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The Essentials of Model Predictive Control Read chapter Read first chapter

2019 | OriginalPaper | Chapter

Real-Time Implementation of Explicit Model Predictive Control

Authors : Michal Kvasnica, Colin N. Jones, Ivan Pejcic, Juraj Holaza, Milan Korda, Peter Bakaráč

Published in: Handbook of Model Predictive Control

Publisher: Springer International Publishing

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Abstract

This chapter explains the synthesis of explicit MPC feedback laws that allow for real-time implementation on hardware with limited computational and storage properties. Four methods are introduced. The first one replaces the potentially complex explicit MPC controller by a simpler feedback law by exploiting the geometry of explicit solutions. The second method reduces the storage footprint of explicit MPC by a complete elimination of critical regions, replaced by a direct evaluation of optimality conditions. The common denominator of both methods is that they preserve optimality while considerably reducing the complexity. The third method trades lower complexity for suboptimality while simultaneously minimizing the performance loss. Finally, a method for designing stabilizing explicit MPC controllers for control of nonlinear systems is introduced.

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previous chapter Explicit (Offline) Optimization for MPC
next chapter Robust Optimization for MPC
Footnotes
1
If \(G_{\mathcal{A}}\) does not have a full row rank, it is always possible to identify a subset of \(\mathcal{A}\) such that all rows of \(G_{\mathcal{A}}\) are linearly independent, see, e.g., [37].
 
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Metadata
Title
Real-Time Implementation of Explicit Model Predictive Control
Authors
Michal Kvasnica
Colin N. Jones
Ivan Pejcic
Juraj Holaza
Milan Korda
Peter Bakaráč
Copyright Year
2019
Book
Handbook of Model Predictive Control

Print ISBN: 978-3-319-77488-6

Electronic ISBN: 978-3-319-77489-3

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-319-77489-3_17