Introducing the quadratically-constrained quadratic programming framework in HPIPM

descriptionPublicationkeyboard_double_arrow_right Article , Preprint , Conference object , Report 12 Jul 2022Publisher:IEEEJournal:2022 European Control Conference (ECC)Funded by:EC | ELO-X, DFG | Optimization-Based Multis...

Authors: Frison, Gianluca; Frey, Jonathan; Messerer, Florian; Zanelli, Andrea; Diehl, Moritz;

doi: 10.23919/ecc55457.2022.9838499

arXiv: 2112.11872

handle: 20.500.11850/577311

Introducing the quadratically-constrained quadratic programming framework in HPIPM

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Abstract

This paper introduces the quadratically-constrained quadratic programming (QCQP) framework recently added in HPIPM alongside the original quadratic-programming (QP) framework. The aim of the new framework is unchanged, namely providing the building blocks to efficiently and reliably solve (more general classes of) optimal control problems (OCP). The newly introduced QCQP framework provides full features parity with the original QP framework: three types of QCQPs (dense, optimal control and tree-structured optimal control QCQPs) and interior point method (IPM) solvers as well as (partial) condensing and other pre-processing routines. Leveraging the modular structure of HPIPM, the new QCQP framework builds on the QP building blocks and similarly provides fast and reliable IPM solvers.

Comment: 7 pages, 1 figure, submitted to ECC 2022

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Keywords

Mathematics - Optimization and Control, Electrical Engineering and Systems Science - Systems and Control

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