Approximation and identification of diffusive interfaces by fractional models

DOI10.1016/j.sigpro.2006.02.025zbMath1172.93398OpenAlexW1986685163MaRDI QIDQ1031345

A. Benchellal, Jean-Claude Trigeassou, Thierry Poinot

Publication date: 29 October 2009

Published in: Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.sigpro.2006.02.025

zbMATH Keywords

estimationmodellingheat transferfractional operatorfractional systemsdiffusive interfacesnon-integer systemsoutput-error identification

Mathematics Subject Classification ID

Estimation and detection in stochastic control theory (93E10)

Related Items

Identification of Multivariable Fractional Order Systems, Vector Fitting fractional system identification using particle swarm optimization, Optimal low order model identification of fractional dynamic systems, Order and pole locator estimation in fractional order systems using bode diagram, Fractional modelling and identification of thermal systems, Time-step heat problem on the mesh: asymptotic behavior and decay rates, Step response-based identification of fractional order time delay models, Initialization of a fractional order identification algorithm applied for Lithium-ion battery modeling in time domain, Analysis and description of the infinite-dimensional nature for nabla discrete fractional order systems, Periodic boundary value problems for semilinear fractional differential equations, Identification of neuro-fractional Hammerstein systems: a hybrid frequency-/time-domain approach, The role of fractional calculus in modeling biological phenomena: a review, Estimation of thermal parameters using fractional modelling, Fractional order calculus: basic concepts and engineering applications, Approximation of high order integer systems by fractional order reduced-parameters models, Generalization of order distribution concept use in the fractional order system identification, Fault detection based on fractional order models: application to diagnosis of thermal systems, Emerging Tools for Quantifying Unconscious Analgesia: Fractional-Order Impedance Models