文章基本信息

标题：Extremum seeking based on a Hammerstein-Wiener representation
本地全文：下载
作者：Christian G. Feudjio Letchindjio ; Jean-Sebastien Deschenes ; Laurent Dewasme 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2018
卷号：51
期号：18
页码：744-749
DOI：10.1016/j.ifacol.2018.09.274
语种：English
出版社：Elsevier
摘要：AbstractThis study is concerned with the development of an extremum seeking (ES) strategy based on recursive least square (RLS) for on-line estimation, and a regression model in the form of a Hammerstein-Wiener model. RLS usually provides a faster convergence than the classical bank of filter estimators, and the consideration of process dynamics allows to take account for the phase-shift and attenuation occurring when increasing the frequency of the dither signal. The resulting ES scheme achieves very significant improvement in convergence speed, as illustrated with a numerical example, and a more realistic application to micro-algae cultures in a photo-bioreactor in simulation.
关键词：KeywordsReal-time optimizationrecursive least squaresprocess controlbiotechnologymicro-algae