Force Control of a Shape Memory Alloy Spring Actuator Based on Internal Electric Resistance Feedback and Artificial Neural Networks

References

• Asua, E., J. Feutchwanger, A. Garcia-Arribas, and V. Etxebarria. 2010. Sensorless control of sma-based actuators using neural networks. Journal of Intelligent Material Systems and Structures 21 (18):1809–1420. doi:10.1177/1045389X10388965.
   Web of Science ®Google Scholar
• Cui, D., G. Song, and H. Li. 2010. Modeling of the electrical resistance of shape memory alloy wires. Smart Materials and Structures 19 (5):5. doi:10.1088/0964-1726/19/5/055019.
   Web of Science ®Google Scholar
• Engeberg, E., S. Dilibal, M. Vatani, J. W. Choi, and J. Lavery. 2015. Anthropomorphic finger antagonistically actuated by sma plates. Bioinspiration & Biomimetics, 10. Article Number: 056002.
   Google Scholar
• Georgieva, P., and S. F. de Azevedo 2011. Neural networks for model predictive control. Proceedings of the International Joint Conference on Neural Networks, San Jose, CA, USA, 111–18.
   Google Scholar
• Hannen, J. C., J. H. Crews, and G. D. Buckner. 2012. Indirect intelligent sliding mode control of a shape memory alloy actuated flexible beam using hysteretic recurrent neural networks. Smart Materials and Structures 21 (8):8. doi:10.1088/0964-1726/21/8/085015.
   Web of Science ®Google Scholar
• Ikuta, K., M. Tsukamoto, and S. Hirose 1988. Shape memory alloy servo actuator system with electric resistance feedback and application for active endoscope. In: Proceedings. 1988 IEEE International Conference on Robotics and Automation, Philadelphia, PA, USA, p. 427–30.
   Google Scholar
• Lagoudas, D. C. 2008. Shape memory alloys: Modeling and engineering applications. New York: Springer.
   Google Scholar
• Li, J., and H. Tian. 2018. Position control of sma actuator based on inverse empirical model and smc-rbf compensation. Mechanical Systems and Signal Processing 108:203–15. doi:10.1016/j.ymssp.2018.02.004.
   Web of Science ®Google Scholar
• Ma, N., G. Song, and H. J. Lee. 2004. Position control of shape memory alloy actuators with internal electrical resistance feedback using neural networks. Smart Materials and Structures 13 (4):777–83. doi:10.1088/0964-1726/13/4/015.
   Web of Science ®Google Scholar
• Ng, W. T., M. F. Sedan, E. J. Abdullah, S. Azrad, and A. S. M. Harithuddin. 2017. Shape memory alloy resistance behaviour at high altitude for feedback control. IOP Conference Series: Materials Science and Engineering 270:012030. doi:10.1088/1757-899X/270/1/012030.
   Google Scholar
• Nikdel, N., P. Nikdel, M. A. Badamchizadeh, and I. Hassanzadeh. 2014. Using neural network model predictive control for controlling shape memory alloy-based manipulator. IEEE Transactions on Industrial Electronics 61 (3):1394–401. doi:10.1109/TIE.2013.2258292.
   Web of Science ®Google Scholar
• Novák, V., P. Šittner, G. Dayananda, F. Braz-Fernandes, and K. Mahesh. 2008. Electric resistance variation of niti shape memory alloy wires in thermomechanical tests: Experiments and simulation. Materials Science and Engineering: A 481-482 (127):133.
   Google Scholar
• Otsuka, K., and C. M. M. Wayman. 1998. Shape memory materials. New York: Cambridge University Press.
   Google Scholar
• Pan, Y., Z. Guo, X. Li, and H. Yu. 2017. Output-feedback adaptive neural control of a compliant differential sma actuator. IEEE Transactions on Control Systems Technology 25 (6):2202–10. doi:10.1109/TCST.2016.2638958.
   Web of Science ®Google Scholar
• Silva, A. F. C., D. S. Ajv, S. Cr, D. A. Cj, and D. S. Sa. 2013. Artificial biometric finger driven by shape-memory alloy wires. Artificial Organs 37:965–72. doi:10.1111/aor.12227.
   PubMed Web of Science ®Google Scholar
• Silva, A., A. Dos Santos, A. Ries, C. Souto, C. de Araújo, and S. Da Silva. 2017. Fuzzy control of a robotic finger actuated by shape memory alloy wires. Journal of Dynamic Systems, Measurement, and Control 140. Article numbers: 064502. doi:10.1115/1.4038652
   Web of Science ®Google Scholar
• Srivastava, A., C. Ward, and R. V. Patel 2017. Adaptive neural preisach model and model predictive control of shape memory alloy actuators. In: 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM), Munich, Germany, p. 1179–84.
   Google Scholar
• Zhang, J. J., Y. H. Yin, and J. Y. Zhu. 2013. Electrical resistivity-based study of self-sensing properties for shape memory alloy-actuated artificial muscle. Sensors 13 (10):12958–74. doi:10.3390/s131012958.
   PubMed Web of Science ®Google Scholar