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  • 标题:Asymptotically exact direct data-driven multivariable controller tuning
  • 本地全文:下载
  • 作者:Simone Formentin ; Andrea Bisoffi ; Tom Oomen
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2015
  • 卷号:48
  • 期号:28
  • 页码:1349-1354
  • DOI:10.1016/j.ifacol.2015.12.319
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractIn this paper, a data-driven controller design method for multivariable systems is introduced and analyzed. The proposed technique is direct, as it is entirely based on experimental data and does not rely on a physical description of the system, and non-iterative, as it does not require controller adjustments based on additional experiments. Compared to the state-of-theart non-iterative technique, i.e. MIMO VRFT, the proposed approach is asymptotically exact, in that it guarantees that the desired closed-loop dynamics is matched when the number of data tends to infinity. The performance of the proposed approach is illustrated and compared with MIMO VRFT on a benchmark simulation example.
  • 关键词:Keywordsdirect data-driven controlmultivariable systemsconvex optimization
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