MODELING AND OPTIMAL CONTROL OF AN UPPER-LIMB BIONIC PROSTHESIS IN THE SAGITTAL PLANE

Authors

DOI:

https://doi.org/10.32782/pet-2025-2-5

Keywords:

bionic prosthesis, dynamic modeling, sagittal plane, linear -quadratic regulator, OpenSim, MATLAB

Abstract

The study investigates the modelling and optimal control of a bionic upper-limb prosthesis in the sagittal plane. The aim is to develop a mathematical model of the bionic upper limb, simulate its motion in the sagittal plane, and design a robust linear–quadratic regulator (LQR) to ensure a physiologically natural response of the elbow joint, taking into account angular position, velocity, and acceleration. To describe upper-limb motions, the Lagrangian formalism is employed, enabling derivation of the equations of motion for a two-link arm model. The system of equations is linearized in the vicinity of operating points. Methods of optimal control theory, in particular the synthesis of an LQR controller, are applied to obtain the optimal control law. Computations and simulations are carried out in MATLAB using the open biomechanical arm model from OpenSim. The work combines nonlinear dynamic modelling with a state-space approximation to develop a robust controller. The proposed approach demonstrates the feasibility of effectively reproducing physiological upper-limb movements using an LQR regulator. The obtained results show the system’s ability to maintain stability and motion accuracy even under disturbances and measurement errors, bringing it closer to biological control principles. The designed LQR controller provides stable, accurate, and energy-efficient control of the bionic upper-limb prosthesis in the sagittal plane. The proposed model can serve as a basis for prototyping high-technology bionic devices and for further studies aimed at extending the model to three-dimensional space and integrating neural or EMG signals for more natural control.

References

Hussain Z., Azlan N. Z. 3-D Dynamic Modeling and Validation of Human Arm for Torque Determination During Eating Activity Using Kane’s Method. Iranian Journal of Science and Technology. Transactions of Mechanical Engineering. 2020. Vol. 44, No. 3. DOI: https://doi.org/10.1007/s40997-019-00299-8

Davoudabadi Farahani S., Svinin M., Andersen M. S., de Zee M., Rasmussen J. Prediction of closed-chain human arm dynamics in a crank-rotation task. Journal of Biomechanics. 2016. Vol. 49, No. 13. P. 2684–2693. DOI: https://doi.org/10.1016/j.jbiomech.2016.05.034

Lemieux P. O., Tétreault P., Hagemeister N., Nuno N. Influence of prosthetic humeral head size and medial offset on the mechanics of the shoulder with cuff tear arthropathy: A numerical study. Journal of Biomechanics. 2013. Vol. 46, No. 4. P. 806–812. DOI: https://doi.org/10.1016/j.jbiomech.2012.11.021

Ali N., Andersen M. S., Rasmussen J., Robertson D. G. E., Rouhi G. The application of musculoskeletal modeling to investigate gender bias in non-contact ACL injury rate during single-leg landings. Computer Methods in Biomechanics and Biomedical Engineering. 2014. Vol. 17, No. 14. P. 1602–1616.

Rasmussen J., Torholm S., de Zee M. Computational analysis of the influence of seat pan inclination and friction on muscle activity and spinal joint forces. International Journal of Industrial Ergonomics. 2009. Vol. 39, No. 1. P. 52–57. DOI: https://doi.org/10.1016/j.ergon.2008.07.008

Rasmussen J., Holmberg L. J., Sorensen K., Kwan M., Andersen M. S., de Zee M. Performance optimization by Musculoskeletal simulation. Movement & Sport Sciences – Science & Motricité. 2012. Vol. 1, No. 75. P. 73–83.

Yamaguchi G. T. Dynamic Modelling of Musculoskeletal Motion. New York: Springer, 2006.

Hussain Z. Kane’s Method for Dynamic Modeling. Proceedings of International Conference, October 2016. P. 174–179.

Ariff F. H. M., Rambely A. S., Ghani N. A. A. Shoulder’s modeling via Kane’s method: Determination of torques in smash activity. IFMBE Proceedings. 2011. Vol. 35, No. 6. P. 207–209. DOI: https://doi.org/10.1007/978-3-642-21729-6_55

Murphy M. A., Sunnerhagen K. S., Johnels B., Willén C. Three-dimensional kinematic motion analysis of a daily activity drinking from a glass: A pilot study. Journal of NeuroEngineering and Rehabilitation. 2006. Vol. 3. P. 1–11. DOI: https://doi.org/10.1186/1743-0003-3-18

Kuo A. An optimal control model for analyzing human postural balance. IEEE Transactions on Biomedical Engineering. 1995. Vol. 42, No. 1. P. 87–101.

Golliday C., Hemami H. Postural stability of the two-degree-of-freedom biped by general linear feedback. IEEE Transactions on Biomedical Engineering. 1995. Vol. 42, No. 1. P. 102–110.

Grzelczyk D., Biesiacki P., Mrozowski J., Awrejcewicz J. A 3-link model of a human for simulating a fall in forward direction. In: Dynamical Systems in Applications. Springer, 2018. P. 845–856.

Grzelczyk D., Szymanowska O., Awrejcewicz J. Kinematic and dynamic simulation of an octopod robot controlled by different central pattern generators. Proceedings of the Institution of Mechanical Engineers. Part I: Journal of Systems and Control Engineering. 2018. Vol. 232, No. 8. P. 1011–1022.

Chadwick E. K., Blana D., Simera J. D., Lambrecht J., Kim S. P., Cornwell A. S., Taylor D. M., Hochberg L. R., Donoghue J. P., Kirsch R. F. Continuous neuronal ensemble control of simulated arm reaching by a human with tetraplegia. Journal of Neural Engineering. 2011. Vol. 8, No. 3. Article 034003. DOI: https://doi.org/10.1088/1741-2560/8/3/034003

Chadwick E. K., Blana D., Kirsch R. F., van den Bogert A. J. Real-Time Simulation of Three-Dimensional Shoulder Girdle and Arm Dynamics. IEEE Transactions on Biomedical Engineering. 2014. In press. URL: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=67554584

Brian D., Anderson O., Moore J. Optimal Control. Linear Quadratic Methods. Canberra: Prentice-Hall International, Inc., 1989. ISBN 0-13-638651-2.

Published

2025-12-30

How to Cite

ЗАМУРУЄВА, О., КРУПКО, К., САХНЮК, В., ІВАНОВСЬКИЙ, А., & ЛЕВАНДОВСЬКИЙ, В. (2025). MODELING AND OPTIMAL CONTROL OF AN UPPER-LIMB BIONIC PROSTHESIS IN THE SAGITTAL PLANE. Physics and Educational Technology, (2), 31–41. https://doi.org/10.32782/pet-2025-2-5

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