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MPC
2015
Springer

A parallel quadratic programming method for dynamic optimization problems

4 years 10 months ago
A parallel quadratic programming method for dynamic optimization problems
Quadratic programming problems (QPs) that arise from dynamic optimization problems typically exhibit a very particular structure. We address the ubiquitous case where these QPs are strictly convex and propose a dual Newton strategy that exploits the block-bandedness similarly to an interior-point method. Still, the proposed method features warmstarting capabilities of active-set methods. We give details for an efficient implementation, including tailored numerical linear algebra, step size computation, parallelization, and infeasibility handling. We prove convergence of the algorithm for the considered problem class. A numerical study based on the open-source implementation qpDUNES shows that the algorithm outperforms both wellestablished general purpose QP solvers as well as state-of-the-art tailored control QP solvers significantly on the considered benchmark problems.
Janick V. Frasch, Sebastian Sager, Moritz Diehl
Added 15 Apr 2016
Updated 15 Apr 2016
Type Journal
Year 2015
Where MPC
Authors Janick V. Frasch, Sebastian Sager, Moritz Diehl
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