Adaptive Estimation of Time-Varying Parameters and Its Application to Time-Derivative Tracker

Wada, Shoji; Mitsunaga, Kouichi; Suemitsu, Haruo; Matsuo, Takami

doi:10.1109/sice.2006.315274

Cited by 5 publications

(1 citation statement)

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“…We demonstrate that a region of convergence of the state error can be expressed explicitly as a function of the identifiers' tuning parameters. After that, inspired by Wada et al (2006) paper, adaptive estimation of distributed time-varying input/parameter with known upper bounds is discussed. The question of input estimation is not only related to plasma heat transport but arises more generally in fault detection and inverse problems.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Distributed Parameter and Input Estimation in Plasma Tokamak Heat Transport

Mechhoud

Witrant

Dugard

et al. 2013

IFAC Proceedings Volumes

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: In this paper, the adaptive estimation of spatially varying diffusion and source term coefficients for a linear parabolic partial differential equation describing tokamak plasma heat transport is considered. An estimator is defined in the infinite-dimensional framework having the system state and the parameters' estimate as its states. Our scheme allows to estimate constant, spatially distributed and spatio-temporally distributed parameters as well as input with known upper bounds in time. While the parameters convergence depends on the plant signal richness assumption, the state convergence is established using the Lyapunov approach. Since the estimator is infinite-dimensional, the Galerkin finite-dimensional technique is used to implement it. In silico simulations are provided to illustrate the performance of the proposed approach.

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Section: Introductionmentioning

confidence: 99%