Mémoires de Fin d’Etudes
Etablissement
Université de Sétif 1 - Ferhat Abbas
Affiliation
Département d’Electronique
Auteur
DAACHI, Mohamed El Hossine
Directeur de thèse
Djamel CHIKOUCHE (Professeur)
Co-directeur
Rais El hadi BEKKA (Professeur)
Filière
Electronique
Diplôme
Doctorat
Titre
CONTRIBUTION A LA COMMANDE ET A L’IDENTIFICATION DE ROBOTS A ARCHITECTURES PARALLELES
Mots clés
Identification, adaptive control, neural networks, parallel robot, exoskeleton, stability
Résumé
In this thesis, we have addressed two aspects in relation with mechatronic systems: Identification and control. Indeed, the MLP-NN (MultiLayer Perceptron Neural Network) is used in several approaches proposed in this thesis. Note that the realized work is purely experimental. The two mechatronic systems considered are the C5 links parallel robot and the wearable robot of exoskeleton type available in the LISSI laboratory. In the first time, we have achieved an identification neural black box of the inverse dynamics of C5 parallel robot. To do this, three identification schemes were tested and compared. On the control part, we have proposed an adaptive control hybrid moment / position of C5 parallel robot directly in the task space. The task space dynamic model of the robot in contact with its environment, seen as a black box, is estimated by a MLP-NN. An adaptation algorithm of the neural parameters resulting from a closed-loop stability analysis is proposed. Another approach of control is proposed to derive the exoskeleton. In this design approach, of the adaptive control, the dynamic model is taken as a gray box. Only its structure is known. The unknown functions of the dynamic model are approximated online. The neural parameters adaptation laws are obtained via stability study in Lyapunov sense of the system in closed loop. The proposed approach is tested on a healthy person in flexion / extension of the knee
Date de soutenance
2012
Cote
TH957
Pagination
115 P
Format
CD
Statut
Soutenue