that the nominal NMPC closed-loop solutions remain inside a set on which the finite horizon optimal control problems defining the NMPC feedback law are feasible. We formally define the property of recursive feasibility and explain why the assumptions of the previous chapters, i.e., viability of the state constraint set or of the terminal constraint set ensure this property. Then we present two ways to relax the viability assumption on the state constraint set in the case that no terminal constraints are used. After a comparative discussion on NMPC schemes with and without stabilizing terminal conditions, we start with the second part of the chapter in which robustness of the closed loop under additive perturbations and measurement errors is investigated. Here robustness concerns both the feasibility and admissibility as well as the stability of the closed loop. We provide different assumptions and resulting NMPC schemes for which we can rigorously prove such robustness results and also discuss examples which show that in general robustness may fail to hold.

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previous chapter Stability and Suboptimality Without Stabilizing Terminal Conditions
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Appendix
Available only for authorised users
Footnotes
1
In fact, the infeasibility already disappears for \(N=3\) and \(N=4\) but this is not covered by our theorem.
 
2
We only learned about this after the first edition of this book was published.
 
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Metadata
Title
Feasibility and Robustness
Authors
Lars Grüne
Jürgen Pannek
Copyright Year
2017
Book
Nonlinear Model Predictive Control

Print ISBN: 978-3-319-46023-9

Electronic ISBN: 978-3-319-46024-6

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-46024-6_7