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Development of Hybrid Prandtl–Ishlinskii and Constitutive Models for Hysteresis of Shape-Memory-Alloy-Driven Actuators

Published online by Cambridge University Press:  04 February 2021

Saeid Shakiba
Affiliation:
PhD Candidate, Center of Advanced Systems and Technologies (CAST), School of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, Iran
Moosa Ayati*
Affiliation:
Associate Professor, School of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, Iran
Aghil Yousefi-Koma
Affiliation:
Professor, Center of Advanced Systems and Technologies (CAST), School of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, Iran
*
*Corresponding author. E-mail: m.ayati@ut.ac.ir

Summary

Prandtl–Ishlinskii (PI) model has an excellent compromise to characterize an asymmetric saturated hysteresis behavior of shape-memory-alloy (SMA)-driven systems, but it cannot consider thermomechanical relations between components of SMA-driven systems. On the other hand, constitutive models are composed of these relations, but their precision needs to be improved. In this paper, PI model is proposed to boost constitutive models in two cases. In the first case, PI model is used to characterize martensite volume fraction (MVF) called hybrid model. In the second case, the model is applied as a regulator in the output of a constitutive model called PI-based output (PIO) regulator. Due to simplicity and ability of Liang–Rogers (LR) model in transformation phases, it is considered as an MVF in the original constitutive model. The performance of both proposed models is compared with the original LR-based constitutive model. Unknown parameters of all three models are identified using genetic algorithm in MATLAB Toolbox. The performance of the three models is investigated at three different frequencies of \[\frac{{2\pi }}{8}\], \[\frac{{2\pi }}{{15}}\], and \[\frac{{2\pi }}{{30}}\] Hz because the excitation frequency changes the hysteresis behavior. Results show that the proposed hybrid model keeps the precision of the original constitutive model at different frequencies. In addition, the proposed PIO model shows the best performance to predict hysteresis behavior at different frequencies.

Type
Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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