Adaptive observer for the joint estimation of parameters and input for a coupled wave PDE and infinite dimensional ODE system
Adaptive observer for the joint estimation of parameters and input for a coupled wave PDE and infinite dimensional ODE system
This paper deals with joint parameters and input estimation for coupled PDE-ODE system. The system consists of a damped wave equation and an infinite dimensional ODE. This model describes the spatiotemporal hemodynamic response in the brain and the objective is to characterize brain regions using functional Magnetic Resonance Imaging (fMRI) data. For this reason, we propose an adaptive estimator and prove the asymptotic convergence of the state, the unknown input and the unknown parameters. The proof is based on a Lyapunov approach combined with a priori identifiability assumptions. The performance of the proposed observer is illustrated through some simulation results.
3435-3440
Belkhatir, Zehor
de90d742-a58f-4425-837c-20ff960fb9b6
Mechhoud, Sarah
d1eecaa6-8c67-44cf-b4c0-7e187709dff1
Laleg-Kirati, Taous-Meriem
0363864e-a21e-44ed-9c9d-f43f3491b758
6 July 2016
Belkhatir, Zehor
de90d742-a58f-4425-837c-20ff960fb9b6
Mechhoud, Sarah
d1eecaa6-8c67-44cf-b4c0-7e187709dff1
Laleg-Kirati, Taous-Meriem
0363864e-a21e-44ed-9c9d-f43f3491b758
Belkhatir, Zehor, Mechhoud, Sarah and Laleg-Kirati, Taous-Meriem
(2016)
Adaptive observer for the joint estimation of parameters and input for a coupled wave PDE and infinite dimensional ODE system.
In 2016 American Control Conference (ACC).
IEEE.
.
(doi:10.1109/ACC.2016.7525445).
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Conference or Workshop Item
(Paper)
Abstract
This paper deals with joint parameters and input estimation for coupled PDE-ODE system. The system consists of a damped wave equation and an infinite dimensional ODE. This model describes the spatiotemporal hemodynamic response in the brain and the objective is to characterize brain regions using functional Magnetic Resonance Imaging (fMRI) data. For this reason, we propose an adaptive estimator and prove the asymptotic convergence of the state, the unknown input and the unknown parameters. The proof is based on a Lyapunov approach combined with a priori identifiability assumptions. The performance of the proposed observer is illustrated through some simulation results.
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Published date: 6 July 2016
Venue - Dates:
2016 American Control Conference, ACC 2016, , Boston, United States, 2016-07-06 - 2016-07-08
Identifiers
Local EPrints ID: 513528
URI: https://eprints.soton.ac.uk/id/eprint/513528
PURE UUID: ae538e4b-3079-440d-af4e-3aebac144e7c
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Date deposited: 19 Aug 2026 16:44
Last modified: 13 Sep 2026 15:50
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Contributors
Author:
Zehor Belkhatir
Author:
Sarah Mechhoud
Author:
Taous-Meriem Laleg-Kirati
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