Work

Active Disturbance Rejection Control via Neural Networks for a Lower-Limb Exoskeleton

Year: 2024

Type: article

Abstract: This article presents the design of a control algorithm based on Artificial Neural Networks (ANNs) applied to a lower-limb exoskeleton, which is aimed to carry out walking trajectories during lower-limb rehabilitation. The interaction between the patient and the exoskeleton leads to model uncertainties and external disturbances that are always present. For this reason, the proposed control considers that the non-linear part of the model is unknown and is perturbed by external disturbances, which are estimated by an active disturbance rejection control via Artificial Neural Networks. To validate the proposed approach, a numerical simulation and an experimental implementation of the ANN-Controller are developed.

Source: Sensors

DOI: 10.3390/s24206546

Authors: Karina I. Espinosa-Espejel, Yukio Rosales-Luengas, Sergio Salazar, Ricardo Lopéz-Gutiérrez, Rogelio Lozano

Institutions: Instituto Politécnico Nacional, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Secretaría de Ciencia, Humanidades, Tecnología e Innovación

Language: English

Topic: Prosthetics and Rehabilitation Robotics

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,955