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Feasibility and Robustness

  • Chapter
Nonlinear Model Predictive Control

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

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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 constraints, 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 feasibility and admissibility as well as 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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Notes

  1. 1.

    In fact, the infeasibility already disappears forN=3 andN=4 but this is not covered by our theorem.

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    Authors
    1. Lars Grüne
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    2. Jürgen Pannek
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    Correspondence to Lars Grüne .

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    © 2011 Springer-Verlag London Limited

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    Grüne, L., Pannek, J. (2011). Feasibility and Robustness. In: Nonlinear Model Predictive Control. Communications and Control Engineering. Springer, London. https://doi.org/10.1007/978-0-85729-501-9_8

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    • DOI: https://doi.org/10.1007/978-0-85729-501-9_8

    • Publisher Name: Springer, London

    • Print ISBN: 978-0-85729-500-2

    • Online ISBN: 978-0-85729-501-9

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