Using a Shape Memory Alloy (SMA) actuator as both an actuator and a sensor provides huge benefits in cost reduction and miniaturization of robotic devices. Despite much effort, reliable and robust self-sensing (using the actuator as a position sensor) has not been achieved for general temperature, loading, hysteresis path, and fatigue conditions. Prior research has sought to model the intricacies of the electrical resistivity changes within the NiTi material. However, for the models to be solvable, nearly every previous technique only models the actuator within very specific boundary conditions. Here, we measure both the voltage across the entire NiTi wire and of a fixed-length segment of it; these dual measurements allow direct calculation of the actuator length without a material model. We review previous self-sensing literature, illustrate the mechanism design that makes the new technique possible, and use the dual measurement technique to determine the length of a single straight wire actuator under controlled conditions. This robust measurement can be used for feedback control in unknown ambient and loading conditions.
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ASME 2016 Conference on Smart Materials, Adaptive Structures and Intelligent Systems
September 28–30, 2016
Stowe, Vermont, USA
Conference Sponsors:
- Aerospace Division
ISBN:
978-0-7918-5049-7
PROCEEDINGS PAPER
Robust Self-Sensing in NiTi Actuators Using a Dual Measurement Technique
Austin Gurley,
Austin Gurley
Auburn University, Auburn, AL
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Tyler Ross Lambert,
Tyler Ross Lambert
Auburn University, Auburn, AL
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Royall Broughton
Royall Broughton
Auburn University, Auburn, AL
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Austin Gurley
Auburn University, Auburn, AL
Tyler Ross Lambert
Auburn University, Auburn, AL
David Beale
Auburn University, Auburn, AL
Royall Broughton
Auburn University, Auburn, AL
Paper No:
SMASIS2016-9242, V002T03A022; 7 pages
Published Online:
November 29, 2016
Citation
Gurley, A, Lambert, TR, Beale, D, & Broughton, R. "Robust Self-Sensing in NiTi Actuators Using a Dual Measurement Technique." Proceedings of the ASME 2016 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. Volume 2: Modeling, Simulation and Control; Bio-Inspired Smart Materials and Systems; Energy Harvesting. Stowe, Vermont, USA. September 28–30, 2016. V002T03A022. ASME. https://doi.org/10.1115/SMASIS2016-9242
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