ALPAQA: A matrix-free solver for nonlinear MPC and large-scale nonconvex optimization

被引：0
|
作者：
Pas, Pieter [1 ]
Schuurmans, Mathijs [1 ]
Patrinos, Panagiotis [1 ]
机构：
[1] Katholieke Univ Leuven, Dept Elect Engn ESAT STADIUS, Kasteelpk Arenberg 10, B-3001 Leuven, Belgium
来源：
2022 EUROPEAN CONTROL CONFERENCE (ECC) | 2022年
基金：
欧盟地平线“2020”;
关键词：
CODE;
D O I：
10.23919/ecc55457.2022.9838172
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents ALPAQA, an open-source C++ implementation of an augmented Lagrangian method for nonconvex constrained numerical optimization, using the first-order PANOC algorithm as inner solver. The implementation is packaged as an easy-to-use library that can be used in C++ and Python. Furthermore, two improvements to the PANOC algorithm are proposed and their effectiveness is demonstrated in NMPC applications and on the CUTEst benchmarks for numerical optimization.
引用
收藏
页码：417 / 422
页数：6
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