IEEE transactions on bio-medical engineering · 2026
Enhancing Prosthetic Wrist Precision With Robust $\mathcal {H}_\infty$ Control and Timoshenko Beam Modelling.
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Sulaiman Shifa, Schetter Francesco, Risi Paolino De, Gohari Mohammad, Ficuciello Fanny
Аннотация
OBJECTIVE: The creation and implementation of control strategies that govern the motions of prosthetic hands are essential for enhancing operational efficiency and user satisfaction. This paper introduces an H-infinity ($\mathcal {H}_\infty$) controller employing Timoshenko beam theory, specifically designed for a tendon-driven soft continuum wrist associated with a prosthetic hand known as 'PRISMA HAND II'. This combined approach focuses on achieving robust control that can effectively manage uncertainties and disturbances, ensuring that the prosthetic wrist responds accurately to the user's intentions.
METHODS: By employing the Timoshenko modeling approach, kinematic and dynamic models of the soft wrist are established, which are used in $\mathcal {H}_\infty$ controller to compute required tendon forces for achieving desired hand movements. These tendon forces are used for computing output deflections of the wrist.
RESULTS: The proposed controller is compared with other controllers to analyse performance of the proposed controller. The proposed $\mathcal {H}_\infty$ controller performed better compared to a Neural Network (NN) based adaptive controller in terms of Root Mean Square Error (RMSE) and steady state error values. Experimental evaluation demonstrated the controller's effectiveness in regulating wrist motions during real-time.
CONCLUSION: The implementation of the control strategy is crucial for advancing the capabilities of soft continuum prosthetics, allowing for more natural and intuitive movements that align with the needs of the user with lower computational effort and better accuracy of motions.
SIGNIFICANCE: Our study contributes to the ongoing progress in adaptable prosthetic technologies, establishing a basis for extensive use in cost-effective healthcare solutions employing an efficient controller.
METHODS: By employing the Timoshenko modeling approach, kinematic and dynamic models of the soft wrist are established, which are used in $\mathcal {H}_\infty$ controller to compute required tendon forces for achieving desired hand movements. These tendon forces are used for computing output deflections of the wrist.
RESULTS: The proposed controller is compared with other controllers to analyse performance of the proposed controller. The proposed $\mathcal {H}_\infty$ controller performed better compared to a Neural Network (NN) based adaptive controller in terms of Root Mean Square Error (RMSE) and steady state error values. Experimental evaluation demonstrated the controller's effectiveness in regulating wrist motions during real-time.
CONCLUSION: The implementation of the control strategy is crucial for advancing the capabilities of soft continuum prosthetics, allowing for more natural and intuitive movements that align with the needs of the user with lower computational effort and better accuracy of motions.
SIGNIFICANCE: Our study contributes to the ongoing progress in adaptable prosthetic technologies, establishing a basis for extensive use in cost-effective healthcare solutions employing an efficient controller.