Robust Control of Shape Memory Alloys for Assistive Robotics Applications

Thilina H. Weerakkody; Elio Matteo Curcio; Giuseppe Carbone; Carmine Maletta; Emanuele Sgambitterra; Caterina Lamuta

doi:10.1007/s40830-025-00596-z

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Robust Control of Shape Memory Alloys for Assistive Robotics Applications

Journal article

Open access

Peer reviewed

Robust Control of Shape Memory Alloys for Assistive Robotics Applications

Thilina H. Weerakkody, Elio Matteo Curcio, Giuseppe Carbone, Carmine Maletta, Emanuele Sgambitterra and Caterina Lamuta

Shape memory and superelasticity : advances in science and technology, Vol.12(1), pp.119-137

03/2026

DOI: 10.1007/s40830-025-00596-z

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Abstract

Shape Memory Alloys (SMAs) are a popular class of actuators widely used in complex soft robotics applications due to their shape memory effect, high recoverable strain, and stress. However, most existing actuation models frequently fail to accurately capture hysteresis and dynamic loading behavior while remaining computationally efficient. Moreover, current control strategies often lack adaptability, robustness, and the ability to generalize to varying system dynamics. This paper presents a robust adaptive closed-loop controller for electro-thermally actuated Ni-Ti SMAs, developed based on a Finite State Machine framework to address these challenges. The proposed controller is designed to compensate for disturbances and uncertainties in the SMA behavior. Experimental validation and statistical analysis have demonstrated the effectiveness of the L-1 adaptive controller across various SMA configurations, enabling precise strain and stress target tracking. Finally, the controller is deployed to a case study involving a Ni-Ti SMA-powered assistive robotic device, where it successfully manages position tracking with enhanced performance.

Materials Science

Technology

Materials Science, Multidisciplinary

Science & Technology

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Details

Title: Subtitle: Robust Control of Shape Memory Alloys for Assistive Robotics Applications
Creators: Thilina H. Weerakkody - University of Iowa
Elio Matteo Curcio - University of Calabria
Giuseppe Carbone - University of Calabria
Carmine Maletta - University of Calabria
Emanuele Sgambitterra - University of Calabria
Caterina Lamuta - University of Iowa, Mechanical Engineering
Resource Type: Journal article
Publication Details: Shape memory and superelasticity : advances in science and technology, Vol.12(1), pp.119-137
DOI: 10.1007/s40830-025-00596-z
ISSN: 2199-384X
eISSN: 2199-3858
Publisher: Springer Nature
Number of pages: 19
Grant note: Smart Multifunctional Material Systems Lab (SMMS) at the University of Iowa, IA, USA
Language: English
Electronic publication date: 12/02/2025
Date published: 03/2026
Academic Unit: Roy J. Carver Department of Biomedical Engineering; Mechanical Engineering
Record Identifier: 9985091363902771

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