文章基本信息

标题：Quasi-Newton Jacobian and Hessian Updates for Pseudospectral based NMPC
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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