Temperature Estimation of Thin Shape Memory Alloy Springs in a Small-Scale Hip Exoskeleton with System Identification and Adaptive Control

This study presents a small-scale hip exoskeleton incorporating bi-directional artificial muscles constructed with springs of Shape Memory Alloy (SMA). The prototype can effectively support hip motion in both extension and flexion, spanning an angular range of −20° to 200°. Experiments for thermo-mechanical characterization were executed to assess the performance of the SMA muscles throughout the entire motion range. The outcomes not only confirmed the suitability of the SMA muscles for the designed exoskeleton but also provided valuable insights into their behavior and capabilities. System identification experiments were carried out to establish an accurate transfer function, guiding the tuning of Proportional-Integral-Derivative (PID) controllers for enhanced motion-control effectiveness. The safety of the SMA system was addressed with a focus on preventing overheating. Challenges in accurately measuring the temperature of a thin spring were overcome by utilizing two thermocouples for each SMA springs group. Additionally, conventional SMA temperature measurement methods, such as infrared and resistance-based techniques, are limited by high cost, nonlinearity, and small range. This study presents a model-based temperature estimation algorithm that integrates a heat transfer model, electrical input data, and thermocouple data to enable accurate and real-time SMA temperature estimation without additional sensors, offering a cost-effective and reliable alternative. To evaluate the small hip prototype and its controller capabilities, control experiments were executed for both stepping and sinusoidal trajectories. The exoskeleton successfully tracked the desired trajectories, showing its precision. Moreover, system performance under adaptive control was further investigated, revealing an RMSE of 0.94° in sinusoidal trajectory experiments, indicating reliable disturbance rejection in the angle measurements.

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Publication Details

Journal
Actuators
Published
2026-01-03
DOI
https://doi.org/10.3390/act15010026
Primary Topic
Prosthetics and Rehabilitation Robotics
Type
article
Field-Weighted Citation Impact
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article

Temperature Estimation of Thin Shape Memory Alloy Springs in a Small-Scale Hip Exoskeleton with System Identification and Adaptive Control

Shuaiby Mohamed, Y. J. Kim, Ejaz Ahmad, Hussein F. M. Ali
Actuators
Prosthetics and Rehabilitation Robotics
article

Temperature Estimation of Thin Shape Memory Alloy Springs in a Small-Scale Hip Exoskeleton with System Identification and Adaptive Control

Shuaiby Mohamed, Y. J. Kim, Ejaz Ahmad, Hussein F. M. Ali
article en

Abstract

This study presents a small-scale hip exoskeleton incorporating bi-directional artificial muscles constructed with springs of Shape Memory Alloy (SMA). The prototype can effectively support hip motion in both extension and flexion, spanning an angular range of −20° to 200°. Experiments for thermo-mechanical characterization were executed to assess the performance of the SMA muscles throughout the entire motion range. The outcomes not only confirmed the suitability of the SMA muscles for the designed exoskeleton but also provided valuable insights into their behavior and capabilities. System identification experiments were carried out to establish an accurate transfer function, guiding the tuning of Proportional-Integral-Derivative (PID) controllers for enhanced motion-control effectiveness. The safety of the SMA system was addressed with a focus on preventing overheating. Challenges in accurately measuring the temperature of a thin spring were overcome by utilizing two thermocouples for each SMA springs group. Additionally, conventional SMA temperature measurement methods, such as infrared and resistance-based techniques, are limited by high cost, nonlinearity, and small range. This study presents a model-based temperature estimation algorithm that integrates a heat transfer model, electrical input data, and thermocouple data to enable accurate and real-time SMA temperature estimation without additional sensors, offering a cost-effective and reliable alternative. To evaluate the small hip prototype and its controller capabilities, control experiments were executed for both stepping and sinusoidal trajectories. The exoskeleton successfully tracked the desired trajectories, showing its precision. Moreover, system performance under adaptive control was further investigated, revealing an RMSE of 0.94° in sinusoidal trajectory experiments, indicating reliable disturbance rejection in the angle measurements.

ActuatorsVol. 15(1)
Hanbat National University (KR), Benha University (EG), Kyungdong University (KR), Assiut University (EG)
Affordable and clean energy
Openalex Percentile: Top 97%
Prosthetics and Rehabilitation Robotics
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