Izvorni znanstveni članak
https://doi.org/10.32985/ijeces.17.9.6
Adaptive Control of a Lower-Limb Prosthesis Using a Momentum Observer and PSO-Based Gain Optimization
Ahmed Qaftan Kafi
; University of Technology, College of Control and Systems Engineering, Iraq.
*
Muayed Sadik Croock
; University of Technology, College of Control and Systems Engineering, Iraq.
Qusay Fadhel Hasan
; University of Technology, College of Control and Systems Engineering, Iraq.
* Dopisni autor.
Sažetak
The number of individuals who live with limb loss has increased worldwide. Individuals with limb loss face significant daily challenges in independent mobility and functional activities. A primary technical barrier in modern active prostheses is the effective management of Ground Reaction Force (GRF), which introduces unpredictable disturbances during the gait cycle and complicates control due to nonlinear dynamics. This research addresses the need for a control framework that can simultaneously compensate for unknown GRF-related disturbances and manage nonlinear prosthetic dynamics. The study proposes an adaptive control framework for a 2-Degree-of-Freedom (DOF) lower-limb prosthesis, integrating a computed-torque-based adaptive controller with a generalized momentum observer for GRF estimation. To enhance performance, Particle Swarm Optimization (PSO) was employed to tune the controller and observer gains, replacing traditional trial-and-error methods. Simulations were conducted in MATLAB/SIMULINK using realistic disturbances derived from the GAITREC GRF dataset. Results demonstrate that PSO-based tuning significantly improved tracking accuracy, reducing Root Mean Square (RMS) tracking errors by 47% at the knee and 94% at the ankle compared to manual tuning. Additionally, GRF estimation errors were reduced by 57% and 48% for the knee and ankle, respectively. Comparative analysis shows that the proposed PSO approach provides superior global search capabilities and convergence stability over previous bio-inspired methods such as the Bat Algorithm(BA). While the framework offers a robust, data-independent solution for various locomotion scenarios, it is currently limited by its simplified 2-DOF model and lack of real-time validation. Future research should focus on implementing the controller in physical hardware to verify its performance and safety in real-world environments.
Ključne riječi
Lower limb prosthesis; adaptive control; PSO optimization; disturbance observer; ground reaction force; Lyapunov theory;
Hrčak ID:
352143
URI
Datum izdavanja:
14.10.2026.
Posjeta: 0 *