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  • 标题:Data-driven analysis and control of continuous-time systems under aperiodic sampling ⁎
  • 本地全文:下载
  • 作者:Julian Berberich ; Stefan Wildhagen ; Michael Hertneck
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2021
  • 卷号:54
  • 期号:7
  • 页码:210-215
  • DOI:10.1016/j.ifacol.2021.08.360
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractWe investigate stability analysis and controller design of unknown continuous-time systems under state-feedback with aperiodic sampling, using only noisy data but no model knowledge. We first derive a novel data-dependent parametrization of all linear time-invariant continuous-time systems which are consistent with the measured data and the assumed noise bound. Based on this parametrization and by combining tools from robust control theory and the time-delay approach to sampled-data control, we compute lower bounds on the maximum sampling interval (MSI) for closed-loop stability under a given state-feedback gain, and beyond that, we design controllers which exhibit a possibly large MSI. Our methods guarantee the stability properties robustly for all systems consistent with the measured data. As a technical contribution, the proposed approach embeds existing methods for sampled-data control into a general robust control framework, which can be directly extended to model-based robust controller design for uncertain time-delay systems under general uncertainty descriptions.
  • 关键词:KeywordsData-driven controlcontinuous time system estimation
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