Adaptive space-time distributed parameter and input estimation in heat transport with unknown bounds

Mechhoud, Sarah; Witrant, Emmanuel; Dugard, Luc

doi:10.1109/icosc.2013.6750931

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…However, the effect of noisy measurements was not investigated. This will be addressed in our future works where the case of space-varying and time-varying parameters presented in [28,29] but using interior-point measurements will also be considered.…”

Section: Discussionmentioning

confidence: 99%

Retraction statement: Adaptive distributed parameter and input estimation in linear parabolic PDEs

Mechhoud

2016

Adaptive Control & Signal

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SUMMARYIn this paper, we discuss the on-line estimation of distributed source term, diffusion, and reaction coefficients of a linear parabolic partial differential equation using both distributed and interior-point measurements. First, new sufficient identifiability conditions of the input and the parameter simultaneous estimation are stated. Then, by means of Lyapunov-based design, an adaptive estimator is derived in the infinitedimensional framework. It consists of a state observer and gradient-based parameter and input adaptation laws. The parameter convergence depends on the plant signal richness assumption, whereas the state convergence is established using a Lyapunov approach. The results of the paper are illustrated by simulation on tokamak plasma heat transport model using simulated data.

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Section: Discussionmentioning

confidence: 99%

Retraction statement: Adaptive distributed parameter and input estimation in linear parabolic PDEs

Mechhoud

2016

Adaptive Control & Signal

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Estimation of Heat Source Term and Thermal Diffusion in Tokamak Plasmas Using a Kalman Filtering Method in the Early Lumping Approach

Mechhoud

Witrant

Dugard

et al. 2015

IEEE Trans. Contr. Syst. Technol.

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14 pagesInternational audience— In this paper, early lumping estimation of space-time varying diffusion coefficient and source term for a non-homogeneous linear parabolic partial differential equation (PDE) describing Tokamak plasma heat transport is considered. The analysis of this PDE is achieved in a finite dimensional framework using the cubic b-splines finite element method with the Galerkin formulation. This leads to a finite dimensional linear time-varying state-space model with unknown parameters and inputs. The Extended Kalman Filter with Unknown Inputs Without Direct Feed-through (EKF-UI-WDF) is applied to estimate simultaneously the unknown parameters and inputs and an adaptive fading memory coefficient is introduced in the EKF-UI-WDF, to deal with time varying parameters. Conditions under which the direct problem is well posed and the reduced order model converges to the initial one are established. Insilico and real data simulations are provided to evaluate the performances of the proposed technique

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Adaptive space-time distributed parameter and input estimation in heat transport with unknown bounds

Cited by 2 publications

References 12 publications

Retraction statement: Adaptive distributed parameter and input estimation in linear parabolic PDEs

Retraction statement: Adaptive distributed parameter and input estimation in linear parabolic PDEs

Estimation of Heat Source Term and Thermal Diffusion in Tokamak Plasmas Using a Kalman Filtering Method in the Early Lumping Approach

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