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タイトル: A Highly Parallelizable Newton-type Method for Nonlinear Model Predictive Control⁎
著者: Deng, Haoyang
Ohtsuka, Toshiyuki
著者名の別形: 大塚, 敏之
キーワード: Nonlinear model predictive control
parallel algorithm
real-time algorithm
発行日: 2018
出版者: Elsevier B.V.
誌名: IFAC-PapersOnLine
巻: 51
号: 20
開始ページ: 349
終了ページ: 355
抄録: We propose a highly parallelizable Newton-type method for nonlinear model predictive control by exploiting the particular structure of the associated Karush-Kuhn-Tucker conditions. These equations are approximately decoupled into single step subproblems along the prediction horizon for parallelization. The coupling variable of each subproblem is approximated toward its optimal value by a simple but effective method in every iteration. The proposed algorithm is applied to control a quadrotor. The numerical simulation results show that the proposed algorithm is highly parallelizable and converges with only a few iterations even to a high accuracy. The proposed method is also shown to be faster compared with several state-of-the-art algorithms.
記述: 6th IFAC Conference on Nonlinear Model Predictive Control NMPC 2018. Madison, Wisconsin, USA, 19–22 August 2018.
著作権等: © 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ . This is not the published version. Please cite only the published version. この論文は出版社版でありません。引用の際には出版社版をご確認ご利用ください。
URI: http://hdl.handle.net/2433/235489
DOI(出版社版): 10.1016/j.ifacol.2018.11.058
出現コレクション:学術雑誌掲載論文等

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