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ファイル | 記述 | サイズ | フォーマット | |
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j.ifacol.2018.11.058.pdf | 550.7 kB | Adobe PDF | 見る/開く |
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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