Configuration-Constrained Tube MPC

This paper is about robust Model Predictive Control (MPC) for linear systems with additive and multiplicative uncertainty. A novel class of configuration-constrained polytopic robust forward invariant tubes is introduced, which admit a joint parameterization of their facets and vertices. They are th...

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Bibliographic Details
Published inAutomatica (Oxford) Vol. 163; p. 111543
Main Authors Villanueva, Mario Eduardo, Müller, Matthias A., Houska, Boris
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.05.2024
Subjects
Convex optimization
Model Predictive Control
Robust control
Robust control
Convex optimization
Model Predictive Control
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Summary:This paper is about robust Model Predictive Control (MPC) for linear systems with additive and multiplicative uncertainty. A novel class of configuration-constrained polytopic robust forward invariant tubes is introduced, which admit a joint parameterization of their facets and vertices. They are the foundation for the development of novel Configuration-Constrained Tube MPC (CCTMPC) controllers that freely optimize the shape of their polytopic tube, subject to conic vertex configuration constraints, as well as associated vertex control laws by solving convex optimization problems online. It is shown that CCTMPC is—under appropriate assumptions—systematically less conservative than Rigid- and Homothetic- Tube MPC. Additionally, it is proven that there exist control systems for which CCTMPC is less conservative than Elastic Tube MPC, Disturbance Affine Feedback MPC, and Fully Parameterized Tube MPC.
ISSN:0005-1098
1873-2836
DOI:10.1016/j.automatica.2024.111543