Distributed Parameter State Estimation for the Gray–Scott Reaction-Diffusion Model

A constructive approach is provided for the reconstruction of stationary and non-stationary patterns in the one-dimensional Gray-Scott model, utilizing measurements of the system state at a finite number of locations. Relations between the parameters of the model and the density of the sensor locati...

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Main Authors: Petro Feketa, Alexander Schaum, Thomas Meurer
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Systems
Subjects:
Online Access:https://www.mdpi.com/2079-8954/9/4/71
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author Petro Feketa
Alexander Schaum
Thomas Meurer
author_facet Petro Feketa
Alexander Schaum
Thomas Meurer
author_sort Petro Feketa
collection DOAJ
description A constructive approach is provided for the reconstruction of stationary and non-stationary patterns in the one-dimensional Gray-Scott model, utilizing measurements of the system state at a finite number of locations. Relations between the parameters of the model and the density of the sensor locations are derived that ensure the exponential convergence of the estimated state to the original one. The designed observer is capable of tracking a variety of complex spatiotemporal behaviors and self-replicating patterns. The theoretical findings are illustrated in particular numerical case studies. The results of the paper can be used for the synchronization analysis of the master–slave configuration of two identical Gray–Scott models coupled via a finite number of spatial points and can also be exploited for the purposes of feedback control applications in which the complete state information is required.
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spelling doaj.art-9c8122ef6ed54a288238a4e82dda92622023-11-23T10:47:29ZengMDPI AGSystems2079-89542021-10-01947110.3390/systems9040071Distributed Parameter State Estimation for the Gray–Scott Reaction-Diffusion ModelPetro Feketa0Alexander Schaum1Thomas Meurer2Automation and Control Group, Kiel University, 24143 Kiel, GermanyAutomation and Control Group, Kiel University, 24143 Kiel, GermanyAutomation and Control Group, Kiel University, 24143 Kiel, GermanyA constructive approach is provided for the reconstruction of stationary and non-stationary patterns in the one-dimensional Gray-Scott model, utilizing measurements of the system state at a finite number of locations. Relations between the parameters of the model and the density of the sensor locations are derived that ensure the exponential convergence of the estimated state to the original one. The designed observer is capable of tracking a variety of complex spatiotemporal behaviors and self-replicating patterns. The theoretical findings are illustrated in particular numerical case studies. The results of the paper can be used for the synchronization analysis of the master–slave configuration of two identical Gray–Scott models coupled via a finite number of spatial points and can also be exploited for the purposes of feedback control applications in which the complete state information is required.https://www.mdpi.com/2079-8954/9/4/71Gray–Scott modelobserver designpattern formationreaction diffusion equations
spellingShingle Petro Feketa
Alexander Schaum
Thomas Meurer
Distributed Parameter State Estimation for the Gray–Scott Reaction-Diffusion Model
Systems
Gray–Scott model
observer design
pattern formation
reaction diffusion equations
title Distributed Parameter State Estimation for the Gray–Scott Reaction-Diffusion Model
title_full Distributed Parameter State Estimation for the Gray–Scott Reaction-Diffusion Model
title_fullStr Distributed Parameter State Estimation for the Gray–Scott Reaction-Diffusion Model
title_full_unstemmed Distributed Parameter State Estimation for the Gray–Scott Reaction-Diffusion Model
title_short Distributed Parameter State Estimation for the Gray–Scott Reaction-Diffusion Model
title_sort distributed parameter state estimation for the gray scott reaction diffusion model
topic Gray–Scott model
observer design
pattern formation
reaction diffusion equations
url https://www.mdpi.com/2079-8954/9/4/71
work_keys_str_mv AT petrofeketa distributedparameterstateestimationforthegrayscottreactiondiffusionmodel
AT alexanderschaum distributedparameterstateestimationforthegrayscottreactiondiffusionmodel
AT thomasmeurer distributedparameterstateestimationforthegrayscottreactiondiffusionmodel