Active Disturbance Rejection Control via Neural Networks for a Lower-Limb Exoskeleton
Karina I. Espinosa-Espejel,
Yukio Rosales-Luengas,
Sergio Salazar,
Ricardo Lopéz-Gutiérrez,
Rogelio Lozano
Affiliations
Karina I. Espinosa-Espejel
Department of Research and Multidisciplinary Studies, Center for Research and Advanced Studies of the National Polytechnic Institute, Mexico City 07360, Mexico
Yukio Rosales-Luengas
Department of Research and Multidisciplinary Studies, Center for Research and Advanced Studies of the National Polytechnic Institute, Mexico City 07360, Mexico
Sergio Salazar
Department of Research and Multidisciplinary Studies, Center for Research and Advanced Studies of the National Polytechnic Institute, Mexico City 07360, Mexico
Ricardo Lopéz-Gutiérrez
CONAHCYT-INAOEP, San Andrés Cholula 72840, Mexico
Rogelio Lozano
Department of Research and Multidisciplinary Studies, Center for Research and Advanced Studies of the National Polytechnic Institute, Mexico City 07360, Mexico
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.
