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  • 标题:Discrete time derivation of the Robust Fixed-Point Transformation method
  • 本地全文:下载
  • 作者:Bence Géza Czakó ; Dániel András Drexler ; Levente Kovács
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2022
  • 卷号:55
  • 期号:1
  • 页码:535-540
  • DOI:10.1016/j.ifacol.2022.04.088
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractDerivation of the Robust Fixed Point Transformations based method is presented in both continuous and discrete time. Foundations of the method are built on the theory of the Input-Output linearization principle. The robustness of the controller is achieved by using fixed-point iterations on the difference between the inverse model and the true structure of the system. Technical details of the method including the deform function and parameter tuning are also discussed. The theory is illustrated with the application of the controller on a tumor growth model.
  • 关键词:KeywordsNonlinear controlRobust fixed point transformationsInput Output linearizationRobust controlTumor growth modelPhysiological control
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