Shape Memory Alloys (SMAs) actuators operate via a nonlinear and hysteretic relationship between input power and mechanical motion. This nonlinearity presents a serious challenge when developing methods for controlling these actuators. Because this hysteresis and nonlinearity is caused by the crystal phase transformation however, the SMA constitutive and kinetic models can be written in Linear Parameter Varying (LPV) form, with the partial derivative of crystal phase fraction with respect to temperature as the varying parameter. This allows a SMA system to be written in a state-space format where the coefficients in the state matrices vary as a function of the state variables, allowing for the application of powerful linear system analysis tools to this model without simplifying assumptions. This LPV model can then be used to create an estimator for the system, allowing for real-time approximations of the system states, including temperature and phase fraction. This paper presents the derivation of one such LPV model and explores its ability to accurately represent a physical SMA actuator system by comparison with an instrumented SMA muscle system.
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ASME 2018 Conference on Smart Materials, Adaptive Structures and Intelligent Systems
September 10–12, 2018
San Antonio, Texas, USA
Conference Sponsors:
- Aerospace Division
ISBN:
978-0-7918-5194-4
PROCEEDINGS PAPER
Linear Parameter Varying Modeling and Estimation of a SMA Wire Actuator
Austin Gurley,
Austin Gurley
Deft Dynamics, Birmingham, AL
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Amanda Skalitzky
Amanda Skalitzky
Auburn University, Auburn, AL
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Kyle Kubik
Auburn University, Auburn, AL
Austin Gurley
Deft Dynamics, Birmingham, AL
David Beale
Auburn University, Auburn, AL
Amanda Skalitzky
Auburn University, Auburn, AL
Paper No:
SMASIS2018-8121, V001T03A023; 9 pages
Published Online:
November 14, 2018
Citation
Kubik, K, Gurley, A, Beale, D, & Skalitzky, A. "Linear Parameter Varying Modeling and Estimation of a SMA Wire Actuator." Proceedings of the ASME 2018 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. Volume 1: Development and Characterization of Multifunctional Materials; Modeling, Simulation, and Control of Adaptive Systems; Integrated System Design and Implementation. San Antonio, Texas, USA. September 10–12, 2018. V001T03A023. ASME. https://doi.org/10.1115/SMASIS2018-8121
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