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  • 标题:On the Implementation of a Preconditioned Riccati Recursion based Primal-Dual Interior-Point Algorithm for Input Constrained Optimal Control Problems ⋆
  • 本地全文:下载
  • 作者:Morten Ryberg Wahlgreen ; John Bagterp Jørgensen
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2022
  • 卷号:55
  • 期号:7
  • 页码:346-351
  • DOI:10.1016/j.ifacol.2022.07.468
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractWe present a preconditioned interior-point algorithm tailored for input constrained quadratic programmings (QPs) arising in optimal control problems (OCPs). The implicit approach to OCPs results in large sparse QPs, which we utilized by a tailored Riccati recursion algorithm. The Riccati recursion algorithm requires the solution of a set of small dense linear sub-systems of equations. The proposed preconditioner is an easily invertible diagonal matrix, which we apply in every linear sub-system of equations. We solve a target tracking OCP for a linearized modified quadruple tank system in Matlab. The computational results indicate that ill-conditioning in the sub-systems are reduced and that the additional CPU time for preconditioning is negligible. Additionally, the paper presents a detailed description of the proposed algorithm and serves as an implementation guide for the algorithm.
  • 关键词:KeywordsInterior-point methodQuadratic programmingOptimal Control ProblemRiccati recursionPreconditioning
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