文章基本信息

标题：Towards a modular software package for embedded optimization
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作者：Robin Verschueren ; Gianluca Frison ; Dimitris Kouzoupis 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2018
卷号：51
期号：20
页码：374-380
DOI：10.1016/j.ifacol.2018.11.062
语种：English
出版社：Elsevier
摘要：AbstractIn this paper we present acados, a new software package for model predictive control. It provides a collection of embedded optimization algorithms written in C, with a strong focus on computational efficiency. Its modular structure makes it useful for rapid prototyping, i.e. designing a control algorithm by putting together different algorithmic components that are readily connected and interchanged. The usefulness of the software is demonstrated with a closed-loop simulation experiment of an inverted pendulum, which shows acados attaining sub-millisecond computation times per iteration. Furthermore, we showcase a new algorithmic idea in the context of embedded nonlinear model predictive control (NMPC), namely sequential convex quadratic programming (SCQP), along with an efficient implementation of it.
关键词：KeywordsNonlinear Model Predictive ControlEmbedded OptimizationSoftware