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  • 标题:A Markov Chain Approach to Compute the ℓ 2-gain of Nonlinear Systems ⁎
  • 本地全文:下载
  • 作者:Matias I. Müller ; Cristian R. Rojas
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2018
  • 卷号:51
  • 期号:15
  • 页码:84-89
  • DOI:10.1016/j.ifacol.2018.09.095
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractIn this work the problem of computing the maximum gain of non-linear systems, also known as itsℓ2-gain, from input-output data is studied. From an input design perspective, this problem reduces to find an optimal input sequence, of bounded norm, maximizing the norm gain of the output, where our target estimation corresponds to the ratio of these quantities. The novelty of this approach lies on the fact that the input signal is a realization of a stationary process with finite memory whose range is a finite set of values. Based on recent developents on input design for nonlinear systems, our approach leads to a linear program whose optimal cost gives an approximation of theℓ2-gain of the system. An illustrative example shows how well the algorithm performs compared to other methods approximating this quantity.
  • 关键词:Keywordsℓ2-gainInputexcitation designnon-linear system identificationidentification for control
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