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  • 标题:Towards a modular software package for embedded optimization
  • 本地全文:下载
  • 作者:Robin Verschueren ; Gianluca Frison ; Dimitris Kouzoupis
  • 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
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