A Dual Active-Set Solver for Embedded Quadratic Programming Using Recursive LDLT Updates

• 成果类型: Article
• 署名作者: Arnstrom, Daniel; Bemporad, Alberto; Axehill, Daniel
• 署名单位: Linkoping University; IMT School for Advanced Studies Lucca
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2022.3176430
• 发表日期: 2022
• 页码: 4362-4369
• 关键词: Embedded optimization; model predictive control; (MPC); quadratic programming (QP)

摘要

In this technical article, we present a dual active-set solver for quadratic programming that has properties suitable for use in embedded model predictive control applications. In particular, the solver is efficient, can easily be warm started, and is simple to code. Moreover, the exact worst-case computational complexity of the solver can be determined offline and, by using outer proximal-point iterations, ill-conditioned problems can be handled in a robust manner.