Identification of internal properties of fibres and micro-swimmers
Author(s) -
Franck Plouraboué,
E. Ibrahima Thiam,
Blaise Delmotte,
Éric Climent
Publication year - 2017
Publication title -
proceedings of the royal society a mathematical physical and engineering sciences
Language(s) - English
Resource type - Journals
eISSN - 1471-2946
pISSN - 1364-5021
DOI - 10.1098/rspa.2016.0517
Subject(s) - identifiability , forcing (mathematics) , identification (biology) , estimator , convergence (economics) , kinematics , mathematics , gaussian , constraint (computer aided design) , noise (video) , parameter identification problem , computer science , mathematical optimization , physics , mathematical analysis , classical mechanics , model parameter , artificial intelligence , statistics , geometry , botany , quantum mechanics , economics , image (mathematics) , biology , economic growth
In this paper, we address the identifiability of constitutive parameters of passive or active micro-swimmers. We first present a general framework for describing fibres or micro-swimmers using a bead-model description. Using a kinematic constraint formulation to describe fibres, flagellum or cilia, we find explicit linear relationship between elastic constitutive parameters and generalized velocities from computing contact forces. This linear formulation then permits one to address explicitly identifiability conditions and solve for parameter identification. We show that both active forcing and passive parameters are both identifiable independently but not simultaneously. We also provide unbiased estimators for generalized elastic parameters in the presence of Langevin-like forcing with Gaussian noise using a Bayesian approach. These theoretical results are illustrated in various configurations showing the efficiency of the proposed approach for direct parameter identification. The convergence of the proposed estimators is successfully tested numerically
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