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Proceedings Paper

Modeling and Bayesian parameter estimation for shape memory alloy bending actuators
Author(s): John H. Crews; Ralph C. Smith
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Paper Abstract

In this paper, we employ a homogenized energy model (HEM) for shape memory alloy (SMA) bending actuators. Additionally, we utilize a Bayesian method for quantifying parameter uncertainty. The system consists of a SMA wire attached to a flexible beam. As the actuator is heated, the beam bends, providing endoscopic motion. The model parameters are fit to experimental data using an ordinary least-squares approach. The uncertainty in the fit model parameters is then quantified using Markov Chain Monte Carlo (MCMC) methods. The MCMC algorithm provides bounds on the parameters, which will ultimately be used in robust control algorithms. One purpose of the paper is to test the feasibility of the Random Walk Metropolis algorithm, the MCMC method used here.

Paper Details

Date Published: 28 March 2012
PDF: 11 pages
Proc. SPIE 8342, Behavior and Mechanics of Multifunctional Materials and Composites 2012, 83421N (28 March 2012); doi: 10.1117/12.914792
Show Author Affiliations
John H. Crews, North Carolina State Univ. (United States)
Ralph C. Smith, North Carolina State Univ. (United States)


Published in SPIE Proceedings Vol. 8342:
Behavior and Mechanics of Multifunctional Materials and Composites 2012
Nakhiah C. Goulbourne; Zoubeida Ounaies, Editor(s)

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