文章基本信息

标题：Preconditioned Krylov iterations and condensing in interior point MPC method
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作者：Alexander Malyshev ; Rien Quirynen ; Andrew Knyazev 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：388-393
DOI：10.1016/j.ifacol.2018.11.064
语种：English
出版社：Elsevier
摘要：AbstractWe investigate using Krylov subspace iterative methods in model predictive control (MPC), where the prediction model is given by linear or linearized systems with linear inequality constraints on the state and the input, and the performance index is quadratic. The inequality constraints are treated by the primal-dual interior point method. We indicate condition numbers of several linear systems, which determine the search direction in the Newton method, and propose a new preconditioner for one of the systems. Numerical results illustrate convergence of Krylov methods with and without preconditioning and demonstrate that our preconditioning reduces the number of Krylov iterations 2–10 times.
关键词：KeywordsModel predictive controlPreconditioningNumerical algorithms