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  • 标题:Quasi-Newton Jacobian and Hessian Updates for Pseudospectral based NMPC
  • 本地全文:下载
  • 作者:Pedro Hespanhol ; Rien Quirynen
  • 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:22-27
  • DOI:10.1016/j.ifacol.2018.10.169
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractPseudospectral and collocation methods form a popular direct approach to solving continuous-time optimal control problems. Lifted Newton-type algorithms have been proposed as a computationally efficient way to implement online pseudospectral methods for nonlinear model predictive control (NMPC). The present paper extends this work based on a rank-one Jacobian update formula for the nonlinear system dynamics. In addition, we describe an algorithm implementation where this rank-one Jacobian update can be used directly to compute a low-rank update to the condensed Hessian, resulting in an overall quadratic computational complexity for each iteration. A preliminary C code implementation is shown to allow considerable numerical speedups for the optimal control case study of the nonlinear chain of masses.
  • 关键词:KeywordsNonlinear predictive controlquasi-Newton methodsOptimal control
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