HPIPM: a high-performance quadratic programming framework for model predictive control

2020/03/05 by Gianluca Frison, Moritz Diehl, Frison, Gianluca +1 · 22 citations
Computer Science · Engineering · Mathematics · #Advanced Control Systems Optimization #FOS: Electrical engineering #FOS: Mathematics #Fault Detection and Control Systems #Fuel Cells and Related Materials #Optimization and Control (math.OC) #Systems and Control (eess.SY) #cs.SY #eess.SY #electronic engineering #information engineering #math.OC

paper · pdf · doi:10.48550/arxiv.2003.02547

openalex publication_date 2020/03/05 · arxiv created 2020/06/06 · arxiv updated 2020/06/09 · openalex created_date 2022/07/26 · openalex updated_date 2026/07/28

Abstract

This paper introduces HPIPM, a high-performance framework for quadratic programming (QP), designed to provide building blocks to efficiently and reliably solve model predictive control problems. HPIPM currently supports three QP types, and provides interior point method (IPM) solvers as well (partial) condensing routines. In particular, the IPM for optimal control QPs is intended to supersede the HPMPC solver, and it largely improves robustness while keeping the focus on speed. Numerical experiments show that HPIPM reliably solves challenging QPs, and that it outperforms other state-of-the-art solvers in speed.

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