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  • 标题:Feedback control of social distancing for COVID-19 via elementary formulae
  • 本地全文:下载
  • 作者:Michel Fliess ; Cédric Join ; Alberto d'Onofrio
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2022
  • 卷号:55
  • 期号:20
  • 页码:439-444
  • DOI:10.1016/j.ifacol.2022.09.134
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractSocial distancing has been enacted in order to mitigate the spread of COVID-19. Like many authors, we adopt the classic epidemic SIR model, where the infection rate is the control variable. Its differential flatness property yields elementary closed-form formulae for open-loop social distancing scenarios, where, for instance, the increase of the number of uninfected people may be taken into account. Those formulae might therefore be useful to decision makers. A feedback loop stemming from model-free control leads to a remarkable robustness with respect to severe uncertainties and mismatches. Although an identification procedure is presented, a good knowledge of the recovery rate is not necessary for our control strategy.
  • 关键词:KeywordsBiomedical controlCOVID-19social distancingSIR modelflatness-based controlmodel-free controlrobustnessidentifiabilityalgebraic differentiator
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