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Fast and Globally Convergent Nonlinear System Model for 3D Magnetostrictive Systems

[+] Author Affiliations
Hafez Tari, Marcelo J. Dapino

Ohio State University, Columbus, OH

Paper No. SMASIS2014-7714, pp. V001T03A040; 11 pages
doi:10.1115/SMASIS2014-7714
From:
  • ASME 2014 Conference on Smart Materials, Adaptive Structures and Intelligent Systems
  • Volume 1: Development and Characterization of Multifunctional Materials; Modeling, Simulation and Control of Adaptive Systems; Structural Health Monitoring; Keynote Presentation
  • Newport, Rhode Island, USA, September 8–10, 2014
  • Conference Sponsors: Aerospace Division
  • ISBN: 978-0-7918-4614-8
  • Copyright © 2014 by ASME

abstract

A globally convergent and fully coupled magnetomechanical model for 3D magnetostrictive systems is presented. In magnetostrictive actuators, magnetic field and stress inputs generate magnetic flux density and strain. We refer to models that follow this scheme as direct models (no relation to the direct magnetomechanical effect). In certain design and control situations, inverse models are necessary in which the magnetic field and stress are found from specified magnetic flux density and strains. This inversion typically involves an iterative procedure, which may be prone to convergence issues. An inverse model approach is proposed for arbitrary magnetostrictive materials. The inversion requirement is a continuous and second order differentiable direct model for any chosen magnetostrictive material. The approach is globally convergent, which makes it ideal for use in finite element frameworks. The premise of the proposed iterative system model is to constitute a recursive correction formula based on second order approximations of a novel scalar error function which allows to achieve a faster convergence rate. A continuation approach is then used to achieve global convergence for arbitrary input parameters. To illustrate, Galfenol is chosen as the magnetostrictive material, and analytical derivations of the Jacobian and Hessian matrices are presented. Finally, the computational efficiency of the proposed approach is shown to compare favorably against existing models.

Copyright © 2014 by ASME

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