A Family of High-Performance Solvers for Linear Model Predictive Control

Publication: Research - peer-reviewArticle in proceedings – Annual report year: 2014

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In Model Predictive Control (MPC), an optimization problem has to be solved at each sampling time, and this has traditionally limited the use of MPC to systems with slow dynamic. In this paper, we propose an e_cient solution strategy for the unconstrained sub-problems that give the search-direction in Interior-Point (IP) methods for MPC, and that usually are the computational bottle-neck. This strategy combines a Riccati-like solver with the use of high-performance computing techniques: in particular, in this paper we explore the performance boost given by the use of single precision computation, and techniques such as inexact search direction and mixed precision computation. Finally, we test our HPMPC toolbox, a family of high-performance solvers tailored for MPC and implemented using these techniques, that is shown to be several times faster than current state-of-the-art solvers for linear MPC.
Original languageEnglish
Title of host publicationProceedings of the 19th IFAC World Congress 2014
Volume19
PublisherInternational Federation of Automatic Control
Publication date2014
Pages3074-3079
DOIs
StatePublished - 2014
Event19th World Congress of the International Federation of Automatic Control (IFAC 2014) - Cape Town, South Africa

Conference

Conference19th World Congress of the International Federation of Automatic Control (IFAC 2014)
CountrySouth Africa
CityCape Town
Period24/08/201429/08/2014
OtherThe theme of the congress: “Promoting automatic control for the benefit of humankind”
Internet address
SeriesI F A C Workshop Series
Number1
Volume19
ISSN1474-6670
CitationsWeb of Science® Times Cited: No match on DOI
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