Numerical Methods for Solution of the Extended Linear Quadratic Control Problem

John Bagterp Jørgensen, Gianluca Frison, Nicolai Fog Gade-Nielsen, Bernd Dammann

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

In this paper we present the extended linear quadratic control problem, its efficient solution, and a discussion of how it arises in the numerical solution of nonlinear model predictive control problems. The extended linear quadratic control problem is the optimal control problem corresponding to the Karush-Kuhn-Tucker system that constitute the majority of computational work in constrained nonlinear and linear model predictive control problems solved by efficient MPC-tailored interior-point and active-set algorithms. We state various methods of solving the extended linear quadratic control problem and discuss instances in which it arises. The methods discussed in the paper have been implemented in efficient C code for both CPUs and GPUs for a number of test examples.
Original languageEnglish
Title of host publicationNonlinear Model Predictive Control
Volume4
PublisherInternational Federation of Automatic Control
Publication date2012
Pages187-193
ISBN (Print)978-3-902823-07-6
DOIs
Publication statusPublished - 2012
Event4th IFAC Nonlinear Model Predictive Control Conference (NMPC 2012) - Noordwijkerhout, Netherlands
Duration: 23 Aug 201227 Aug 2012
http://www.nmpc12.tue.nl/

Conference

Conference4th IFAC Nonlinear Model Predictive Control Conference (NMPC 2012)
CountryNetherlands
CityNoordwijkerhout
Period23/08/201227/08/2012
Internet address
SeriesIFAC Proceedings Volumes (IFAC-PapersOnline)

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