arXiv 2212.017522022-12-04math.OCcs.SYeess.SY

Sampled-Data Observer Design for Linear Kuramoto-Sivashinsky Systems with Non-Local Output

Iasson Karafyllis, Tarek Ahmed Ali

备注：: 11 pages, 1 figure, submitted to Automatica for possible publication

英文摘要：

The aim of this paper is to provide a novel systematic methodology for the design of sampled-data observers for Linear Kuramoto-Sivashinsky systems (LK-S) with non-local outputs. More precisely, we extend the systematic sampled-data observer design approach which is based on the use of an Inter-Sample output predictor to the class of LK-S systems. By using a small-gain methodology we provide sufficient conditions ensuring the Input-to-Output Stability (IOS) property of the estimation errors in the presence of measurement noise. Our Inter-Sample output predictor contains a tuning term which can enlarge significantly the Maximum Allowable Sampling Period (MASP).

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