Sampled-Data Observers for 1-D Parabolic PDEs with Non-Local Outputs

Fuente: arXiv
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Main Authors: Karafyllis, Iasson, Ahmed-Ali, Tarek, Giri, Fouad
Format: Preprint
Published: 2019
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author Karafyllis, Iasson
Ahmed-Ali, Tarek
Giri, Fouad
author_facet Karafyllis, Iasson
Ahmed-Ali, Tarek
Giri, Fouad
contents The present work provides a systematic approach for the design of sampled-data observers to a wide class of 1-D, parabolic PDEs with non-local outputs. The studied class of parabolic PDEs allows the presence of globally Lipschitz nonlinear and non-local terms in the PDE. Two different sampled-data observers are presented: one with an inter-sample predictor for the unavailable continuous measurement signal and one without an inter-sample predictor. Explicit conditions on the upper diameter of the (uncertain) sampling schedule for both designs are derived for exponential convergence of the observer error to zero in the absence of measurement noise and modeling errors. Moreover, explicit estimates of the convergence rate can be deduced based on the knowledge of the upper diameter of the sampling schedule. When measurement noise and/or modeling errors are present, Input-to-Output Stability (IOS) estimates of the observer error hold for both designs with respect to noise and modeling errors. The main results are illustrated by two examples which show how the proposed methodology can be extended to other cases (e.g., boundary point measurements).
format Preprint
id arxiv_https___arxiv_org_abs_1901_02434
institution arXiv
publishDate 2019
record_format arxiv
spellingShingle Sampled-Data Observers for 1-D Parabolic PDEs with Non-Local Outputs
Karafyllis, Iasson
Ahmed-Ali, Tarek
Giri, Fouad
Optimization and Control
Systems and Control
The present work provides a systematic approach for the design of sampled-data observers to a wide class of 1-D, parabolic PDEs with non-local outputs. The studied class of parabolic PDEs allows the presence of globally Lipschitz nonlinear and non-local terms in the PDE. Two different sampled-data observers are presented: one with an inter-sample predictor for the unavailable continuous measurement signal and one without an inter-sample predictor. Explicit conditions on the upper diameter of the (uncertain) sampling schedule for both designs are derived for exponential convergence of the observer error to zero in the absence of measurement noise and modeling errors. Moreover, explicit estimates of the convergence rate can be deduced based on the knowledge of the upper diameter of the sampling schedule. When measurement noise and/or modeling errors are present, Input-to-Output Stability (IOS) estimates of the observer error hold for both designs with respect to noise and modeling errors. The main results are illustrated by two examples which show how the proposed methodology can be extended to other cases (e.g., boundary point measurements).
title Sampled-Data Observers for 1-D Parabolic PDEs with Non-Local Outputs
topic Optimization and Control
Systems and Control
url https://arxiv.org/abs/1901.02434