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2011 | OriginalPaper | Buchkapitel

3. Nonlinear Model Predictive Control

verfasst von : Lars Grüne, Jürgen Pannek

Erschienen in: Nonlinear Model Predictive Control

Verlag: Springer London

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Abstract

In this chapter, we introduce the nonlinear model predictive control algorithm in a rigorous way. We start by defining a basic NMPC algorithm for constant reference and continue by formalizing state and control constraints. Viability (or weak forward invariance) of the set of state constraints is introduced and the consequences for the admissibility of the NMPC feedback law are discussed. After having introduced NMPC in a special setting, we describe various extensions of the basic algorithm, considering time varying reference solutions, terminal constraints and costs and additional weights. Finally, we investigate the optimal control problem corresponding to this generalized setting and prove several properties, most notably the dynamic programming principle.

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Metadaten
Titel
Nonlinear Model Predictive Control
verfasst von
Lars Grüne
Jürgen Pannek
Copyright-Jahr
2011
Verlag
Springer London
DOI
https://doi.org/10.1007/978-0-85729-501-9_3

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