State observers of a vascular fluid-structure interaction model through measurements in the solid

被引:11
作者
Bertoglio, C. [1 ]
Chapelle, D. [2 ]
Fernandez, M. A. [1 ]
Gerbeau, J. -F. [1 ]
Moireau, P. [2 ]
机构
[1] Inria Paris Rocquencourt, Project Team Reo, Paris, France
[2] Inria Paris Rocquencourt, Project Team Macs, Paris, France
关键词
Estimation; Observers; Fluid-structure interaction; Hemodynamics; PARAMETER-ESTIMATION; JOINT STATE; STABILIZATION; ALGORITHMS; SIMULATION; STABILITY; TISSUE;
D O I
10.1016/j.cma.2012.12.010
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
We analyze the performances of two types of Luenberger observers - namely, the so-called Direct Velocity Feedback and Schur Displacement Feedback procedures, originally devised for elasto-dynamics - to estimate the state of a fluid-structure interaction model for hemodynamics, when the measurements are assumed to be restricted to displacements or velocities in the solid. We first assess the observers using hemodynamics-inspired test problems with the complete model, including the Navier-Stokes equations in Arbitrary Lagrangian-Eulerian formulation, in particular. Then, in order to obtain more detailed insight we consider several well-chosen simplified models, each of which allowing a thorough analysis - emphasizing spectral considerations - while illustrating a major phenomenon of interest for the observer performance, namely, the added mass effect for the structure, the coupling with a lumped-parameter boundary condition model for the fluid flow, and the fluid dynamics effect per se. Whereas improvements can be sought when additional measurements are available in the fluid domain in order to more effectively deal with strong uncertainties in the fluid state, in the present framework this establishes Luenberger observer methods as very attractive strategies - compared, e.g., to classical variational techniques - to perform state estimation, and more generally for uncertainty estimation since other observer procedures can be conveniently combined to estimate uncertain parameters. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:149 / 168
页数:20
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