文章基本信息

标题：Parallel Explicit MPC for Hardware with Limited Memory
本地全文：下载
作者：Juraj Oravec ; Yuning Jiang ; Boris Houska 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2017
卷号：50
期号：1
页码：3301-3306
DOI：10.1016/j.ifacol.2017.08.506
语种：English
出版社：Elsevier
摘要：AbstractThis paper proposes a real-time model predictive control (MPC) algorithm for problems with convex quadratic objectives, linear dynamic systems, as well as polytopic state-and control constraints. The method features, on the one hand, explicit model predictive control algorithms and parametric optimization, but, on the other hand, also uses ideas from iterative distributed optimization. This leads to an explicit real-time algorithm with constant and verifiable run-time bounds that scale linearly with the prediction horizon length of the MPC problem. Moreover, unlike standard explicit MPC algorithms, the memory requirements of the proposed algorithm do not dependent on the prediction horizon length. The practical advantages of the method are illustrated with a numerical example.
关键词：KeywordsExplicit MPCParametric OptimizationDistributed Optimization