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

2022/12/04 by Iasson Karafyllis, Karafyllis, Iasson, Tarek Ahmed Ali +1
Computer Science · Engineering · #93B53 #93C20 #FOS: Electrical engineering #FOS: Mathematics #Nonlinear Dynamics and Pattern Formation #Optimization and Control (math.OC) #Stability and Controllability of Differential Equations #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2212.01752

openalex publication_date 2022/12/04 · openalex created_date 2022/12/18 · openalex updated_date 2026/07/28

Abstract

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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