Systems identification with fractional models using noisy input output data

This thesis deals with continuous-time system identification by fractional models in the EIV context. Two classes of methods are developed : the first class is based on third-order statistics and the second one is based on fourth-order statistics. Firstly, all differentiation orders are known a priori and only the coefficients of the differential equation are estimated using the developed algorithms based on higher-order statistics. Then, they are extended to estimate both the fractional differential equation coefficients and the commensurate order. Simulation examples display the theoretical developments on system identification in the EIV context. A practical application for modeling heat transfer phenomena in an aluminium rod and for modeling an electronic real system have shown the efficiency of the developed methods.

Data and Resources

Additional Info

Field Value
Source https://theses.hal.science/tel-00989549
Author Chetoui, Manel
Maintainer CCSD
Last Updated May 5, 2026, 11:35 (UTC)
Created May 5, 2026, 11:35 (UTC)
Identifier NNT: 2013BOR15244
Language fr
Rights https://about.hal.science/hal-authorisation-v1/
contributor Laboratoire de l'intégration, du matériau au système (IMS) ; Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux-Centre National de la Recherche Scientifique (CNRS)
creator Chetoui, Manel
date 2013-12-18T00:00:00
harvest_object_id b4697d6c-2bed-41e8-828d-759e18890f92
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2026-03-31T00:00:00
set_spec type:THESE