Vanadium dioxide (VO2)-coated silicon dioxide microactuators demonstrate fully reversible actuation, large bending and high energy density. To better utilize its actuation potential while minimizing the cost in obtaining sensory feedback, a novel composite hysteresis model is presented to obtain the deflection feedback based on the resistance measurement. In this model the deflection is obtained from the voltage value through a generalized Prandtl-Ishlinskii model, while the voltage in turn is calculated based on the resistance measurement through the analytical inverse of another generalized Prandtl-Ishlinskii model. For comparison purposes, a Preisach model and a polynomial model, respectively, are adopted to estimate the deflection based on resistance measurement directly. Experimental results show that, for a 550 μm long VO2-based microactuator, the average absolute errors of the self-sensing schemes based on the composite model, the Preisach model, and the polynomial model are 0.554 μm, 1.232 μm, and 2.898 μm, respectively, over the deflection range of [−0.2, 102.9] μm. The composite model also shows advantages over the Preisach model in terms of the calculation time needed in deflection estimation. In addition, in separate verification experiments, the error resulted from the composite model-based self-sensing scheme is only 60% and 40 % of those under the schemes using the Preisach model and the polynomial model, respectively.
- Dynamic Systems and Control Division
A Hysteresis-Compensated Self-Sensing Scheme for Vanadium Dioxide-Coated Microactuators
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Zhang, J, Torres, D, Merced, E, Sepúlveda, N, & Tan, X. "A Hysteresis-Compensated Self-Sensing Scheme for Vanadium Dioxide-Coated Microactuators." Proceedings of the ASME 2014 Dynamic Systems and Control Conference. Volume 3: Industrial Applications; Modeling for Oil and Gas, Control and Validation, Estimation, and Control of Automotive Systems; Multi-Agent and Networked Systems; Control System Design; Physical Human-Robot Interaction; Rehabilitation Robotics; Sensing and Actuation for Control; Biomedical Systems; Time Delay Systems and Stability; Unmanned Ground and Surface Robotics; Vehicle Motion Controls; Vibration Analysis and Isolation; Vibration and Control for Energy Harvesting; Wind Energy. San Antonio, Texas, USA. October 22–24, 2014. V003T45A006. ASME. https://doi.org/10.1115/DSCC2014-6222
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