Title: Fuzzy logic-based PI controller design and implementation of shape memory alloy actuator

Authors: Yasser M. Alsayed; A.A. Abouelsoud; Ahmed M.R. Fath El Bab

Addresses: School of Innovative Design Engineering, Mechatronics and Robotics Engineering Department, Egypt-Japan University of Science and Technology (E-JUST), P.O. Box 21934, New Borg El-Arab, Alexandria, Egypt ' School of Innovative Design Engineering, Mechatronics and Robotics Engineering Department, Egypt-Japan University of Science and Technology (E-JUST), P.O. Box 21934, New Borg El-Arab, Alexandria, Egypt; Electronics and Communication Engineering Department, Faculty of Engineering, Cairo University, Egypt ' School of Innovative Design Engineering, Mechatronics and Robotics Engineering Department, Egypt-Japan University of Science and Technology (E-JUST), P.O. Box 21934, New Borg El-Arab, Alexandria, Egypt; Mechanical Engineering Department, Assiut University, Assiut, Egypt

Abstract: In this paper, a new implementation method is proposed for shape memory alloy (SMA) model which is used to design and control SMA-based linear actuator. This implementation method is based on strain-driven approach rather than stress-driven approach found in the literature. This approach removes problems associated with model implementation of SMA actuator. An algorithm reminiscent to the return mapping algorithm is used to implement the strain-driven SMA model. A dynamic system that describes the characteristics of one-way bias force-based SMA actuator is simulated using this implementation approach. An adaptive fuzzy logic-based PI controller is designed to tune PI controller gains. The proposed controller shows superior response over existing controllers of SMA wire actuators found in the literature in terms of zero steady state error, no overshoot and reduced hysteresis.

Keywords: shape memory alloy; SMA; actuators; linear actuator; hysteresis characteristics; austenite phase fraction; martensite phase fraction; stress-driven approach; strain-driven approach; adaptive fuzzy logic PI controller.

DOI: 10.1504/IJAAC.2018.092851

International Journal of Automation and Control, 2018 Vol.12 No.3, pp.427 - 448

Received: 02 Dec 2016
Accepted: 03 Mar 2017
Published online: 01 Jul 2018 *

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